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  • 1.
    Aghanavesi, Somayeh
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Memedi, Mevludin
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Nyholm, Dag
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Verification of a method for measuring Parkinson’s disease related temporal irregularity in spiral drawings2017In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 17, no 10, article id 2341Article in journal (Refereed)
    Abstract [en]

    Parkinson's disease (PD) is a progressive movement disorder caused by the death of dopamine-producing cells in the midbrain. There is a need for frequent symptom assessment, since the treatment needs to be individualized as the disease progresses. The aim of this paper was to verify and further investigate the clinimetric properties of an entropy-based method for measuring PD-related upper limb temporal irregularities during spiral drawing tasks. More specifically, properties of a temporal irregularity score (TIS) for patients at different stages of PD, and medication time points were investigated. Nineteen PD patients and 22 healthy controls performed repeated spiral drawing tasks on a smartphone. Patients performed the tests before a single levodopa dose and at specific time intervals after the dose was given. Three movement disorder specialists rated videos of the patients based on the unified PD rating scale (UPDRS) and the Dyskinesia scale. Differences in mean TIS between the groups of patients and healthy subjects were assessed. Test-retest reliability of the TIS was measured. The ability of TIS to detect changes from baseline (before medication) to later time points was investigated. Correlations between TIS and clinical rating scores were assessed. The mean TIS was significantly different between healthy subjects and patients in advanced groups (p-value = 0.02). Test-retest reliability of TIS was good with Intra-class Correlation Coefficient of 0.81. When assessing changes in relation to treatment, TIS contained some information to capture changes from Off to On and wearing off effects. However, the correlations between TIS and clinical scores (UPDRS and Dyskinesia) were weak. TIS was able to differentiate spiral drawings drawn by patients in an advanced stage from those drawn by healthy subjects, and TIS had good test-retest reliability. TIS was somewhat responsive to single-dose levodopa treatment. Since TIS is an upper limb high-frequency-based measure, it cannot be detected during clinical assessment.

  • 2.
    Aghanavesi, Somayeh
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    A review of Parkinson’s disease cardinal and dyskinetic motor symptoms assessment methods using sensor systems2016Conference paper (Refereed)
    Abstract [en]

    This paper is reviewing objective assessments of Parkinson’s disease(PD) motor symptoms, cardinal, and dyskinesia, using sensor systems. It surveys the manifestation of PD symptoms, sensors that were used for their detection, types of signals (measures) as well as their signal processing (data analysis) methods. A summary of this review’s finding is represented in a table including devices (sensors), measures and methods that were used in each reviewed motor symptom assessment study. In the gathered studies among sensors, accelerometers and touch screen devices are the most widely used to detect PD symptoms and among symptoms, bradykinesia and tremor were found to be mostly evaluated. In general, machine learning methods are potentially promising for this. PD is a complex disease that requires continuous monitoring and multidimensional symptom analysis. Combining existing technologies to develop new sensor platforms may assist in assessing the overall symptom profile more accurately to develop useful tools towards supporting better treatment process.

  • 3. Ahmed, Mobyen
    et al.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Nyholm, Dag
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Groth, Torgny
    A fuzzy rule-based decision support system for Duodopa treatment in Parkinson2006In: 23rd annual workshop of the Swedish Artificial Intelligence Society, Umeå, 2006Conference paper (Refereed)
    Abstract [en]

    A decision support system (DSS) was implemented based on a fuzzy logic inference system (FIS) to provide assistance in dose alteration of Duodopa infusion in patients with advanced Parkinson’s disease, using data from motor state assessments and dosage. Three-tier architecture with an object oriented approach was used. The DSS has a web enabled graphical user interface that presents alerts indicating non optimal dosage and states, new recommendations, namely typical advice with typical dose and statistical measurements. One data set was used for design and tuning of the FIS and another data set was used for evaluating performance compared with actual given dose. Overall goodness-of-fit for the new patients (design data) was 0.65 and for the ongoing patients (evaluation data) 0.98. User evaluation is now ongoing. The system could work as an assistant to clinical staff for Duodopa treatment in advanced Parkinson’s disease.

  • 4. Begum, Shahina
    et al.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Funk, Peter
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Induction of an Adaptive Neuro-Fuzzy Inference System for investing fluctuation in Parkinson’s disease2006In: 23rd annual workshop of the Swedish Artificial Intelligence Society, Umeå, 2006Conference paper (Refereed)
    Abstract [en]

    This paper presents a methodology to formulate natural language rules for an adaptive neuro-fuzzy system based on discovered knowledge, supported by prior knowledge and statistical modeling. Relationships between disease related variables and fluctuations in Parkinson’s disease is often complex. Experts have simplified but mostly reliable “fuzzy” rules based on experience. These rules could be improved using statistical methods and neural nets. This gives clinicians a valuable tool to explore the importance of different variables and their relations in a disease and could aid treatment selection. A prototype using the proposed methodology has been used to induce an Adaptive Neuro Fuzzy Inference Model that has been used to “discover” relationships between fluctuation, treatment and disease severity. More data is needed to confirm these findings. The project shows that artificial intelligence techniques and methods in combination with statistical methods offer medical research and applications valuable opportunities.

  • 5. Brännström, Mattias
    et al.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Classification of structural timber by decision trees: a comparison to the certified method2009In: Forest products journal, ISSN 0015-7473, Vol. 59, no 3, p. 53-61Article in journal (Refereed)
    Abstract [en]

    This work is an example of how to adapt a classification method, in this case a classification tree, to the present standardized method for the development of settings for strength grading machines. Data from commercially available industrial strength grading equipment were used on a large sample (approximately 1440 pieces) of Norway spruce (Picea abies (L. Karsten)) in various sawn dimensions. The equipment is a multisensor scanning device combining planar X-ray and resonance frequency measurement. Destructive testing was done according to European standard EN408. The goal was to make the classification, based on machine data, as close as possible to the optimum grading, which was done according to standard. Two different approaches for classification by cost-sensitive decision trees were applied to the data and compared to classification accredited according to EN14081. Classification accuracy increased from 64% correctly classified to 73%, and a reduction from 33% False Negative to 23% was achieved. False Positive increased from 3% to 4%. The outcome was an increase in value for the producer by 0.9%–2.1% at 2007 average price level. The improvement came mainly from an in-yield increase in C30 by 10%.

  • 6.
    Dougherty, Mark
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Sofi H
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    The April Fool Turing Test2006In: tripleC (cognition, communication, co-operation): Journal for a Global Sustainable Information Society / Unified Theory of Information Research Group, ISSN 1726-670X, E-ISSN 1726-670X, Vol. 4, no 2Article in journal (Refereed)
    Abstract [en]

    This paper explores certain issues concerning the Turing test; non-termination, asymmetry and the need for a control experiment. A standard diagonalisation argument to show the non-computability of AI is extended to yields a socalled “April fool Turing test”, which bears some relationship to Wizard of Oz experiments and involves placing several experimental participants in a symmetrical paradox – the “April Fool Turing Test”. The fundamental question which is asked is whether escaping from this paradox is a sign of intelligence. An important ethical consideration with such an experiment is that in order to place humans in such a paradox it is necessary to fool them. Results from an actual April Fool Turing Test experiment are reported. It is concluded that the results clearly illustrate some of the difficulties and paradoxes which surround the classical Turing Test.

  • 7.
    Dougherty, Mark
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Slutrapport för projektet E-MOTIONS2013Report (Other academic)
  • 8.
    Fleyeh, Hasan
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Extracting Body Landmarks from Videos for Parkinson Gait Analysis2019Conference paper (Refereed)
    Abstract [en]

    Patients with Parkinson disease (PD) exhibit a gait disorder called festinating gait which is caused by deficiency of dopamine in the basal ganglia. To analyze gait of patients with PD, different spatiotemporal parameters such as stride length, cadence, and walking speed should be calculated. This paper aims to present a method to extract useful information represented by the positions of certain landmarks on the human body that can be used for analysis of PD patients’ gait. This method is tested using 132 videos collected from 7 PD patients and 7 healthy controls. The positions of 4 body landmarks, namely body’s center of gravity (COG), the position of the head, and the position of the feet, was computed using a total of more than 41000 of video frames. Results of object’s movement plots show high level of accuracy in the calculation of the body landmarks.

  • 9. Johansson, D.
    et al.
    Ericsson, A.
    Johansson, A.
    Medvedev, A.
    Nyholm, D.
    Ohlsson, F.
    Senek, M.
    Spira, J.
    Thomas, Ilias
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Individualization of levodopa treatment using a microtablet dispenser and ambulatory accelerometry2018In: CNS Neuroscience & Therapeutics, ISSN 1755-5930, E-ISSN 1755-5949, Vol. 24, no 5, p. 439-447Article in journal (Refereed)
    Abstract [en]

    Aim

    This 4‐week open‐label observational study describes the effect of introducing a microtablet dose dispenser and adjusting doses based on objective free‐living motor symptom monitoring in individuals with Parkinson's disease (PD).

    Methods

    Twenty‐eight outpatients with PD on stable levodopa treatment with dose intervals of ≤4 hour had their daytime doses of levodopa replaced with levodopa/carbidopa microtablets, 5/1.25 mg (LC‐5) delivered from a dose dispenser device with programmable reminders. After 2 weeks, doses were adjusted based on ambulatory accelerometry and clinical monitoring.

    Results

    Twenty‐four participants completed the study per protocol. The daily levodopa dose was increased by 15% (112 mg, < 0.001) from period 1 to 2, and the dose interval was reduced by 12% (22 minutes, P = 0.003). The treatment adherence to LC‐5 was high in both periods. The MDS‐UPDRS parts II and III, disease‐specific quality of life (PDQ‐8), wearing‐off symptoms (WOQ‐19), and nonmotor symptoms (NMS Quest) improved after dose titration, but the generic quality‐of‐life measure EQ‐5D‐5L did not. Blinded expert evaluation of accelerometry results demonstrated improvement in 60% of subjects and worsening in 25%.

    Conclusions

    The introduction of a levodopa microtablet dispenser and accelerometry aided dose adjustments improve PD symptoms and quality of life in the short term.

  • 10. Johansson, Dongni
    et al.
    Thomas, Ilias
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Ericsson, Anders
    Johansson, Anders
    Medvedev, Alexander
    Memedi, Mevludin
    Nyholm, Dag
    Ohlsson, Fredrik
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Bergquist, Filip
    Evaluation of a sensor algorithm for motor state rating in Parkinson's disease2019In: Parkinsonism & Related Disorders, ISSN 1353-8020, E-ISSN 1873-5126Article in journal (Refereed)
    Abstract [en]

    INTRODUCTION: A treatment response objective index (TRIS) was previously developed based on sensor data from pronation-supination tests. This study aimed to examine the performance of TRIS for medication effects in a new population sample with Parkinson's disease (PD) and its usefulness for constructing individual dose-response models.

    METHODS: Twenty-five patients with PD performed a series of tasks throughout a levodopa challenge while wearing sensors. TRIS was used to determine motor changes in pronation-supination tests following a single levodopa dose, and was compared to clinical ratings including the Treatment Response Scale (TRS) and six sub-items of the UPDRS part III.

    RESULTS: As expected, correlations between TRIS and clinical ratings were lower in the new population than in the initial study. TRIS was still significantly correlated to TRS (rs = 0.23, P < 0.001) with a root mean square error (RMSE) of 1.33. For the patients (n = 17) with a good levodopa response and clear motor fluctuations, a stronger correlation was found (rs = 0.38, RMSE = 1.29, P < 0.001). The mean TRIS increased significantly when patients went from the practically defined off to their best on state (P = 0.024). Individual dose-response models could be fitted for more participants when TRIS was used for modelling than when TRS ratings were used.

    CONCLUSION: The objective sensor index shows promise for constructing individual dose-response models, but further evaluations and retraining of the TRIS algorithm are desirable to improve its performance and to ensure its clinical effectiveness.

  • 11.
    Khan, Taha
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Memedi, Mevludin
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Song, William Wei
    Dalarna University, School of Technology and Business Studies, Information Systems.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    A case study in healthcare informatics: a telemedicine framework for automated parkinson’s disease symptom assessment2014In: Smart Health: International Conference, ICSH 2014, Beijing, China, July 10-11, 2014. Proceedings / [ed] Zheng X. et al., Springer, 2014, p. 197-199Conference paper (Refereed)
    Abstract [en]

    This paper reports the development and evaluation of a mobile-based telemedicine framework for enabling remote monitoring of Parkinson’s disease (PD) symptoms. The system consists of different measurement devices for remote collection, processing and presentation of symptom data of advanced PD patients. Different numerical analysis techniques were applied on the raw symptom data to extract clinically symptom information which in turn were then used in a machine learning process to be mapped to the standard clinician-based measures. The methods for quantitative and automatic assessment of symptoms were then evaluated for their clinimetric properties such as validity, reliability and sensitivity to change. Results from several studies indicate that the methods had good metrics suggesting that they are appropriate to quantitatively and objectively assess the severity of motor impairments of PD patients.

  • 12.
    Khan, Taha
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering. Malardalen University, Vasteras 72123, Sweden.
    Nyholm, Dag
    Department of Neuroscience, Neurology, Uppsala University, Uppsala, Sweden.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    A Computer Vision Framework For Finger-Tapping Evaluation In Parkinson's Disease2013In: Movement Disorders: Supplement: Abstracts of the Seventeenth International Congress of Parkinson's Disease and Movement Disorders, Movement Disorder Society , 2013, p. 110-111Conference paper (Refereed)
    Abstract [en]

    Objective:

    To define and evaluate a Computer-Vision (CV) method for scoring Paced Finger-Tapping (PFT) in Parkinson's disease (PD) using quantitative motion analysis of index-fingers and to compare the obtained scores to the UPDRS (Unified Parkinson's Disease Rating Scale) finger-taps (FT).

    Background:

    The naked-eye evaluation of PFT in clinical practice results in coarse resolution to determine PD status. Besides, sensor mechanisms for PFT evaluation may cause patients discomfort. In order to avoid cost and effort of applying wearable sensors, a CV system for non-invasive PFT evaluation is introduced.

    Methods:

    A database of 221 PFT videos from 6 PD patients was processed. The subjects were instructed to position their hands above their shoulders besides the face and tap the index-finger against the thumb consistently with speed. They were facing towards a pivoted camera during recording. The videos were rated by two clinicians between symptom levels 0-to-3 using UPDRS-FT.

    The CV method incorporates a motion analyzer and a face detector. The method detects the face of testee in each video-frame. The frame is split into two images from face-rectangle center. Two regions of interest are located in each image to detect index-finger motion of left and right hands respectively. The tracking of opening and closing phases of dominant hand index-finger produces a tapping time-series. This time-series is normalized by the face height. The normalization calibrates the amplitude in tapping signal which is affected by the varying distance between camera and subject (farther the camera, lesser the amplitude). A total of 15 features were classified using K-nearest neighbor (KNN) classifier to characterize the symptoms levels in UPDRS-FT. The target ratings provided by the raters were averaged.

    Results:

    A 10-fold cross validation in KNN classified 221 videos between 3 symptom levels with 75% accuracy. An area under the receiver operating characteristic curves of 82.6% supports feasibility of the obtained features to replicate clinical assessments.

    Conclusions:

    The system is able to track index-finger motion to estimate tapping symptoms in PD. It has certain advantages compared to other technologies (e.g. magnetic sensors, accelerometers etc.) for PFT evaluation to improve and automate the ratings

  • 13.
    Khan, Taha
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering. Malardalen University, Vasteras 72123, Sweden.
    Nyholm, Dag
    Department of Neuroscience, Neurology, Uppsala University, Uppsala, Sweden.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    A computer vision framework for finger-tapping evaluation in Parkinson’s disease2014In: Artificial Intelligence in Medicine, ISSN 0933-3657, E-ISSN 1873-2860, Vol. 60, no 1, p. 27-40Article in journal (Refereed)
    Abstract [en]

    Objectives: The rapid finger-tapping test (RFT) is an important method for clinical evaluation of movementdisorders, including Parkinson’s disease (PD). In clinical practice, the naked-eye evaluation of RFT results in a coarse judgment of symptom scores. We introduce a novel computer-vision (CV) method forquantification of tapping symptoms through motion analysis of index fingers. The method is unique asit utilizes facial features to calibrate tapping amplitude for normalization of distance variation betweenthe camera and subject.

    Methods: The study involved 387 video footages of RFT recorded from 13 patients diagnosed with advanced PD. Tapping performance in these videos was rated by two clinicians between the symptom severity levels (‘0: normal’ to ‘3: severe’) using the unified Parkinson’s disease rating scale motor examination of finger-tapping (UPDRS-FT). Another set of recordings in this study consisted of 84 videos of RFT recorded from 6 healthy controls. These videos were processed by a CV algorithm that tracks the index-finger motion between the video-frames to produce a tapping time-series. Different features were computed from this time series to estimate speed, amplitude, rhythm and fatigue in tapping. The features were trained in a support vector machine (1) to categorize the patient group between UPDRS-FT symptom severity levels, and (2) to discriminate between PD patients and healthy controls.

    Results: A new representative feature of tapping rhythm, ‘cross-correlation between the normalized peaks’ showed strong Guttman correlation (u2 =−0.80) with the clinical ratings. The classification oftapping features using the support vector machine classifier and 10-fold cross validation categorized the patient samples between UPDRS-FT levels with an accuracy of 88%. The same classification scheme discriminated between RFT samples of healthy controls and PD patients with an accuracy of 95%.

    Conclusion: The work supports the feasibility of the approach, which is presumed suitable for PD monitoringin the home environment. The system offers advantages over other technologies (e.g. magneticsensors, accelerometers, etc.) previously developed for objective assessment of tapping symptoms.

  • 14.
    Khan, Taha
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Assessment of PD Speech Anomalies @ Home2011In: 15th International Congress of Parkinson's Disease and Movement Disorders, Toronto, Canada, 2011Conference paper (Refereed)
    Abstract [en]

    Background: Voice processing in real-time is challenging. A drawback of previous work for Hypokinetic Dysarthria (HKD) recognition is the requirement of controlled settings in a laboratory environment. A personal digital assistant (PDA) has been developed for home assessment of PD patients. The PDA offers sound processing capabilities, which allow for developing a module for recognition and quantification HKD. Objective: To compose an algorithm for assessment of PD speech severity in the home environment based on a review synthesis. Methods: A two-tier review methodology is utilized. The first tier focuses on real-time problems in speech detection. In the second tier, acoustics features that are robust to medication changes in Levodopa-responsive patients are investigated for HKD recognition. Keywords such as Hypokinetic Dysarthria , and Speech recognition in real time were used in the search engines. IEEE explorer produced the most useful search hits as compared to Google Scholar, ELIN, EBRARY, PubMed and LIBRIS. Results: Vowel and consonant formants are the most relevant acoustic parameters to reflect PD medication changes. Since relevant speech segments (consonants and vowels) contains minority of speech energy, intelligibility can be improved by amplifying the voice signal using amplitude compression. Pause detection and peak to average power rate calculations for voice segmentation produce rich voice features in real time. Enhancements in voice segmentation can be done by inducing Zero-Crossing rate (ZCR). Consonants have high ZCR whereas vowels have low ZCR. Wavelet transform is found promising for voice analysis since it quantizes non-stationary voice signals over time-series using scale and translation parameters. In this way voice intelligibility in the waveforms can be analyzed in each time frame. Conclusions: This review evaluated HKD recognition algorithms to develop a tool for PD speech home-assessment using modern mobile technology. An algorithm that tackles realtime constraints in HKD recognition based on the review synthesis is proposed. We suggest that speech features may be further processed using wavelet transforms and used with a neural network for detection and quantification of speech anomalies related to PD. Based on this model, patients' speech can be automatically categorized according to UPDRS speech ratings.

  • 15.
    Khan, Taha
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Methods for Detection of Speech Impairment Using Mobile Devices2011In: Recent Patents on Signal Processing, ISSN 2210-6863, Vol. 1, no 2Article in journal (Refereed)
    Abstract [en]

    Speech impairment is an important symptom of Parkinson’s disease(PD). This paper presents a detailed systematic literature review on speech impairment assessment through mobile devices. A two-tier review methodology is utilized. The first tier focuses on real-time problems in speech detection. In the second tier, acoustics features that respond to medication changes in Levodopa responsive PD patients are investigated for recognition of speech symptoms. The investigation of the patents reveals that speech disorder assessment can be made by a comparative analysis between pathological acoustic patterns and the normal acoustic patterns saved in a database. The review depicts that vowel and consonant formants are the most relevant acoustic parameters to reflect PD medication changes. Since consonants have high zero-crossing rate (ZCR) whereas vowels have low ZCR, enhancements in voice segmentation can be done by inducing ZCR. Our synthesis further suggests that wavelet transforms have potential for being useful in real-time voice analysis for detection and quantification of symptoms at home.

  • 16.
    Khan, Taha
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Motion Cues Analysis for Parkinson Gait Recognition2011In: 15th International Congress of Parkinson's Disease and Movement Disorders, Toronto, Canada, 2011Conference paper (Refereed)
    Abstract [en]

    Background: Previous assessment methods for PG recognition used sensor mechanisms for PG that may cause discomfort. In order to avoid stress of applying wearable sensors, computer vision (CV) based diagnostic systems for PG recognition have been proposed. Main constraints in these methods are the laboratory setup procedures: Novel colored dresses for the patients were specifically designed to segment the test body from a specific colored background. Objective: To develop an image processing tool for home-assessment of Parkinson Gait(PG) by analyzing motion cues extracted during the gait cycles. Methods: The system is based on the idea that a normal body attains equilibrium during the gait by aligning the body posture with the axis of gravity. Due to the rigidity in muscular tone, persons with PD fail to align their bodies with the axis of gravity. The leaned posture of PD patients appears to fall forward. Whereas a normal posture exhibits a constant erect posture throughout the gait. Patients with PD walk with shortened stride angle (less than 15 degrees on average) with high variability in the stride frequency. Whereas a normal gait exhibits a constant stride frequency with an average stride angle of 45 degrees. In order to analyze PG, levodopa-responsive patients and normal controls were videotaped with several gait cycles. First, the test body is segmented in each frame of the gait video based on the pixel contrast from the background to form a silhouette. Next, the center of gravity of this silhouette is calculated. This silhouette is further skeletonized from the video frames to extract the motion cues. Two motion cues were stride frequency based on the cyclic leg motion and the lean frequency based on the angle between the leaned torso tangent and the axis of gravity. The differences in the peaks in stride and lean frequencies between PG and normal gait are calculated using Cosine Similarity measurements. Results: High cosine dissimilarity was observed in the stride and lean frequencies between PG and normal gait. High variations are found in the stride intervals of PG whereas constant stride intervals are found in the normal gait. Conclusions: We propose an algorithm as a source to eliminate laboratory constraints and discomfort during PG analysis. Installing this tool in a home computer with a webcam allows assessment of gait in the home environment.

  • 17.
    Khan, Taha
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering. Malardalen University.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Cepstral separation difference: a novel approach for speech impairment quantification in Parkinson’s disease2014In: Biocybernetics and Biomedical Engineering, ISSN 0208-5216, Vol. 34, no 1, p. 25-34Article in journal (Refereed)
    Abstract [en]

    This paper introduces a novel approach, Cepstral Separation Difference (CSD), for quantification of speech impairment in Parkinson’s disease (PD). CSD represents a ratio between the magnitudes of glottal (source) and supra-glottal (filter) log-spectrums acquired using the source-filter speech model. The CSD-based features were tested on a database consisting of 240 clinically rated running speech samples acquired from 60 PD patients and 20 healthy controls. The Guttmann (µ2) monotonic correlations between the CSD features and the speech symptom severity ratings were strong (up to 0.78). This correlation increased with the increasing textual difficulty in different speech tests. CSD was compared with some non-CSD speech features (harmonic ratio, harmonic-to-noise ratio and Mel-frequency cepstral coefficients) for speech symptom characterization in terms of consistency and reproducibility. The high intra-class correlation coefficient (>0.9) and analysis of variance indicates that CSD features can be used reliably to distinguish between severity levels of speech impairment. Results motivate the use of CSD in monitoring speech symptoms in PD.

  • 18.
    Khan, Taha
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering. Malardalen University, Vasteras 72123, Sweden.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Classification of speech intelligibility in Parkinson's disease: Speech Impairment Classification2014In: Biocybernetics and Biomedical Engineering, ISSN 0208-5216, Vol. 34, no 1, p. 35-45Article in journal (Refereed)
    Abstract [en]

    A problem in the clinical assessment of running speech in Parkinson's disease (PD) is to track underlying deficits in a number of speech components including respiration, phonation, articulation and prosody, each of which disturbs the speech intelligibility. A set of 13 features, including the cepstral separation difference and Mel-frequency cepstral coefficients were computed to represent deficits in each individual speech component. These features were then used in training a support vector machine (SVM) using n-fold cross validation. The dataset used for method development and evaluation consisted of 240 running speech samples recorded from 60 PD patients and 20 healthy controls. These speech samples were clinically rated using the Unified Parkinson's Disease Rating Scale Motor Examination of Speech (UPDRS-S). The classification accuracy of SVM was 85% in 3 levels of UPDRS-S scale and 92% in 2 levels with the average area under the ROC (receiver operating characteristic) curves of around 91%. The strong classification ability of selected features and the SVM model supports suitability of this scheme to monitor speech symptoms in PD

  • 19.
    Khan, Taha
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Motion cue analysis for parkinsonian gait recognition2013In: The open biomedical engineering journal, ISSN 1874-1207, Vol. 7, p. 1-8Article in journal (Refereed)
    Abstract [en]

    This paper presents a computer-vision based marker-free method for gait-impairment detection in Patients with Parkinson's disease (PWP). The system is based upon the idea that a normal human body attains equilibrium during the gait by aligning the body posture with Axis-of-Gravity (AOG) using feet as the base of support. In contrast, PWP appear to be falling forward as they are less-able to align their body with AOG due to rigid muscular tone. A normal gait exhibits periodic stride-cycles with stride-angle around 45o between the legs, whereas PWP walk with shortened stride-angle with high variability between the stride-cycles. In order to analyze Parkinsonian-gait (PG), subjects were videotaped with several gait-cycles. The subject's body was segmented using a color-segmentation method to form a silhouette. The silhouette was skeletonized for motion cues extraction. The motion cues analyzed were stride-cycles (based on the cyclic leg motion of skeleton) and posture lean (based on the angle between leaned torso of skeleton and AOG). Cosine similarity between an imaginary perfect gait pattern and the subject gait patterns produced 100% recognition rate of PG for 4 normal-controls and 3 PWP. Results suggested that the method is a promising tool to be used for PG assessment in home-environment.

  • 20.
    Khan, Taha
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Funk, Peter
    Mälardalen univ.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Quantification of speech impairment in Parkinson's disease2012In: Movement Disorders, ISSN 0885-3185, E-ISSN 1531-8257, Vol. 27, p. S510-S511Article in journal (Refereed)
  • 21.
    Memedi, Mevludin
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Aghanavesi, Somayeh
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    A method for measuring Parkinson's disease related temporal irregularity in spiral drawings2016In: 2016 IEEE International Conference on Biomedical and Health Informatics, 2016, p. 410-413Conference paper (Refereed)
    Abstract [en]

    The objective of this paper was to develop and evaluate clinimetric properties of a method for measuring Parkinson's disease (PD)-related temporal irregularities using digital spiral analysis. In total, 108 (98 patients in different stages of PD and 10 healthy elderly subjects) performed repeated spiral drawing tasks in their home environments using a touch screen device. A score was developed for representing the amount of temporal irregularity during spiral drawing tasks, using Approximate Entropy (ApEn) technique. In addition, two previously published spiral scoring methods were adapted and their scores were analyzed. The mean temporal irregularity score differed significantly between healthy elderly subjects and advanced PD patients (P<0.005). The ApEn-based method had a better responsiveness and test-retest reliability when compared to the other two methods. In contrast to the other methods, the mean scores of the ApEn-based method improved significantly during a 3 year clinical study, indicating a possible impact of pathological basal ganglia oscillations in temporal control during spiral drawing tasks. In conclusion, the ApEn-based method could be used for differentiating between patients in different stages of PD and healthy subjects. The responsiveness and test-retest reliability were good for the ApEn-based method indicating that this method is useful for measuring upper limb temporal irregularity at a micro-level.

  • 22.
    Memedi, Mevludin
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Aghanavesi, Somayeh
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Digital spiral analysis for objective assessment of fine motor timing variability in Parkinson's disease2015Conference paper (Other academic)
    Abstract [en]

    OBJECTIVES: To develop a method for objective assessment of fine motor timing variability in Parkinson’s disease (PD) patients, using digital spiral data gathered by a touch screen device.

    BACKGROUND: A retrospective analysis was conducted on data from 105 subjects including65 patients with advanced PD (group A), 15 intermediate patients experiencing motor fluctuations (group I), 15 early stage patients (group S), and 10 healthy elderly subjects (HE) were examined. The subjects were asked to perform repeated upper limb motor tasks by tracing a pre-drawn Archimedes spiral as shown on the screen of the device. The spiral tracing test was performed using an ergonomic pen stylus, using dominant hand. The test was repeated three times per test occasion and the subjects were instructed to complete it within 10 seconds. Digital spiral data including stylus position (x-ycoordinates) and timestamps (milliseconds) were collected and used in subsequent analysis. The total number of observations with the test battery were as follows: Swedish group (n=10079), Italian I group (n=822), Italian S group (n = 811), and HE (n=299).

    METHODS: The raw spiral data were processed with three data processing methods. To quantify motor timing variability during spiral drawing tasks Approximate Entropy (APEN) method was applied on digitized spiral data. APEN is designed to capture the amount of irregularity or complexity in time series. APEN requires determination of two parameters, namely, the window size and similarity measure. In our work and after experimentation, window size was set to 4 and similarity measure to 0.2 (20% of the standard deviation of the time series). The final score obtained by APEN was normalized by total drawing completion time and used in subsequent analysis. The score generated by this method is hence on denoted APEN. In addition, two more methods were applied on digital spiral data and their scores were used in subsequent analysis. The first method was based on Digital Wavelet Transform and Principal Component Analysis and generated a score representing spiral drawing impairment. The score generated by this method is hence on denoted WAV. The second method was based on standard deviation of frequency filtered drawing velocity. The score generated by this method is hence on denoted SDDV. Linear mixed-effects (LME) models were used to evaluate mean differences of the spiral scores of the three methods across the four subject groups. Test-retest reliability of the three scores was assessed after taking mean of the three possible correlations (Spearman’s rank coefficients) between the three test trials. Internal consistency of the methods was assessed by calculating correlations between their scores.

    RESULTS: When comparing mean spiral scores between the four subject groups, the APEN scores were different between HE subjects and three patient groups (P=0.626 for S group with 9.9% mean value difference, P=0.089 for I group with 30.2%, and P=0.0019 for A group with 44.1%). However, there were no significant differences in mean scores of the other two methods, except for the WAV between the HE and A groups (P<0.001). WAV and SDDV were highly and significantly correlated to each other with a coefficient of 0.69. However, APEN was not correlated to neither WAV nor SDDV with coefficients of 0.11 and 0.12, respectively. Test-retest reliability coefficients of the three scores were as follows: APEN (0.9), WAV(0.83) and SD-DV (0.55).

    CONCLUSIONS: The results show that the digital spiral analysis-based objective APEN measure is able to significantly differentiate the healthy subjects from patients at advanced level. In contrast to the other two methods (WAV and SDDV) that are designed to quantify dyskinesias (over-medications), this method can be useful for characterizing Off symptoms in PD. The APEN was not correlated to none of the other two methods indicating that it measures a different construct of upper limb motor function in PD patients than WAV and SDDV. The APEN also had a better test-retest reliability indicating that it is more stable and consistent over time than WAV and SDDV.

  • 23.
    Memedi, Mevludin
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Aghanavesi, Somayeh
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Objective quantification of Parkinson's disease upper limb motor timing variability using spirography2015Conference paper (Refereed)
    Abstract [en]

    Objective quantification of the upper limb motor timing variability of Parkinson’s disease (PD) patients was evaluated using traces of spirals by groups of patients at different disease stages, stable (S), intermediate (I), advanced (A) and a healthy elderly (HE) group. The approximate entropy (APEN) method of quantifying motor timing variability in time series was applied to capture the amount of irregularity during the spiral drawing process. The APEN score was then normalized by total drawing completion time and used in subsequent analysis. In addition, two previously published methods (WAV and SDDV) were applied on the spiral data. Comparing subject groups’ APEN mean scores, they were found to be significantly different from HE group, for group A (P<0.001) indicating this method’s ability in distinguishing patients at advanced disease stage. Comparing the three methods’ ability to track response to advanced treatment, APEN scores were all significantly different between base-line and levodopa-carbidopa intestinal gel (LCIG) treatment, during the 36 month study period as opposed to WAV and SDDV as they were not significantly improving for all periods. APEN scores were weakly correlated to WAV and SDDV, indicating that they measure different aspects of symptom severity.

  • 24.
    Memedi, Mevludin
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Bergqvist, Ulf
    Nordforce Technology AB.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Grenholm, Peter
    Neuroscience, Neurology, Uppsala University.
    Nyholm, Dag
    Neuroscience, Neurology, Uppsala University.
    A web-based system for visualizing upper limb motor performance of Parkinson’s disease patients2013In: Movement Disorders: Supplement: Abstracts of the Seventeenth International Congress of Parkinson's Disease and Movement Disorders, Wiley-Blackwell, 2013, p. S112-S113Conference paper (Refereed)
    Abstract [en]

    Objective

    To design, develop and set up a web-based system for enabling graphical visualization of upper limb motor performance (ULMP) of Parkinson’s disease (PD) patients to clinicians.

    Background

    Sixty-five patients diagnosed with advanced PD have used a test battery, implemented in a touch-screen handheld computer, in their home environment settings over the course of a 3-year clinical study. The test items consisted of objective measures of ULMP through a set of upper limb motor tests (finger to tapping and spiral drawings). For the tapping tests, patients were asked to perform alternate tapping of two buttons as fast and accurate as possible, first using the right hand and then the left hand. The test duration was 20 seconds. For the spiral drawing test, patients traced a pre-drawn Archimedes spiral using the dominant hand, and the test was repeated 3 times per test occasion. In total, the study database consisted of symptom assessments during 10079 test occasions.

    Methods

    Visualization of ULMP

    The web-based system is used by two neurologists for assessing the performance of PD patients during motor tests collected over the course of the said study. The system employs animations, scatter plots and time series graphs to visualize the ULMP of patients to the neurologists. The performance during spiral tests is depicted by animating the three spiral drawings, allowing the neurologists to observe real-time accelerations or hesitations and sharp changes during the actual drawing process. The tapping performance is visualized by displaying different types of graphs. Information presented included distribution of taps over the two buttons, horizontal tap distance vs. time, vertical tap distance vs. time, and tapping reaction time over the test length.

    Assessments

    Different scales are utilized by the neurologists to assess the observed impairments. For the spiral drawing performance, the neurologists rated firstly the ‘impairment’ using a 0 (no impairment) – 10 (extremely severe) scale, secondly three kinematic properties: ‘drawing speed’, ‘irregularity’ and ‘hesitation’ using a 0 (normal) – 4 (extremely severe) scale, and thirdly the probable ‘cause’ for the said impairment using 3 choices including Tremor, Bradykinesia/Rigidity and Dyskinesia. For the tapping performance, a 0 (normal) – 4 (extremely severe) scale is used for first rating four tapping properties: ‘tapping speed’, ‘accuracy’, ‘fatigue’, ‘arrhythmia’, and then the ‘global tapping severity’ (GTS). To achieve a common basis for assessment, initially one neurologist (DN) performed preliminary ratings by browsing through the database to collect and rate at least 20 samples of each GTS level and at least 33 samples of each ‘cause’ category. These preliminary ratings were then observed by the two neurologists (DN and PG) to be used as templates for rating of tests afterwards. In another track, the system randomly selected one test occasion per patient and visualized its items, that is tapping and spiral drawings, to the two neurologists.

    Statistical methods

    Inter-rater agreements were assessed using weighted Kappa coefficient. The internal consistency of properties of tapping and spiral drawing tests were assessed using Cronbach’s α test. One-way ANOVA test followed by Tukey multiple comparisons test was used to test if mean scores of properties of tapping and spiral drawing tests were different among GTS and ‘cause’ categories, respectively.

    Results

    When rating tapping graphs, inter-rater agreements (Kappa) were as follows: GTS (0.61), ‘tapping speed’ (0.89), ‘accuracy’ (0.66), ‘fatigue’ (0.57) and ‘arrhythmia’ (0.33). The poor inter-rater agreement when assessing “arrhythmia” may be as a result of observation of different things in the graphs, among the two raters. When rating animated spirals, both raters had very good agreement when assessing severity of spiral drawings, that is, ‘impairment’ (0.85) and irregularity (0.72). However, there were poor agreements between the two raters when assessing ‘cause’ (0.38) and time-information properties like ‘drawing speed’ (0.25) and ‘hesitation’ (0.21). Tapping properties, that is ‘tapping speed’, ‘accuracy’, ‘fatigue’ and ‘arrhythmia’ had satisfactory internal consistency with a Cronbach’s α coefficient of 0.77. In general, the trends of mean scores of tapping properties worsened with increasing levels of GTS. The mean scores of the four properties were significantly different to each other, only at different levels. In contrast from tapping properties, kinematic properties of spirals, that is ‘drawing speed’, ‘irregularity’ and ‘hesitation’ had a questionable consistency among them with a coefficient of 0.66. Bradykinetic spirals were associated with more impaired speed (mean = 83.7 % worse, P < 0.001) and hesitation (mean = 77.8% worse, P < 0.001), compared to dyskinetic spirals. Both these ‘cause’ categories had similar mean scores of ‘impairment’ and ‘irregularity’.

    Conclusions

    In contrast from current approaches used in clinical setting for the assessment of PD symptoms, this system enables clinicians to animate easily and realistically the ULMP of patients who at the same time are at their homes. Dynamic access of visualized motor tests may also be useful when observing and evaluating therapy-related complications such as under- and over-medications. In future, we foresee to utilize these manual ratings for developing and validating computer methods for automating the process of assessing ULMP of PD patients.

  • 25.
    Memedi, Mevludin
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Khan, Taha
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Grenholm, Peter
    Department of Neuroscience, Neurology, Uppsala University.
    Nyholm, Dag
    Department of Neuroscience, Neurology, Uppsala University.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Automatic and objective assessment of alternating tapping performance in Parkinson’s disease2013In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 13, no 12, p. 16965-16984Article in journal (Refereed)
    Abstract [en]

    This paper presents the development and evaluation of a method for enabling quantitative and automatic scoring of alternating tapping performance of patients with Parkinson’s disease (PD). Ten healthy elderly subjects and 95 patients in different clinical stages of PD have utilized a touch-pad handheld computer to perform alternate tapping tests in their home environments. First, a neurologist used a web-based system to visually assess impairments in four tapping dimensions (‘speed’, ‘accuracy’, ‘fatigue’ and ‘arrhythmia’) and a global tapping severity (GTS). Second, tapping signals were processed with time series analysis and statistical methods to derive 24 quantitative parameters. Third, principal component analysis was used to reduce the dimensions of these parameters and to obtain scores for the four dimensions. Finally, a logistic regression classifier was trained using a 10-fold stratified cross-validation to map the reduced parameters to the corresponding visually assessed GTS scores. Results showed that the computed scores correlated well to visually assessed scores and were significantly different across Unified Parkinson’s Disease Rating Scale scores of upper limb motor performance. In addition, they had good internal consistency, had good ability to discriminate between healthy elderly and patients in different disease stages, had good sensitivity to treatment interventions and could reflect the natural disease progression over time. In conclusion, the automatic method can be useful to objectively assess the tapping performance of PD patients and can be included in telemedicine tools for remote monitoring of tapping.

  • 26.
    Memedi, Mevludin
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering. School of Science and Technology, Örebro University.
    Nyholm, Dag
    Department of Neuroscience, Neurology, Uppsala University.
    Johansson, Anders
    Department of Clinical Neuroscience, Neurology, Karolinska Institutet.
    Pålhagen, Sven
    Department of Clinical Neuroscience, Neurology, Karolinska Institutet.
    Willows, Thomas
    Department of Neurology, Karolinska University Hospital.
    Widner, Håkan
    Department of Neurology, Skåne University Hospital.
    Linder, Jan
    Department of Pharmacology and Clinical Neuroscience, Umeå University.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Self-assessments and motor tests via telemetry in a 36-month levodopa-carbidopa intestinal gel infusion trial2014Manuscript (preprint) (Other academic)
    Abstract [en]

    Objective: The aim of this study was to investigate if a telemetry test battery can be used to measure effects of Parkinson’s disease (PD) treatment intervention and disease progression.

    Methods: Sixty-five patients diagnosed with advanced PD were recruited in an open longitudinal 36-month study; 35 treated with levodopa-carbidopa intestinal gel (LCIG) and 30 were candidates for switching from oral PD treatment to LCIG. They utilized a test battery, consisting of self-assessments of symptoms and fine motor tests (tapping and spiral drawings), four times per day in their homes during week-long test periods. The repeated measurements were summarized into an overall test score (OTS) to represent the global condition of the patient during a test period. Clinical assessments included ratings on Unified PD Rating Scale (UPDRS) and 39-item PD Questionnaire (PDQ-39) scales.

    Results: In LCIG-naïve patients, mean OTS compared to baseline was significantly improved from the first test period on LCIG treatment until month 24. In LCIG-non-naïve patients, there were no significant changes in mean OTS, except at month 36 (P<0.01). The OTS correlated adequately with total UPDRS (rho = 0.59) and total PDQ-39 (0.59).

    Conclusions: PD symptoms can be remotely monitored over time with this test battery. The trends of the test scores were similar to the trends of clinical rating scores. Correlations between OTS and clinical rating scales were adequate indicating that the test battery contains important elements of the information of the well-established scales.

  • 27.
    Memedi, Mevludin
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Nyholm, Dag
    Department of Neuroscience, Neurology, Uppsala University, Uppsala, Sweden.
    Johansson, Anders
    Department of Clinical Neuroscience, Neurology, Karolinska Institutet, Stockholm, Sweden.
    Pålhagen, Sven
    Department of Neurology, Karolinska University Hospital, Stockholm, Sweden.
    Willows, Thomas
    Department of Neurology, Karolinska University Hospital, Stockholm, Sweden.
    Widner, Håkan
    Department of Neurology, Skåne University Hospital, Lund, Sweden.
    Linder, Jan
    Department of Pharmacology and Clinical Neuroscience, Umeå University, Umeå, Sweden.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Validity and responsiveness of at-home touch-screen assessments in advanced Parkinson's disease2015In: IEEE journal of biomedical and health informatics, ISSN 2168-2194, E-ISSN 2168-2208, Vol. 19, no 6, p. 1829-1834Article in journal (Refereed)
    Abstract [en]

    The aim of this study was to investigate if a telemetry test battery can be used to measure effects of Parkinson’s disease (PD) treatment intervention and disease progression in patients with fluctuations. Sixty-five patients diagnosed with advanced PD were recruited in an open longitudinal 36-month study; 35 treated with levodopa-carbidopa intestinal gel (LCIG) and 30 were candidates for switching from oral PD treatment to LCIG. They utilized a test battery, consisting of self-assessments of symptoms and fine motor tests (tapping and spiral drawings), four times per day in their homes during week-long test periods. The repeated measurements were summarized into an overall test score (OTS) to represent the global condition of the patient during a test period. Clinical assessments included ratings on Unified PD Rating Scale (UPDRS) and 39-item PD Questionnaire (PDQ-39) scales. In LCIG-naïve patients, mean OTS compared to baseline was significantly improved from the first test period on LCIG treatment until month 24. In LCIG-non-naïve patients, there were no significant changes in mean OTS until month 36. The OTS correlated adequately with total UPDRS (rho = 0.59) and total PDQ-39 (0.59). Responsiveness measured as effect size was 0.696 and 0.536 for OTS and UPDRS respectively. The trends of the test scores were similar to the trends of clinical rating scores but dropout rate was high. Correlations between OTS and clinical rating scales were adequate indicating that the test battery contains important elements of the information of well-established scales. The responsiveness and reproducibility were better for OTS than for total UPDRS.

  • 28.
    Memedi, Mevludin
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Nyholm, Dag
    Neuroscience, Neurology, Uppsala University.
    Johansson, Anders
    Clinical Neuroscience, Karolinska Institutet.
    Pålhagen, Sven
    Clinical Neuroscience, Karolinska Institutet.
    Willows, Thomas
    Neurology, Karolinska University Hospital.
    Widner, Håkan
    Neurology, Skåne University Hospital.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Self-reported symptoms and motor tests via telemetry in a 36-month levodopa-carbidopa intestinal gel infusion trial2013In: Movement Disorders :  Supplement: Abstracts of the Seventeenth International Congress of Parkinson's Disease and Movement Disorders S1, Wiley-Blackwell, 2013, p. S168-S168Conference paper (Refereed)
    Abstract [en]

    Objective

    To investigate if a home environment test battery can be used to measure effects of Parkinson’s disease (PD) treatment intervention and disease progression.

    Background

    Seventy-seven patients diagnosed with advanced PD were recruited in an open longitudinal 36-month study at 10 clinics in Sweden and Norway; 40 of them were treated with levodopa-carbidopa intestinal gel (LCIG) and 37 patients were candidates for switching from oral PD treatment to LCIG. They utilized a mobile device test battery, consisting of self-assessments of symptoms and objective measures of motor function through a set of fine motor tests (tapping and spiral drawings), in their homes. Both the LCIG-naïve and LCIG-non-naïve patients used the test battery four times per day during week-long test periods.

    Methods

    Assessments

    The LCIG-naïve patients used the test battery at baseline (before LCIG), month 0 (first visit; at least 3 months after intraduodenal LCIG), and thereafter quarterly for the first year and biannually for the second and third years. The LCIG-non-naïve patients used the test battery from the first visit, i.e. month 0. Out of the 77 patients, only 65 utilized the test battery; 35 were LCIG-non-naïve and 30 LCIG-naïve. In 20 of the LCIG-naïve patients, assessments with the test battery were available during oral treatment and at least one test period after having started infusion treatment. Three LCIG-naïve patients did not use the test battery at baseline but had at least one test period of assessments thereafter. Hence, n=23 in the LCIG-naïve group. In total, symptom assessments in the full sample (including both patient groups) were collected during 379 test periods and 10079 test occasions. For 369 of these test periods, clinical assessments including UPDRS and PDQ-39 were performed in afternoons at the start of the test periods. The repeated measurements of the test battery were processed and summarized into scores representing patients’ symptom severities over a test period, using statistical methods. Six conceptual dimensions were defined; four subjectively-reported: ‘walking’, ‘satisfied’, ‘dyskinesia’, and ‘off’ and two objectively-measured: ‘tapping’ and ‘spiral’. In addition, an ‘overall test score’ (OTS) was defined to represent the global health condition of the patient during a test period.

    Statistical methods

    Change in the test battery scores over time, that is at baseline and follow-up test periods, was assessed with linear mixed-effects models with patient ID as a random effect and test period as a fixed effect of interest. The within-patient variability of OTS was assessed using intra-class correlation coefficient (ICC), for the two patient groups. Correlations between clinical rating scores and test battery scores were assessed using Spearman’s rank correlations (rho).

    Results

    In LCIG-naïve patients, mean OTS compared to baseline was significantly improved from the first test period on LCIG treatment until month 24. However, there were no significant changes in mean OTS scores of LCIG-non-naïve patients, except for worse mean OTS at month 36 (p<0.01, n=16). The mean scores of all subjectively-reported dimensions improved significantly throughout the course of the study, except ‘walking’ at month 36 (p=0.41, n=4). However, there were no significant differences in mean scores of objectively-measured dimensions between baseline and other test periods, except improved ‘tapping’ at month 6 and month 36, and ‘spiral’ at month 3 (p<0.05). The LCIG-naïve patients had a higher within-subject variability in their OTS scores (ICC=0.67) compared to LCIG-non-naïve patients (ICC=0.71). The OTS correlated adequately with total UPDRS (rho=0.59) and total PDQ-39 (rho=0.59).

    Conclusions

    In this 3-year follow-up study of advanced PD patients treated with LCIG we found that it is possible to monitor PD progression over time using a home environment test battery. The significant improvements in the mean OTS scores indicate that the test battery is able to measure functional improvement with LCIG sustained over at least 24 months.

  • 29.
    Memedi, Mevludin
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering. Örebro University.
    Nyholm, Dag
    Neuroscience, Neurology, Uppsala University.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Combined fine-motor tests and self-assessments for remote detection of motor fluctuations2013In: Recent Patents on Biomedial Engineering, ISSN 1874-7647, Vol. 6, no 2, p. 127-135Article in journal (Refereed)
    Abstract [en]

    A major problem with the clinical management of fluctuating movement disorders, e.g. Parkinson's disease (PD), is the large variability in manifestation of symptoms among patients. In this condition, frequent measurements which account for both patient-reported and objective assessments are needed in order to capture symptom fluctuations, with the purpose to optimize therapy. The main focus of this paper is to present a mobile-based system for enabling remote monitoring of PD patients from their home environment conditions. The system consists of a patient diary section for collecting patient-based self-assessments, a motor test section for collecting fine motor movements through upper limb motor tests, and a scheduler for restricting operation to a multitude of predetermined limited time intervals. The system processes and compiles time series data into different summary scores representing symptom severity. In addition, the paper presents a review of recent inventions which were filed after year 2000 in the field of telemedicine applications. The review includes a summary of systems and methods which enable remote symptom assessments of patients, not necessarily suffering from movement disorders, through repeated measurements and which take into account their subjective and/or objective health indicators. The findings conclude that there are a small number of inventions which collect subjective and objective health measures in telemedicine settings. Consequently, there is a lack of mechanisms that combine these two types of information into scores to provide a more in-depth assessment of the patient's general health, their motor and non-motor symptom fluctuations and treatment effects. The paper also provides a discussion concerning different approaches for analyzing and combining subjective and objective measures, and handling data from longitudinal studies.

  • 30.
    Memedi, Mevludin
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering. Örebro universitet.
    Thomas, Ilias
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nyholm, Dag
    Uppsala University Hospital.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Senek, Marina
    Uppsala University Hospital.
    Medvedev, Alexander
    Uppsala University.
    Askmark, Håkan
    Uppsala University.
    Aquilonius, Sten-Magnus
    Uppsala University.
    Bergquist, Filip
    University of Gothenburg.
    Constantinescu, Radu
    Ohlsson, Fredrik
    Acreo AB.
    Spira, Jack
    Sensidose AB.
    Lycke, Sara
    Cenvigo AB.
    Ericsson, Anders
    Acreo AB.
    Construction of a levodopa-response index from wearable sensorsfor quantifying Parkinson’s disease motor functions: Preliminary results2016Conference paper (Other academic)
  • 31.
    Memedi, Mevludin
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Methods for detection of handwriting/drawing impairment using inputs from touch screens2011In: Recent Patents on Signal Processing, ISSN 2210-6863, Vol. 1, no 2Article in journal (Refereed)
    Abstract [en]

    Fine motor dysfunction in patients with movement disorders, such as Parkinson’s disease, is characterized by slowness of movements, decrease of reaction time and involuntary movements. In this article, recent patents on detecting and assessing the said dysfunction are reviewed; their implementation in telemedicine settings, design considerations and ability to assist in dose and time adjustments are discussed. These patents explain application of signal processing techniques in analysis and interpretation of digitized handwriting/drawing information of individuals based on data gathered using touch screens. The study reveals that measures concerning forces, accelerations and radial displacements are the most relevant measurements to detect fine movement anomalies. These findings demonstrate that digitized analysis of handwriting/drawing movements may be useful in clinical trials evaluating fine motor control. This review further depicts the role of employing event-based data acquisition and signal processing techniques suitable for nonstationary signals, such as Wavelet transform, in systems for patient home-monitoring.

  • 32.
    Memedi, Mevludin
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Spiral drawing during self-rated dyskinesia is more impaired than during self-rated off2011In: 15th International Congress of Parkinson's Disease and Movement Disorders, Toronto, Canada, 2011Conference paper (Refereed)
    Abstract [en]

    Background: A mobile device test battery, consisting of a patient diary collection section with disease-related questions and a fine motor test section (including spiral drawing tasks), was used by 65 patients with advanced Parkinson's disease (PD)(treated with intraduodenal levodopa/carbidopa gel infusion, Duodopa®, or candidates for this treatment) on 10439 test occasions in their home environments. On each occasion, patients traced three pre-drawn Archimedes spirals using an ergonomic stylus and self-assessed their motor function on a global Treatment Response Scale (TRS) ranging from -3 = very 'off' to 0 = 'on' to +3 = very dyskinetic. The spirals were processed by a computer-based method that generates a "spiral score" representing the PD-related drawing impairment. The scale for the score was based on a modified Bain & Findley rating scale in the range from 0 = no impairment to 5 = moderate impairment to 10 = extremely severe impairment. Objective: To analyze the test battery data for the purpose to find differences in spiral drawing performance of PD patients in relation to their self-assessments of motor function. Methods: Three motor states were used in the analysis; OFF state (including moderate and very 'off'), ON state ('on') and a dyskinetic (DYS) state (moderate and very dyskinetic). In order to avoid the problem of multiple test occasions per patient, 200 random samples of single test occasions per patient were drawn. One-way analysis of variance, ANOVA, test followed by Tukey multiple comparisons test was used to test if mean values of spiral test parameters, i.e. the spiral score and drawing completion times (in seconds), were different among the three motor states. Statistical significance was set at p<0.05. To investigate changes in the spiral score over the time-of-day test sessions for the three motor states, plots of statistical summaries were inspected. Results: The mean spiral score differed significantly across the three self-assessed motor states (p<0.001, ANOVA test). Tukey post-hoc comparisons indicate that the mean spiral score (mean ± SD; [95% CI for mean]) in DYS state (5.2 ± 1.8; [5.12, 5.28]) was higher than the mean spiral score in OFF (4.3 ± 1.7; [4.22, 4.37]) and ON (4.2 ± 1.7; [4.17, 4.29]) states. The mean spiral score was also significantly different among individual TRS values of slightly 'off' (4.02 ± 1.63), 'on' (4.07 ± 1.65) and slightly dyskinetic (4.6 ± 1.71), (p<0.001). There were no differences in drawing completion times among the three motor states (p=0.509). In the OFF and ON states, patients drew slightly more impaired spirals in the afternoon whereas in the DYS state the spiral drawing performance was more impaired in the morning. Conclusion: It was found that when patients considered themselves as being dyskinetic spiral drawing was more impaired (nearly one unit change in a 0-10 scale) compared to when they considered themselves as being 'off' and 'on'. The spiral drawing at patients that self-assessed their motor state as dyskinetic was slightly more impaired in the morning hours, between 8 and 12 o'clock, a situation possibly caused by the morning dose effect.

  • 33.
    Memedi, Mevludin
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Nyholm, Dag
    Department of Neuroscience, Neurology, Uppsala University, Uppsala, Sweden.
    Spiral drawing during self-rated dyskinesia is more impaired than during self-rated off2013In: Parkinsonism & Related Disorders, ISSN 1353-8020, E-ISSN 1873-5126, Vol. 19, no 5, p. 553-556Article in journal (Refereed)
    Abstract [en]

    Objective. The purpose of this study was to examine repeated measures of fine motor function in relation to self-assessed motor conditions in Parkinson's disease (PD).

    Methods. One-hundred PD patients, 65 with advanced PD and 35 patients with different disease stages have utilized a test battery in a telemedicine setting. On each test occasion, they initially self-assessed their motor condition (from ‘very off’ to ‘very dyskinetic’) and then performed a set of fine motor tests (tapping and spiral drawings).

    Results. The motor tests scores were found to be the best during self-rated On. Self-rated dyskinesias caused more impaired spiral drawing performance (mean = 9.8% worse, P < 0.001) but at the same time tapping speed was faster (mean = 5.0% increase, P < 0.001), compared to scores in self-rated Off.

    Conclusions. The fine motor tests of the test battery capture different symptoms; the spiral impairment primarily relates to dyskinesias whereas the tapping speed captures the Off symptoms.

  • 34.
    Memedi, Mevludin
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Nyholm, Dag
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Groth, Torgny
    A web application for follow-up of results from a mobile device test battery for Parkinson's disease patients2011In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 104, no 2, p. 219-226Article in journal (Refereed)
    Abstract [en]

    This paper describes a web-based system for enabling remote monitoring of patients with Parkinson's disease (PD) and supporting clinicians in treating their patients. The system consists of a patient node for subjective and objective data collection based on a handheld computer, a service node for data storage and processing, and a web application for data presentation. Using statistical and machine learning methods, time series of raw data are summarized into scores for conceptual symptom dimensions and an "overall test score" providing a comprehensive profile of patient's health during a test period of about one week. The handheld unit was used quarterly or biannually by 65 patients with advanced PD for up to four years at nine clinics in Sweden. The IBM Computer System Usability Questionnaire was administered to assess nurses' satisfaction with the web application. Results showed that a majority of the nurses were quite satisfied with the usability although a sizeable minority were not. Our findings support that this system can become an efficient tool to easily access relevant symptom information from the home environment of PD patients. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

  • 35.
    Memedi, Mevludin
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Nyholm, Dag
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Groth, Torgny
    A web application for follow-up of results from a mobile device test battery for parkinson’s disease patients2010In: European Journal of Neurology, ISSN 1351-5101, E-ISSN 1468-1331Article in journal (Refereed)
    Abstract [en]

    Background: A test battery consisting of self-assessments and motor tests (tapping and spiral drawing) was developed for a hand computer with touch screen in a telemedicine setting.

    Objectives: To develop and evaluate a web-based system that delivers decision support information to the treating clinical staff for assessing PD symptoms in their patients based on the test battery data. Methods: The test battery is currently being used in a clinical trial (DAPHNE, EudraCT No. 2005-002654-21) by sixty five patients with advanced Parkinson’s disease (PD) on 9991 test occasions (four tests per day during in all 362 week-long test periods) at nine clinics around Sweden. Test results are sent continuously from the hand unit over a mobile net to a central computer and processed with statistical methods. They are summarized into scores for different dimensions of the symptom state and an ‘overall test score’ reflecting the overall condition of the patient during a test period. The information in the web application is organized and presented graphically in a way that the general overview of the patient performance per test period is emphasized. Focus is on the overall test score, symptom dimensions and daily summaries. In a recent preliminary user evaluation, the web application was demonstrated to the fifteen study nurses who had used the test battery in the clinical trial. At least one patient per clinic was shown.

    Results: In general, the responses from nurses were positive. They claimed that the test results shown in the system were consistent with their own clinical observations. They could follow complications, changes and trends within their patients.

    Discussion: In conclusion, the system is able to summarise the various time series of motor test results and self-assessments during test periods and present them in a useful manner. Its main contribution is a novel and reliable way to capture and easily access symptom information from patients’ home environment. The convenient access to current symptom profile as well as symptom history provides a basis for individualized evaluation and adjustment of treatments.

  • 36.
    Saqlain, Murshid
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Brandt, Daniel
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Stochastic differential equations modelling of levodopa concentration in patients with Parkinson's disease2018Conference paper (Other academic)
    Abstract [en]

    The purpose of this study is to investigate a pharmacokinetic model of levodopa concentration in patients with Parkinson's disease by introducing stochasticity so that inter-individual variability may be separated into measurement and system noise. It also aims to investigate whether the stochastic differential equations (SDE) model provide better fits than its ordinary differential equations (ODE) counterpart, by using a real data set. Westin et al. developed a pharmacokinetic-pharmacodynamic model for duodenal levodopa infusion described by four ODEs, the first three of which define the pharmacokinetic model. In this study, system noise variables are added to the aforementioned first three equations through a standard Wiener process, also known as Brownian motion. The R package PSM for mixed-effects models is used on data from previous studies for modelling levodopa concentration and parameter estimation. First, the diffusion scale parameter, σ, and bioavailability are estimated with the SDE model. Second, σ is fixed to integer values between 1 and 5, and bioavailability is estimated. Cross-validation is performed to determine whether the SDE based model explains the observed data better or not by comparingthe average root mean squared errors (RMSE) of predicted levodopa concentration. Both ODE and SDE models estimated bioavailability to be about 88%. The SDE model converged at different values of σ that were signicantly different from zero while estimating bioavailability to be about 88%. The average RMSE for the ODE model wasfound to be 0.2980, and the lowest average RMSE for the SDE model was 0.2748 when σ was xed to 4. Both models estimated similar values for bioavailability, and the non-zero σ estimate implies that the inter-individual variability may be separated. However, the improvement in the predictive performance of the SDE model turned out to be rather small, compared to the ODE model.

  • 37.
    Schiavella, Mauro
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Pelagatti, Matteo
    University Milano-Bicocca.
    Lepore, Gabriele
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    PokerMapper: mapping executive functions, poker playing ability and responsible gambling in online environments2015Conference paper (Refereed)
    Abstract [en]

    Research objectives

    Poker and responsible gambling both entail the use of the executive functions (EF), which are higher-level cognitive abilities. The main objective of this work was to assess if online poker players of different ability show different performances in their EF and if so, which functions are the most discriminating ones. The secondary objective was to assess if the EF performance can predict the quality of gambling, according to the Gambling Related Cognition Scale (GRCS), the South Oaks Gambling Screen (SOGS) and the Problem Gambling Severity Index (PGSI).

    Sample and methods

    The study design consisted of two stages: 46 Italian active players (41m, 5f; age 32±7,1ys; education 14,8±3ys) fulfilled the PGSI in a secure IT web system and uploaded their own hand history files, which were anonymized and then evaluated by two poker experts. 36 of these players (31m, 5f; age 33±7,3ys; education 15±3ys) accepted to take part in the second stage: the administration of an extensive neuropsychological test battery by a blinded trained professional. To answer the main research question we collected all final and intermediate scores of the EF tests on each player together with the scoring on the playing ability. To answer the secondary research question, we referred to GRCS, PGSI and SOGS scores.  We determined which variables that are good predictors of the playing ability score using statistical techniques able to deal with many regressors and few observations (LASSO, best subset algorithms and CART). In this context information criteria and cross-validation errors play a key role for the selection of the relevant regressors, while significance testing and goodness-of-fit measures can lead to wrong conclusions.

     

    Preliminary findings

    We found significant predictors of the poker ability score in various tests. In particular, there are good predictors 1) in some Wisconsin Card Sorting Test items that measure flexibility in choosing strategy of problem-solving, strategic planning, modulating impulsive responding, goal setting and self-monitoring, 2) in those Cognitive Estimates Test variables related to deductive reasoning, problem solving, development of an appropriate strategy and self-monitoring, 3) in the Emotional Quotient Inventory Short (EQ-i:S) Stress Management score, composed by the Stress Tolerance and Impulse Control scores, and in the Interpersonal score (Empathy, Social Responsibility, Interpersonal Relationship). As for the quality of gambling, some EQ-i:S scales scores provide the best predictors: General Mood for the PGSI; Intrapersonal (Self-Regard; Emotional Self-Awareness, Assertiveness, Independence, Self-Actualization) and Adaptability  (Reality Testing, Flexibility, Problem Solving) for the SOGS, Adaptability for the GRCS.

    Implications for the field

    Through PokerMapper we gathered knowledge and evaluated the feasibility of the construction of short tasks/card games in online poker environments for profiling users’ executive functions. These card games will be part of an IT system able to dynamically profile EF and provide players with a feedback on their expected performance and ability to gamble responsibly in that particular moment. The implementation of such system in existing gambling platforms could lead to an effective proactive tool for supporting responsible gambling. 

  • 38.
    Schiavella, Mauro
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Pelagatti, Matteo
    University Milano-Bicocca.
    Lepore, Gabriele
    Sisal Poker.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Cherubini, Paolo
    University Milano-Bicocca.
    PokerMapper: Final report2015Report (Other academic)
  • 39. Schiavella, Mauro
    et al.
    Pelagatti, Matteo
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Lepore, Gabriele
    Cherubini, Paolo
    Profiling online poker players: Are executive functions correlated with poker ability and problem gambling?2018In: Journal of Gambling Studies, ISSN 1050-5350, E-ISSN 1573-3602, Vol. 34, no 3, p. 823-851Article in journal (Refereed)
    Abstract [en]

    Poker playing and responsible gambling both entail the use of the executive functions (EF), which are higher-level cognitive abilities. This study investigated if online poker players of different ability showed different performances in their EF and if so, which functions were the most discriminating for their playing ability. Furthermore, it assessed if the EF performance was correlated to the quality of gambling, according to self-reported questionnaires (PGSI, SOGS, GRCS). Three poker experts evaluated anonymized poker hand history files and, then, a trained professional administered an extensive neuropsychological test battery. Data analysis determined which variables of the tests correlated with poker ability and gambling quality scores. The highest correlations between EF test results and poker ability and between EF test results and gambling quality assessment showed that mostly different clusters of executive functions characterize the profile of the strong(er) poker player and those ones of the problem gamblers (PGSI and SOGS) and the one of the cognitions related to gambling (GRCS). Taking into consideration only the variables overlapping between PGSI and SOGS, we found some key predictive factors for a more risky and harmful online poker playing: a lower performance in the emotional intelligence competences (Emotional Quotient inventory Short) and, in particular, those grouped in the Intrapersonal scale (emotional self-awareness, assertiveness, self-regard, independence and self-actualization).

  • 40. Senek, Marina
    et al.
    Aquilonius, Sten-Magnus
    Askmark, Håkan
    Bergquist, Filip
    Constantinescu, Radu
    Ericsson, Anders
    Lycke, Sara
    Memedi, Mevludin
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Nyholm, Dag
    Levodopa/carbidopa microtablets in Parkinson's disease: a study of pharmacokinetics and blinded motor assessment2017In: European Journal of Clinical Pharmacology, ISSN 0031-6970, E-ISSN 1432-1041, Vol. 73, no 5, p. 563-571Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Motor function assessments with rating scales in relation to the pharmacokinetics of levodopa may increase the understanding of how to individualize and fine-tune treatments.

    OBJECTIVES: This study aimed to investigate the pharmacokinetic profiles of levodopa-carbidopa and the motor function following a single-dose microtablet administration in Parkinson's disease.

    METHODS: This was a single-center, open-label, single-dose study in 19 patients experiencing motor fluctuations. Patients received 150% of their individual levodopa equivalent morning dose in levodopa-carbidopa microtablets. Blood samples were collected at pre-specified time points. Patients were video recorded and motor function was assessed with six UPDRS part III motor items, dyskinesia score, and the treatment response scale (TRS), rated by three blinded movement disorder specialists.

    RESULTS: AUC0-4/dose and C max/dose for levodopa was found to be higher in Parkinson's disease patients compared with healthy subjects from a previous study, (p = 0.0008 and p = 0.026, respectively). The mean time to maximum improvement in sum of six UPDRS items score was 78 min (±59) (n = 16), and the mean time to TRS score maximum effect was 54 min (±51) (n = 15). Mean time to onset of dyskinesia was 41 min (±38) (n = 13).

    CONCLUSIONS: In the PD population, following levodopa/carbidopa microtablet administration in fasting state, the Cmax and AUC0-4/dose were found to be higher compared with results from a previous study in young, healthy subjects. A large between subject variability in response and duration of effect was observed, highlighting the importance of a continuous and individual assessment of motor function in order to optimize treatment effect.

  • 41.
    Thomas, Ilias
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Bergquist, Filip
    Johansson, Dongni
    Memedi, Mevludin
    Nyholm, Dag
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Sensor-based algorithmic dosing suggestions for oral administration of levodopa/carbidopa microtablets for Parkinson's disease: a first experience2019In: Journal of Neurology, ISSN 0340-5354, E-ISSN 1432-1459, Vol. 266, no 3, p. 651-658Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE: Dosing schedules for oral levodopa in advanced stages of Parkinson's disease (PD) require careful tailoring to fit the needs of each patient. This study proposes a dosing algorithm for oral administration of levodopa and evaluates its integration into a sensor-based dosing system (SBDS).

    MATERIALS AND METHODS: In collaboration with two movement disorder experts a knowledge-driven, simulation based algorithm was designed and integrated into a SBDS. The SBDS uses data from wearable sensors to fit individual patient models, which are then used as input to the dosing algorithm. To access the feasibility of using the SBDS in clinical practice its performance was evaluated during a clinical experiment where dosing optimization of oral levodopa was explored. The supervising neurologist made dosing adjustments based on data from the Parkinson's KinetiGraph™ (PKG) that the patients wore for a week in a free living setting. The dosing suggestions of the SBDS were compared with the PKG-guided adjustments.

    RESULTS: The SBDS maintenance and morning dosing suggestions had a Pearson's correlation of 0.80 and 0.95 (with mean relative errors of 21% and 12.5%), to the PKG-guided dosing adjustments. Paired t test indicated no statistical differences between the algorithmic suggestions and the clinician's adjustments.

    CONCLUSION: This study shows that it is possible to use algorithmic sensor-based dosing adjustments to optimize treatment with oral medication for PD patients.

  • 42.
    Thomas, Ilias
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Bergquist, Filip
    Senek, Marina
    Nyholm, Dag
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Individual levodopa dosing suggestions based on a single dose test2016Conference paper (Other academic)
  • 43.
    Thomas, Ilias
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nyholm, Dag
    Senek, Marina
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Individual dose-response models for levodopa infusion dose optimization2018In: International Journal of Medical Informatics, ISSN 1386-5056, E-ISSN 1872-8243, Vol. 112, p. 137-142Article in journal (Refereed)
    Abstract [en]

    Background and Objective

    To achieve optimal effect with continuous infusion treatment in Parkinson’s disease (PD), the individual doses (morning dose and continuous infusion rate) are titrated by trained medical personnel. This study describes an algorithmic method to derive optimized dosing suggestions for infusion treatment of PD, by fitting individual dose-response models. The feasibility of the proposed method was investigated using patient chart data.

    Methods

    Patient records were collected at Uppsala University hospital which provided dosing information and dose-response evaluations. Mathematical optimization was used to fit individual patient models using the records’ information, by minimizing an objective function. The individual models were passed to a dose optimization algorithm, which derived an optimized dosing suggestion for each patient model.

    Results

    Using data from a single day’s admission the algorithm showed great ability to fit appropriate individual patient models and derive optimized doses. The infusion rate dosing suggestions had 0.88 correlation and 10% absolute mean relative error compared to the optimal doses as determined by the hospital’s treating team. The morning dose suggestions were consistency lower that the optimal morning doses, which could be attributed to different dosing strategies and/or lack of on-off evaluations in the morning.

    Conclusion

    The proposed method showed promise and could be applied in clinical practice, to provide the hospital personnel with additional information when making dose adjustment decisions.

  • 44.
    Thomas, Ilias
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Senek, Marina
    Uppsala University Hospital.
    Dag, Nyholm
    Uppsala University Hospital.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Minimizing levodopa titration period for Parkinson’s disease2016Conference paper (Other academic)
  • 45.
    Thomas, Ilias
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Memedi, Mevludin
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Nyholm, Dag
    The effect of continuous levodopa treatment during the afternoon hours2019In: Acta Neurologica Scandinavica, ISSN 0001-6314, E-ISSN 1600-0404, Vol. 139, no 1, p. 70-75Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE: The aim of this retrospective study was to investigate if patients with PD, who are treated with levodopa-carbidopa intestinal gel (LCIG), clinically worsen during the afternoon hours and if so, to evaluate whether this occurs in all LCIG-treated patients or in a sub-group of patients.

    METHODS: Three published studies were identified and included in the analysis. All studies provided individual response data assessed on the treatment response scale (TRS) and patients were treated with continuous LCIG. Ninety-eight patients from the three studies fulfilled the criteria. T-tests were performed to find differences on the TRS values between the morning and the afternoon hours, linear mixed effect models were fitted on the afternoon hours' evaluations to find trends of wearing-off, and patients were classified into three TRS categories (meaningful increase in TRS, meaningful decrease in TRS, non -meaningful increase or decrease).

    RESULTS: In all three studies significant statistical differences were found between the morning TRS values and the afternoon TRS values (p-value <= 0.001 in all studies). The linear mixed effect models had significant negative coefficients for time in two studies, and 48 out of 98 patients (49%) showed a meaningful decrease of TRS during the afternoon hours.

    CONCLUSION: The results from all studies were consistent, both in the proportion of patients in the three groups and the value of TRS decrease in the afternoon hours. Based on these findings there seems to be a group of patients with predictable "off" behavior in the later parts of the day. This article is protected by copyright. All rights reserved.

  • 46.
    Thomas, Ilias
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Bergquist, F.
    Nyholm, D.
    Senek, M.
    Memedi, Mevludin
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    A treatment–response index from wearable sensors for quantifying Parkinson's disease motor states2018In: IEEE journal of biomedical and health informatics, ISSN 2168-2194, E-ISSN 2168-2208, Vol. 22, no 5, p. 1341-1349Article in journal (Refereed)
    Abstract [en]

    The goal of this study was to develop an algorithm that automatically quantifies motor states (off,on,dyskinesia) in Parkinson's disease (PD), based on accelerometry during a hand pronation-supination test. Clinician's ratings using the Treatment Response Scale (TRS), ranging from -3 (very Off) to 0 (On) to +3 (very dyskinetic), was used as target. For that purpose, 19 participants with advanced PD and 22 healthy persons were recruited in a single center open label clinical trial in Uppsala, Sweden. The trial consisted of single levodopa dose experiments for the people with PD (PwP), where participants were asked to perform standardized wrist rotation tests, using each hand, before and at pre-specified time points after the dose. The participants used wrist sensors containing a 3D accelerometer and gyroscope. Features to quantify the level, variation and asymmetry of the sensor signals, three-level Discrete Wavelet Transform features and approximate entropy measures were extracted from the sensors data. At the time of the tests, the PwP were video recorded. Three movement disorder specialists rated the participants’ state on the TRS scale. A Treatment Response Index from Sensors (TRIS) was constructed to quantify the motor states based on the wrist rotation tests. Different machine learning algorithms were evaluated to map the features derived from the sensor data to the ratings provided by the three specialists. Results from cross validation, both in 10-fold and a leave-one-individual out setting, showed good predictive power of a support vector machine model and high correlation to the TRS scale. Values at the end tails of the TRS scale were under and over predicted due to the lack of observations at those values but the model managed to accurately capture the dose - effect profiles of the patients. In addition, the TRIS had good test-retest reliability on the baseline levels of the PD participants (Intraclass correlation coefficient of 0.83) and reasonable sensitivity to levodopa treatment (0.33 for the TRIS). For a series of test occasions the proposed algorithms provided dose - effect time profiles for participants with PD, which could be useful during therapy individualization of people suffering from advanced PD

  • 47.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Decision support for treatment of patients with advanced Parkinson’s disease2010Doctoral thesis, monograph (Other academic)
    Abstract [en]

    The overall aim of this thesis was to develop, deploy and evaluate new IT-based methods for supporting treatment and assessment of treatment of advanced Parkinson’s disease. In this condition a number of different motor and non-motor symptoms occur in episodes of varying frequency, duration and severity. In order to determine outcome of treatment changes, repeated assessments are necessary. Hospitalization for observation is expensive and may not be representative for the situation at home. Paper home diaries have questionable reliability and storage and retrieval of results are problematic. Approaches for monitoring using wearable sensors are unable to address important non-motor symptoms. A test battery system consisting of both self-assessments of symptoms and motor function tests was constructed for a touch screen mobile phone. Tests are performed on several occasions per day during test periods of one week. Data is transmitted over the mobile net to a central server where summaries in different symptom dimensions and an overall test score per patient and test period are calculated. There is a web application that graphically presents the results to treating clinical staff. As part of this work, a novel method for assessment of spiral drawing impairment useful during event-driven sampling was developed. To date, the system has been used by over 100 patients in 10 clinics in Sweden and Italy. Evidence is growing that the test battery is useful, reliable and valid for assessment of symptoms during advanced Parkinson’s disease. Infusion of a levodopa/carbidopa gel into the small intestine has been shown to reduce variation in plasma drug levels and improve clinical response in this patient category. A pharmacokinetic-pharmacodynamic model of this intestinal gel infusion was constructed. Possibly this model can assist the process of individualization of dosage for this treatment through in numero simulations. Results from an exploratory data analysis indicate that severity measures during oral levodopa treatment may be factors to consider when deciding candidates for infusion treatment.

  • 48.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Improved assessment of patients with motor fluctuations, using an electronic diary combining standardized questionnaires and motor tests.2008In: The 8th Scandinavian Orion Pharma/Solvay Pharma sponsored meeting / [ed] Pedersen, Stephen Wörlich, Stockholm, Sweden, 2008, Vol. 20070330Conference paper (Refereed)
    Abstract [en]

    A test battery for assessing patient state in advanced Parkinson’s disease consisting of diary assessments and motor tests (tapping and spiral drawing) was constructed and implemented on a hand computer with touch screen and built-in mobile communication. The test battery should be used several times daily in the home environment over test periods of about one week. An evaluation with two pilot patients was performed before and after receiving new treatments and compliance is being assessed in an ongoing clinical trial.

  • 49.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Remote monitoring of movement disorders2013In: Recent Patents on Biomedical Engineering, ISSN 1874-7647, Vol. 6, no 2, p. 81-Article in journal (Refereed)
    Abstract [en]

    Remote monitoring technologies provide means for low-cost, long-term, frequent and repeated assessments of patients, havingpotential to improve the quality and efficiency of care and increase treatment compliance. This thematic issue covers methodsand apparatuses aimed for remote detection and quantification of impairments related to movement disorders such as Parkinson’sdisease, tremors and related disorders. Instances of this include electronic diaries, body-attached sensors, and videobasedassessment systems to name a few. Accurate and timely symptom information has a real potential of improving patients’quality of life since some symptoms are in fact treatable although timing and individualization of treatment delivery are essential.Today assessments of motor symptoms and follow-up of treatments are primarily done by using clinical ratings based onobservations and judgments by physicians or by patient home diaries. More objective assessment methods for quantifying motorfunction can complement and enhance the physician and patient perspectives. Recent advances in micro-electro-mechanical,wireless and internet technologies are now making this option possible, along with a gradual acceptance from the medical profession.The issue contains five articles discussing recent innovations concerning different types of wearable sensors, video processing,different testing devices and related aspects on data transfer and processing. The contexts of the articles are different assome focus on a technology and some on a phenomenon to monitor. Topics about how to manage devices for symptom monitoringby input control innovations are also covered. One article focuses on the state of art and technical challenges associatedwith the hardware design of novel wearable movement sensors appropriate for biomedical applications. Another article reviewspatents of computerized gait disorder analysis with a special focus on computer vision. A third article provides a review of recentpatents focused on detection and quantification of human tremor. Another article focuses on technology with the aim toallow people with movement disorders to control their environment including input devices in form of switches and touchscreens, inertia and inclinometer sensors, voice control and gesture control. One article reviews patents concerning assessmentsof patients through repeated measurements which take into account subjective and objective health indicators.With an aging world population, there is a projected increase globally in neurological diagnoses including common movementdisorders. The number of sufferers from Parkinson’s disease will be around 10 million in 2030, which is about twice thenumber today. In combination with well-known limiting resources in society, this will lead to strong demands for efficiency inthe healthcare sector. Caregiver organizations of today are becoming increasingly more mature in adopting monitoring technologyin their practice, which opens up opportunities for technology providers. Successful adoption of adequate remote monitoringtechnologies may lead to better access to healthcare, not least for patients in developing countries.

  • 50.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Slutrapport PAULINA2015Report (Other academic)
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