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  • 51. Siril, Yella
    et al.
    Askar, Kalid
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Expert system to calculate the cofficient of friction: an approach to enhance traffic safety2004Ingår i: Cybernetics and Intelligent Systems, 2004 IEEE Conference on, Singapore, 2004, Vol. 2, s. 803-808Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    Friction plays a key role in causing slipperiness as a low coefficient of friction on the road may result in slippery and hazardous conditions. Analyzing the strong relation between friction and accident risk on winter roads is a difficult task. Many weather forecasting organizations use a variety of standard and bespoke methods to predict the coefficient of friction on roads. This article proposes an approach to predict the extent of slipperiness by building and testing an expert system. It estimates the coefficient of friction on winter roads in the province of Dalarna, Sweden using the prevailing weather conditions as a basis. Weather data from the road weather information system, Sweden (RWIS) was used. The focus of the project was to use the expert system as a part of a major project in VITSA, within the domain of intelligent transport systems

  • 52.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Ahmed, M. U.
    Nyholm, D.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Groth, T.
    A fuzzy rule-based decision support system for Duodopa treatment in Parkinson's disease2006Ingår i: European Journal of Neurology, ISSN 1351-5101, E-ISSN 1468-1331, Vol. 13, nr s2, s. 214-214Artikel i tidskrift (Övrigt vetenskapligt)
  • 53.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Groth, Torgny
    IDOL Project (KKS-2002/0203) Final Report: Decision support in advanced Parkinson2006Rapport (Övrigt vetenskapligt)
  • 54.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Groth, Torgny
    Nyholm, Dag
    Movement disorder monitoring2006Patent (Övrig (populärvetenskap, debatt, mm))
    Abstract [en]

    A test battery (10) for patients having fluctuating movement disorder, e.g. Parkinson's disease, comprises both a motor test section (17) and a patient diary collection section (19) collecting data representing patient subjective experiences. The test battery (10) further comprises a scheduler (20), which is arranged to restrict operation of the motor test section (17) and the patient diary collection section (19) to a multitude of predetermined limited time intervals. This restriction in time provides an association in time between the two types of tests, as well as a possibility for timing the test intervals dependent on e.g. the medication schedule or the daily activity schedule. The limited time intervals are preferably shorter than or equal to one hour, and preferably there is at least one limited time interval each 24 hours. The test battery (10) is preferably implemented as a portable device, enabling monitoring under home environment conditions.

  • 55.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Nyholm, D.
    Groth, T.
    A home environment test battery for status assessment in patients with motor fluctuations2006Ingår i: European Journal of Neurology, ISSN 1351-5101, E-ISSN 1468-1331, Vol. 13, nr s2, s. 213-214Artikel i tidskrift (Övrigt vetenskapligt)
  • 56.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Nyholm, Dag
    Groth, Torgny
    A home environment test battery for status assessment in patients with advanced Parkinson's disease2010Ingår i: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 98, nr 1, s. 27-35Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A test battery for assessing patient state in advanced Parkinson's disease, consisting of self-assessments and motor tests, was constructed and implemented on a hand computer with touch screen in a telemedicine setting. The aim of this work was to construct an assessment device, applicable during motor fluctuations in the patient's home environment. Selection of self-assessment questions was based on questions from an e-diary, previously used in a clinical trial. Both un-cued and cued tapping tests and spiral drawing tests were designed for capturing upper limb stiffnes, slowness and involuntary movements. The patient interface gave an audible signal at scheduled response times and was locked otherwise. Data messages in an XML-format were sent from the hand unit to a central server for storage, processing and presentation. In tapping tests, speed and accuracy were calculated and in spiral tests, standard deviation of frequency filtered radial drawing velocity was calculated. An overall test score, combining repeated assessments of the different test items during a test period, was defined based on principal component analysis and linear regression. An evaluation with two pilot patients before and after receiving new types of treatments was performed. Compliance and usability was assessed in a clinical trial (65 patients with advanced Parkinson's disease) and correlations between different test items and internal consistency were investigated. The test battery could detect treatment effect in the two pilot patients, both in self-assessments, tapping tests' results and spiral scores. It had good patient compliance and acceptable usability according to nine nurses. Correlation analysis showed that tapping results provided different information as compared to diary responses. Internal consistency of the test battery was good and learning effects in the tapping tests were small. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

  • 57.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Nyholm, Dag
    Groth, Torgny
    A home environment test battery for status assessment in patients with motor fluctuations2006Ingår i: European Journal of Neurology, Glasgow, UK, 2006, Vol. 13, s. 213-14Konferensbidrag (Refereegranskat)
    Abstract [en]

    Background and aims Evaluating status in patients with motor fluctuations is complex and occasional observations/measurements do not give an adequate picture as to the time spent in different states. We developed a test battery to assess advanced Parkinson patients' status consisting of diary assessments and motor tests. This battery was constructed and implemented on a handheld computer with built-in mobile communication. In fluctuating patients, it should typically be used several times daily in the home environment, over periods of about one week. The aim of this battery is to provide status information in order to evaluate treatment effects in clinical practice and research, follow up treatments and disease progression and predict outcome to optimize treatment strategy. Methods Selection of diary questions was based on a previous study with Duodopa® (DIREQT). Tapping tests (with and without visual cueing) and a spiral drawing test were added. Rapid prototyping was used in development of the user interface. An evaluation with two pilot patients was performed before and after receiving new treatments for advanced disease (one received Duodopa® and one received DBS). Speed and proportion missed taps were calculated for the tapping tests and entropy of the radial drawing velocity was calculated for the spiral tests. Test variables were evaluated using non-parametric statistics. Results Post-treatment improvement was detected in both patients in many of the test variables. Conclusions Although validation work remains, preliminary results are promising and the test battery is currently being evaluated in a long-term health economics study with Duodopa® (DAPHNE).

  • 58.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Nyholm, Dag
    Groth, Torgny
    Analysis of tapping test results in a test battery for advanced PD patients2008Ingår i: Movement Disorders, 2008; :, Chicago, IL, USA, 2008, Vol. 23, s. 84-85Konferensbidrag (Refereegranskat)
    Abstract [en]

    Objective: To compare results from various tapping tests with diary responses in advanced PD. Background: A home environment test battery for assessing patient state in advanced PD, consisting of diary assessments and motor tests was constructed for a hand computer with touch screen and mobile communication. The diary questions: 1. walking, 2. time in off , on and dyskinetic states, 3. off at worst, 4. dyskinetic at worst, 5. cramps, and 6. satisfied with function, relate to the recent past. Question 7, self-assessment, allows seven steps from -3 ( very off ) to +3 ( very dyskinetic ) and relate to right now. Tapping tests outline: 8. Alternately tapping two fields (un-cued) with right hand 9. Same as 8 but using left hand 10. Tapping an active field (out of two) following a system-generated rhythm (increasing speed) with the dominant hand 11. Tapping an active field (out of four) that randomly changes location when tapped using the dominant hand Methods: 65 patients (currently on Duodopa, or candidates for this treatment) entered diary responses and performed tapping tests four times per day during one to six periods of seven days length. In total there were 224 test periods and 6039 test occasions. Speed for tapping test 10 was discardedand tests 8 and 9 were combined by taking means. Descriptive statistics were used to present the variation of the test variables in relation to self assessment (question 7). Pearson correlation coefficients between speed and accuracy (percent correct) in tapping tests and diary responses were calculated. Results: Mean compliance (percentage completed test occasions per test period) was 83% and the median was 93%. There were large differences in both mean tapping speed and accuracy between the different self-assessed states. Correlations between diary responses and tapping results were small (-0.2 to 0.3, negative values for off-time and dyskinetic-time that had opposite scale directions). Correlations between tapping results were all positive (0.1 to 0.6). Conclusions: The diary responses and tapping results provided different information. The low correlations can partly be explained by the fact that questions related to the past and by random variability, which could be reduced by taking means over test periods. Both tapping speed and accuracy reflect the motor function of the patient to a large extent.

  • 59.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Nyholm, Dag
    Groth, Torgny
    Patient Diary Test Battery2005Patent (Övrig (populärvetenskap, debatt, mm))
  • 60.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Ghiamati Yazdi, Samira
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Memedi, Mevludin
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Nyholm, D.
    Johansson, A.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Groth, T.
    A successful computer method for assessing drawing impairment in Parkinson's disease2009Ingår i: European Journal of Neurology, ISSN 1351-5101, E-ISSN 1468-1331, Vol. 16, s. 559-559Artikel i tidskrift (Övrigt vetenskapligt)
  • 61.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Ghiamati Yazdi, Samira
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Memedi, Mevludin
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Nyholm, Dag
    Johansson, Anders
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Groth, Torgny
    A new computer method for assessing drawing impairment in Parkinson's disease2010Ingår i: Journal of Neuroscience Methods, ISSN 0165-0270, E-ISSN 1872-678X, Vol. 190, nr 1, s. 143-148Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A test battery, consisting of self-assessments and motor tests (tapping and spiral drawing tasks) was used on 9482 test occasions by 62 patients with advanced Parkinson's disease (PD) in a telemedicine setting. On each test occasion, three Archimedes spirals were traced. A new computer method, using wavelet transforms and principal component analysis processed the spiral drawings to generate a spiral score. In a web interface, two PD specialists rated drawing impairment in spiral drawings from three random test occasions per patient, using a modification of the Bain & Findley 10-category scale. A standardised manual rating was defined as the mean of the two raters' assessments. Bland-Altman analysis was used to evaluate agreement between the spiral score and the standardised manual rating. Another selection of spiral drawings was used to estimate the Spearman rank correlations between the raters (r = 0.87), and between the mean rating and the spiral score (r = 0.89). The 95% confidence interval for the method's prediction errors was +/- 1.5 scale units, which was similar to the differences between the human raters. In conclusion, the method could assess PD-related drawing impairments well comparable to trained raters.

  • 62.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Memedi, Mevludin
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Ghiamati Yazdi, Samira
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Nyholm, Dag
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Groth, Torgny
    Defining a test score for status assessment during motor fluctuations in Parkinson's disease2009Ingår i: The Movement Disorder Society's 13th International Congress of Parkinson's Disease and Movement Disorders, Paris, 2009Konferensbidrag (Refereegranskat)
    Abstract [en]

    Objective: To define and evaluate a computer method for assessing drawing impairment in spiral drawings. To define an overall score, summarizing self-assessments and motor test data from a test battery for patients with advanced Parkinson's disease (PD). Background: A test battery, consisting of self-assessments (modified PDQ-8) and motor tests (tapping and spiral drawing) was developed for a hand computer with touch screen in a telemedicine setting. Assessments and tests were carried out four times per day in a group of 65 patients with advanced PD (Duodopa treated or candidates) during 1-6 weekly test periods each. For most test periods, UPDRS ratings were available. Methods: In a web interface, a PD specialist assessed drawing impairment in 505 selected spiral drawings, representing all categories on the Bain & Findley 10-category scale. A computer method, using wavelet transforms and principal component analysis, processed the same spirals to generate a 'spiral score'. According to the PD specialist and co-author Dr Nyholm, the information content of a test period with the test battery could be descibed by six dimensions, 'off', 'dyskinesia', 'walking', 'satisfaction', 'spiral', and 'tapping'. Each dimension was defined as the first principal component of the level (mean) and fluctuation (standard deviation) for the questions or tests that this dimension is based on. Tapping dimension was based on both speed and accuracy. To obtain weights for an overall score, linear regression of the dimensions vs. simultaneous UPDRS ratings was performed. To assess the internal consistency of the test battery, Cronbach's Alpha for the six dimensions was calculated. Results: Pearson correlation between spiral score and clinical rating of drawing impairment was 0.87. Weights in overall test score were (%): spirals, 41, tapping, 24, satisfied, 19, dyskinetic, 10, walking, 5.4 and off, 0.1. Internal consistency for the dimensions was 0.81. Conclusions: The computer generated spiral score was strongly correlated to clinical assessment of drawing impairment. Spirals were assigned highest weight in overall score, reflecting the high weight of motor function in total UPDRS. Internal consistency was strong, implying all dimensions represent aspects of a common characteristic.

  • 63.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Nyholm, Dag
    Groth, Torgny
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Pålhagen, Sven
    Analysis of response to enteral infusion of levodopa in patients with Parkinson's disease2004Ingår i: Movement Disorders 2004; 19(S9):165-166, Rome, 2004, Vol. PosterKonferensbidrag (Refereegranskat)
    Abstract [en]

    Objective: We present a new evaluation of levodopa plasma concentrations and clinical effects during duodenal infusion of a levodopa/carbidopa gel (Duodopa ) in 12 patients with advanced Parkinson s disease (PD), from a study reported previously (Nyholm et al, Clin Neuropharmacol 2003; 26(3): 156-163). One objective was to investigate in what state of PD we can see the greatest benefits with infusion compared with corresponding oral treatment (Sinemet CR). Another objective was to identify fluctuating response to levodopa and correlate to variables related to disease progression. Methods: We have computed mean absolute error (MAE) and mean squared error (MSE) for the clinical rating from -3 (severe parkinsonism) to +3 (severe dyskinesia) as measures of the clinical state over the treatment periods of the study. Standard deviation (SD) of the rating was used as a measure of response fluctuations. Linear regression and visual inspection of graphs were used to estimate relationships between these measures and variables related to disease progression such as years on levodopa (YLD) or unified PD rating scale part II (UPDRS II). Results: We found that MAE for infusion had a strong linear correlation to YLD (r2=0.80) while the corresponding relation for oral treatment looked more sigmoid, particularly for the more advanced patients (YLD>18).

  • 64.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Nyholm, Dag
    Groth, Torgny
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Yerramsetty, Praveen
    Pålhagen, Sven
    Outcome prediction of enteral levodopa/carbidopa infusion in advanced Parkinson's disease2006Ingår i: Parkinsonism & Related Disorders, ISSN 1353-8020, E-ISSN 1873-5126, Vol. 12, nr 8, s. 509-513Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Two studies comparing intraduodenal infusion of a levodopa/carbidopa gel with oral treatments in advanced PD patients, demonstrated improvement in UPDRS scores and in frequent clinical ratings on a global treatment response scale. Further analysis of data from these studies was performed to find predictive factors related to degree of improvement with infusion. Pearson correlation coefficients between measures of improvement and baseline variables were calculated. Using data from one study, a prediction model was designed and was then evaluated using the other study’s data. Correlations were found indicating that patients with more severe symptoms at baseline were most improved after infusion.

  • 65.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Nyholm, Dag
    Groth, Torgny
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Yerramsetty, Praveen
    Pålhagen, Sven
    The most severe parkinsonian patients are most improved with duodenal levodopa infusion2005Ingår i: Parkinsonism & Related Disorders 2005; 11(S2):216, Berlin, 2005, Vol. PosterKonferensbidrag (Refereegranskat)
    Abstract [en]

    Objectives: To find variables correlated to improvement with intraduodenal levodopa/carbidopa infusion (Duodopa) in order to identify potential candidates for this treatment. Two clinical studies comparing Duodopa with oral treatments in patients with advanced Parkinson’s disease have shown significant improvement in percent on-time on a global treatment response scale (TRS) based on hourly and half-hourly clinical ratings and in median UPDRS scores. Methods: Data from study 1 comparing infusion with Sinemet CR (12 patients, Nyholm et al, Clin Neuropharmacol 2003; 26(3): 156-163) and study 2 comparing infusion with individually optimised conventional combination therapies (18 patients, Nyholm et al, Neurology, in press) were used. Measures of severity were defined as total UPDRS score and scores for sections II and III, percent functional on-time and mean squared error of ratings on the TRS and as mean of diary questions about mobility and satisfaction (only study 2). Absolute improvement was defined as difference in severity, and relative improvement was defined as percent absolute improvement/severity on oral treatment. Pearson correlation coefficients between measures of improvement and other variables were calculated. Results: Correlations (r2>0.28, p<0.05) between severity during oral treatment and absolute improvement on infusion were found for: Total UPDRS, UPDRS III and TRS ratings (studies 1 and 2) and for diary question 1 (mobility) and UPDRS II (study 2). Correlation to relative improvement was found for total UPDRS (study 2, r2=0.47). Figure 1 illustrates absolute improvement in total UPDRS vs. total UPDRS during oral treatment (study 2). Conclusion: Correlating different measures of severity and improvement revealed that patients with more severe symptoms were most improved and that the relation between severity and improvement was linear within the studied groups. The result, which was reproducible between two clinical studies, could be useful when deciding candidates for the treatment.

  • 66.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Nyholm, Dag
    Johansson, Anders
    Memedi, Mevludin
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Groth, Torgny
    Pålhagen, Sven
    12-month results from a novel test battery used in a duodenal levodopa infusion trial2010Ingår i: European Journal of Neurology, ISSN 1351-5101, E-ISSN 1468-1331, Vol. 17, nr s3, s. 21-21Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A novel test battery consisting of self-assessments and motor tests (tapping and spiral drawing) for patients with Parkinson’s disease (PD) was developed for a hand computer with touch screen in a telemedicine setting. Tests are performed four times per day in the home environment during weeklong test periods. Results are processed into scores for different dimensions of the symptom state and an ‘overall score’ reflecting the global condition of a patient during a test period. The test battery was validated in a separate study recently submitted to Mov Disord. This test battery is currently being used in an open longitudinal trial (DAPHNE, EudraCT No. 2005- 002654-21) by sixty-five patients with advanced PD at nine clinics around Sweden. On inclusion, the patients were either receiving treatment with duodenal levodopa/carbidopa infusion (Duodopa®) (n=36), or they were candidates for receiving this treatment (n=29). We now present interim results for the first twelve months. Test periods were performed in three-month intervals. During most of the periods, UPDRS ratings were performed in afternoons at the start of the week. In twenty of the patients, scores were available during individually optimized oral polypharamacy, before receiving infusion and at least one test period after having started infusion treatment. Usability and compliance with performing tests, this far are good, both with patients and clinical staff. Correlations between test periods 2 and 3 during infusion treatment (three months apart) are stronger for overall test score than for total UPDRS, indicating good reliability. The correlation between overall test score and UPDRS for all test periods is adequate (r=-0.6). In an exact Wilcoxon signed rank test, where the endpoint is the change from the first to the twelve month test period (n=25), there was no change in test results in any of the test battery dimensions for the patients already receiving infusion when included. However, in the patients entering the study before receiving infusion, there was a significant change (improvement) from the baseline to the twelve month test period in dimensions; ‘off’, ‘dyskinesia’ and ‘satisfied’ and in the ‘overall score’ (n=15). The mean improvement in overall score after infusion was 29% (p=0.015). We conclude that the test battery is able to measure a functional improvement with infusion that is sustained over at least twelve months.

  • 67.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Nyholm, Dag
    Pålhagen, Sven
    Willows, Thomas
    Groth, Torgny
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Karlsson, Mats
    A pharmacokinetic-pharmacodynamic model for duodenal levodopa infusion2011Ingår i: Clinical neuropharmacology, ISSN 0362-5664, E-ISSN 1537-162X, Vol. 32, nr 2, s. 61-65Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Objective: The purpose of this work was to identify and estimate a population pharmacokinetic- pharmacodynamic model for duodenal infusion of a levodopa/carbidopa gel (Duodopa) to examine pharmacological properties of this treatment.

    Methods: The modeling involved pooling data from 3 studies (on advanced Parkinson disease) and fixing some parameters to values found in literature. The first study involved 12 patients studied on 3 occasions each and was previously published. The second study involved 3 patients on 2 occasions. A bolus dose was given after a washout during night. Plasma samples and motor ratings (clinical assessment of motor function on a 7-point treatment response scale ranging from "very off" to "very hyperkinetic") were collected until the clinical effect returned to baseline. The third study involved 5 patients on 3 occasions receiving 5 different dose levels. Different structural models were evaluated using the nonlinear mixed-effects modeling program NONMEM VI. Population mean parameter values, and interindividual, interoccasion, and residual variabilities were estimated.

    Results: Absorption of the levodopa/carbidopa gel can be adequately described with first-order absorption with bioavailability and lag time. Estimated population parameter values were a mean absorption time of 28.5 minutes, a lag time of 2.9 minutes, and a bioavailability of 88%. The pharmacodynamic model for motor ratings had the following population values: a half-life of effect delay of 21 minutes, a concentration at 50% effect of 1.55 mg/L, an Emax of 2.39 U on the treatment response scale, and a sigmoidicity of the Emax function of 11.6.

    Conclusions: For the typical unmedicated subject, it will take 51.4 minutes until the peak levodopa effect is reached after a bolus dose. This delay is, like the magnitude of the effect, highly variable in this patient group. The residual error magnitudes of 20% for levodopa concentrations and 0.92 U (SD) for motor ratings indicate that the models developed provide predictions of a relevant quality. The developed model may be a first step toward model-guided treatment individualization of duodenal infusion of levodopa.

  • 68.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Schiavella, Mauro
    Memedi, Mevludin
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Nyholm, Dag
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Antonini, Angelo
    Validation of a home environment test battery for supporting assessments in advanced Parkinson's disease2012Ingår i: Neurological Sciences, ISSN 1590-1874, E-ISSN 1590-3478, Vol. 3, nr 4, s. 831-838Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Test sequences in a test battery for Parkinson’s disease patients, consisting of self-assessments and motor tests, were carried out repeatedly in a telemedicine setting, during week-long test periods and results were summarized in an ‘overall score’. 35 patients in stable and fluctuating conditions (15 age- and gender-matched pairs) used the test battery for 1 week, and were then assessed with UPDRS and PDQ-39. This procedure was repeated 1 week later, without treatment changes. Reliability was assessed by intraclass correlation coefficients and Cronbach’s alpha. Convergent validity was assessed by Spearman rank correlations and known-groups’ validity, by the Mann–Whitney test. According to anonymous usability questionnaires, the patients could easily complete the tasks. Median compliance (93%) and test–retest reliability (0.88) were good. The correlations between overall score and total UPDRS (-0.64) and PDQ-39 (-0.72) were adequate. Median overall score was 18% better in the stable compared to the fluctuating group (p = 0.0014).

  • 69.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Willows, T.
    Groth, T.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Palhagen, S.
    Pedal: Identification of models for duodenal administration of levodopa2006Ingår i: European Journal of Neurology, ISSN 1351-5101, E-ISSN 1468-1331, Vol. 13, nr s2, s. 220-221Artikel i tidskrift (Övrigt vetenskapligt)
  • 70.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Willows, Thomas
    Groth, Torgny
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Karlsson, Mats
    Nyholm, Dag
    Pålhagen, Sven
    A pharmacokinetic-pharmacodynamic model for duodenal levodopa infusion2007Ingår i: Parkinsonism & Related Disorders, Amsterdam, Netherlands, 2007, Vol. 13, s. S102-S103Konferensbidrag (Refereegranskat)
    Abstract [en]

    Objective Levodopa in presence of decarboxylase inhibitors is following two-compartment kinetics and its effect is typically modelled using sigmoid Emax models. Pharmacokinetic modelling of the absorption phase of oral distributions is problematic because of irregular gastric emptying. The purpose of this work was to identify and estimate a population pharmacokinetic- pharmacodynamic model for duodenal infusion of levodopa/carbidopa (Duodopa®) that can be used for in numero simulation of treatment strategies. Methods The modelling involved pooling data from two studies and fixing some parameters to values found in literature (Chan et al. J Pharmacokinet Pharmacodyn. 2005 Aug;32(3-4):307-31). The first study involved 12 patients on 3 occasions and is described in Nyholm et al. Clinical Neuropharmacology 2003:26:156-63. The second study, PEDAL, involved 3 patients on 2 occasions. A bolus dose (normal morning dose plus 50%) was given after a washout during night. Plasma samples and motor ratings (clinical assessment of motor function from video recordings on a treatment response scale between -3 and 3, where -3 represents severe parkinsonism and 3 represents severe dyskinesia.) were repeatedly collected until the clinical effect was back at baseline. At this point, the usual infusion rate was started and sampling continued for another two hours. Different structural absorption models and effect models were evaluated using the value of the objective function in the NONMEM package. Population mean parameter values, standard error of estimates (SE) and if possible, interindividual/interoccasion variability (IIV/IOV) were estimated. Results Our results indicate that Duodopa absorption can be modelled with an absorption compartment with an added bioavailability fraction and a lag time. The most successful effect model was of sigmoid Emax type with a steep Hill coefficient and an effect compartment delay. Estimated parameter values are presented in the table. Conclusions The absorption and effect models were reasonably successful in fitting observed data and can be used in simulation experiments.

  • 71.
    Westin, Jerker
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Willows, Thomas
    Groth, Torgny
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Karlsson, Mats
    Pålhagen, Sven
    Pedal : identification of models for duodenal administration of levodopa2006Ingår i: European Journal of Neurology, Glasgow, UK, 2006, Vol. 13, s. 220-21Konferensbidrag (Refereegranskat)
    Abstract [en]

    Backgound and aims: The main purpose of the PEDAL study is to identify and estimate sample individual pharmacokinetic- pharmacodynamic (PK/PD) models for duodenal infusion of levodopa/carbidopa (Duodopa®) that can be used for in numero simulation of treatment strategies. Other objectives are to study the absorption of Duodopa® and to form a basis for power calculation for a future larger study. PK/PD based on oral levodopa is problematic because of irregular gastric emptying. Preliminary work with data from [Gundert-Remy U et al. Eur J Clin Pharmacol 1983;25:69-72] suggested that levodopa infusion pharmacokinetics can be described by a two-compartment model. Background research led to a hypothesis for an effect model incorporating concentration-unrelated fluctuations, more complex than standard E-max models. Methods: PEDAL involved a few patients already on Duodopa®. A bolus dose (normal morning dose plus 50%) was given after a washout during night. Data collection continued until the clinical effect was back at baseline. The procedure was repeated on two non-consecutive days per patient. The following data were collected in 5 to 15 minutes intervals: i) Accelerometer data. ii) Three e-diary questions about ability to walk, feelings of “off” and “dyskinesia”. iii) Clinical assessment of motor function by a physician. iv) Plasma concentrations of levodopa, carbidopa and the metabolite 3-O-methyldopa. The main effect variable will be the clinical assessment. Results: At date of abstract submission, lab analyses were currently being performed. Modelling results, simulation experiments and conclusions will be presented in our poster.

  • 72.
    Yella, Siril
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Baskar, Jayalakshmi
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Machine vision for analysing the position of fastening nails on wooden railway sleepers2011Ingår i: Signal and Image Processing, 2011 / [ed] Rao, K.R., Dallas, Texas, USA, 2011Konferensbidrag (Refereegranskat)
    Abstract [en]

    Wooden railway sleeper inspections in Sweden and to a large extent elsewhere are carried out manually by a human operator; visual inspection being the most common approach. Manually inspecting railway sleepers is slow and time consuming. Machine vision algorithms investigating surface cracks on the sleeper and sinking of the metal plate have been studied for the purpose of automating the task. In this particular article, information concerning how far the fastening nail has lifted out of position is investigated with an aim of using such information while assessing the condition of the sleeper. Laser beams incident on the sleeper have been used to highlight the geometrical form of the sleeper/plate/nail complex. Digital images of the nail were acquired mimic human visual capabilities. Appropriate image analysis techniques were applied to further process the images and necessary features were extracted. Results of unsupervised learning, achieved in the current work indicate that expectation maximization algorithm produced reliable results.

  • 73.
    Yella, Siril
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Automatically detecting the number of logs on a timber truck2013Ingår i: Journal of Intelligent Systems, ISSN 2191-026X, Vol. 22, nr 4, s. 417-435Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This article describes a method of automatically detecting, counting and classifying logs on a timber truck using a photograph (taken by the driver). An image-processing algorithm is developed to process the photograph to calculate an estimate of the number of logs present and their respective diameters. The algorithm uses color information in multiple color spaces as well as geometrical operators to segment the image and extract the relevant information. This information enables the sawmill to better plan internal logistics and production in advance of the truck’s arrival time. The algorithm is robust with respect to external factors such as varying lighting conditions and camera angle, but some inaccuracies remain, mainly caused by logs being occluded or covered in mud or snow.

  • 74.
    Yella, Siril
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Philosophical challenges concerning education and career orientation in the ITS area2005Ingår i: 10th Euro Working Group in Transportation, Poznan, Poland: Proc 10th Euro Working Group in Transportation , 2005Konferensbidrag (Övrigt vetenskapligt)
  • 75.
    Yella, Siril
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Gupta, N K
    Artificial Intelligence techniques for the automatic interpretation of data from non-destructive testing2006Ingår i: Insight (Northampton), ISSN 1354-2575, E-ISSN 1754-4904, Vol. 48, nr 1, s. 10-20Artikel i tidskrift (Övrigt vetenskapligt)
    Abstract [en]

    This paper attempts to summarise the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from non-destructive testing (NDT). Problems in the rail transport domain are mainly discussed. However, a majority of the emphasis in this paper is laid on rail inspection problems, since it was believed that the review would provide a perfect ground to the authors in pursuing further work within the rail inspection area. NDT is a broad name for a variety of methods and procedures concerned with all aspects of uniformity, quality and serviceability of materials and structures, without causing damage to the material that is being inspected. During the past several years, problems concerning the automatic interpretation of data from NDT have received good attention and have stimulated interests in other areas like transportation, for making key assessments within some of its subject areas. Rail, air and marine industries together with bridge inspection and pavement maintenance are good examples of such areas where a considerable amount of work has been done. Such work neatly splits into two schools. The first school investigates the classical usage of data by an experienced human operator to determine the condition of the inspected material or structure. The other school focuses attention on the automatic interpretation of NDT data using AI techniques, in determining the result of inspection. The scope of this paper is only limited to the automatic interpretation of data from NDT, with the goal of assessing embedded flaws as quickly and accurately as possible in a cost effective fashion. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in the area. A secondary goal was to provide an insight into possible research methods concerning railway sleeper inspection by automatic interpretation of data. A brief introduction is provided for the benefit of the readers unfamiliar with the techniques.

  • 76.
    Yella, Siril
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Gupta, Narendra
    Fuzzy logic approach for automating visual condition monitoring of railway sleepers2007Ingår i: IICAI, Indian International Conference on Artificial Intelligence, Pune, India, 2007Konferensbidrag (Övrigt vetenskapligt)
  • 77.
    Yella, Siril
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Gupta, Narendra K.
    Condition monitoring of wooden railway sleepers2009Ingår i: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 17, nr 1, s. 38-55Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are to large extent based on visual analysis. In this paper a machine vision based approach has been considered to emulate the visual abilities of the human operator to enable automation of the process. Digital images from either ends (left and right) of the sleepers have been acquired. A pattern recognition approach has been adopted to classify the condition of the sleeper into classes (good or bad) and thereby achieve automation. Appropriate image analysis techniques were applied and relevant features such as the number of cracks on a sleeper, average length and width of the crack and the condition of the metal plate were determined. Feature fusion has been proposed in order to integrate the features obtained from each end for the classification task which follows. The effect of using classifiers like multi-layer perceptron and support vector machines has been tested and compared. Results obtained from the experiments show that multi-layer perceptron and support vector machines have achieved encouraging results, with a classification accuracy of 90%; thereby exhibiting a competitive performance when compared to a human operator.

  • 78.
    Yella, Siril
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Gupta, Narendra K.
    Data fusion for automating condition monitoring of wooden railway sleepers2008Ingår i: Insight (Northampton), ISSN 1354-2575, E-ISSN 1754-4904, Vol. 50, nr 7, s. 356-363Artikel i tidskrift (Övrigt vetenskapligt)
    Abstract [en]

    Wooden railway sleeper inspections in Sweden are currently done by hand. That is to say, a human inspector in charge of the maintenance activities visually examines each structure in turn for the presence of cracks on the sleeper. Where necessary some deeper inspection may be carried out on site, for example using an axe to hit and judge the condition of the sleeper by listening to the sound produced. Though the manual procedure uses non-destructive testing methods (visual and sound analysis), decision-making is largely based on intuition; moreover the process is rather slow, expensive and also requires skilled and trained staff. Maintaining an even quality standard is another serious issue. Hence, it is desired to automate the human inspection process by proposing automatic testing procedures for future inspections concerning the condition of the sleeper. Studies based on emulation of the human inspection process have been considered a promising route of enquiry for automation. Such an emulation process is achieved by selecting and evaluating two non-destructive inspection methods. The first method (impact acoustic analysis) aims to build an automatic system to replace the usage of an axe for distinguishing sounds. The second method (visual analysis) is to develop an appropriate machine vision algorithm to replicate the visual examination. Further, the above-mentioned methods were fused (data fusion) to generate a single output condition concerning the condition of the sleeper. In the current work, fusion has been achieved in mainly three levels, namely sensor-level, feature-level and classifier-level. Experimental results achieved in this work indicate that data fusion has achieved superior performance when compared with using data from one method at a time.

  • 79.
    Yella, Siril
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Ghiamati, Samira
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Condition monitoring of wooden railway sleepers using time-frequency techniques and pattern classification2009Ingår i: Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on Systems, San Antonio, Texas, USA, 2009, s. 4164-4169Konferensbidrag (Refereegranskat)
    Abstract [en]

    Railway sleepers are a key engineering element of all railways. Lack of much sophistication in monitoring railway sleepers makes it a key problem within the rail transportation domain. Current day condition monitoring applications involving wooden railway sleepers are mostly carried out through visual inspection and if necessary some impact acoustic examination is carried out. Decision making is largely based on intuition; moreover the process of manually inspecting sleepers is rather slow and expensive. Maintaining an even quality standard is another serious issue. In this article, a pattern recognition and classification approach is taken to automate such intuitive human skills for the development of more robust and reliable testing methods. Features were extracted from the impact acoustic emissions of wooden sleepers and were used for pattern classification. Time-frequency based feature extraction techniques such short-time Fourier transform and discrete wavelet transform yielded good results. Multi-layer perceptron, radial basis function neural networks and support vector machine classifiers have been tested and compared. Further classifier fusion was investigated by considering the output of single best classifiers as input to a new classifier with an aim of improving performance. Results obtained experimentally demonstrate a classification accuracy of around 84%.

  • 80.
    Yella, Siril
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Gupta, Naredra K.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Automating condition monitoring of wooden railway sleepers2007Ingår i: EngineerIT, ISSN 1991-5047, Vol. 2, nr 10Artikel i tidskrift (Övrigt vetenskapligt)
  • 81.
    Yella, Siril
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Gupta, Naren
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Condition monitoring using pattern recognition techniques on data from acoustic emissions2006Ingår i: ICMLA 2006: 4th International Conference on Machine Learning and Applications, Proceedings, 2006Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    Condition monitoring applications deploying the usage of impact acoustic techniques are mostly done intuitively by skilled personnel. In this article, a pattern recognition approach is taken to automate such intuitive human skills for the development of more robust and reliable testing methods. The focus of this work is to use the approach as a part of a major research project in the rail inspection area, within the domain of Intelligent Transport Systems. Data from impact acoustic tests made on wooden beams have been used. The relation between condition of the wooden beams and respective sounds they make when struck, has been analyzed experimentally. Features were extracted from the acoustic emissions of wooden beams and were used for pattern classification. Features such as magnitude of the signal, natural logarithm of the magnitude and Mel-frequency cepstral coefficients, yielded good results. The extracted feature vectors were used as input to various pattern classifiers for further pattern recognition task. The effect of using classifiers like Support vector machines and Multi-layer perceptron has been tested and compared. Results obtained experimentally, demonstrate that Support vector machines provide good detection rates for the classification of impact acoustic signals in the NDT domain.

  • 82.
    Yella, Siril
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Gupta, Narendra
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Comparison of pattern recognition techniques for the classification of impact acoustic emissions2007Ingår i: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 15, nr 6, s. 345-360Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Current day condition monitoring applications involving wood are mostly carried out through visual inspection and if necessary some impact acoustic examination is carried out. These inspections are mainly done intuitively by skilled personnel. In this paper, a pattern recognition approach has been considered to automate such intuitive human skills for the development of robust and reliable methods within the area. The study presents a comparison of several pattern recognition techniques combined with various stationary feature extraction techniques for classification of impact acoustic emissions. Further issues concerning feature fusion are discussed as well. It is hoped that this kind of broad analysis could be used to handle a wide spectrum of tasks within the area, and would provide a perfect ground for future research directions. A brief introduction to the techniques is provided for the benefit of the readers unfamiliar with the techniques. Pattern classifiers such as support vector machines, etc. are combined with stationary feature extraction techniques such as linear predictive cepstral coefficients, etc. Results from support vector machines in combination with linear predictive cepstral coefficients delivered good classification rates. However, Gaussian mixture models delivered higher classification rates when feature fusion is proposed.

  • 83.
    Yella, Siril
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Nyberg, Roger G
    Högskolan Dalarna, Akademin Industri och samhälle, Informatik.
    Gupta, Narendra K.
    Edinburgh Napier University.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Reliability of manual assessments in determining the types of vegetation on railway tracks2015Ingår i: Web Information Systems Engineering – WISE 2015: 16th International Conference, Miami, FL, USA, November 1-3, 2015, Proceedings, Part II / [ed] Wang, J., Cellary, W., Wang, D., Wang, H., Chen, S.-C., Li, T., Zhang, Y., Springer, 2015, Vol. 9149, s. 391-399Konferensbidrag (Refereegranskat)
    Abstract [en]

    Current day vegetation assessments within railway maintenance are (to a large extent) carried out manually. This study has investigated the reliability of such manual assessments by taking three non-domain experts into account. Thirty-five track images under different conditions were acquired for the purpose. For each image, the raters’ were asked to estimate the cover of woody plants, herbs and grass separately (in %) using methods such as aerial canopy cover, aerial foliar cover and sub-plot frequency. Visual estimates of raters’ were recorded and analysis-of-variance tests on the mean cover estimates were investigated to see whether if there were disagreements between the raters’.  In tra-correl ation coefficient was used to study the differences between the estimates. Results achieved in this work revealed that seven out of the nine analysis-of-variance tests conducted in this study have demonstrated significant difference in the mean estimates of cover (p < 0.05).

  • 84.
    Yella, Siril
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Nyberg, Roger G.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Payvar, Barsam
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Gupta, Narendra
    Edinburgh Napier University.
    Machine vision approach for automating vegetation detection on railway tracks2013Ingår i: Journal of Intelligent Systems, ISSN 2191-026X, Vol. 22, nr 2, s. 179-196Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The presence of vegetation on railway tracks (amongst other issues) threatens track safety and longevity. However, vegetation inspections in Sweden (and elsewhere in the world) are currently being carried out manually. Manually inspecting vegetation is very slow and time consuming. Maintaining an even quality standard is also very difficult. A machine vision-based approach is therefore proposed to emulate the visual abilities of the human inspector. Work aimed at detecting vegetation on railway tracks has been split into two main phases. The first phase is aimed at detecting vegetation on the tracks using appropriate image analysis techniques. The second phase is aimed at detecting the rails in the image to determine the cover of vegetation that is present between the rails as opposed to vegetation present outside the rails. Results achieved in the current work indicate that the machine vision approach has performed reasonably well in detecting the presence/absence of vegetation on railway tracks when compared with a human operator.

  • 85.
    Yella, Siril
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Pasha, Sajjad M.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Gupta, Narendra K.
    Classifier fusion for condition monitoring of wooden railway sleepers2008Ingår i: Engineer IT, ISSN 1991-5047, s. 31-35Artikel i tidskrift (Övrigt vetenskapligt)
  • 86.
    Yella, Siril
    et al.
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Shaik, Asif ur Rahman
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Dougherty, Mark
    Högskolan Dalarna, Akademin Industri och samhälle, Datateknik.
    Pattern recognition for classifying the condition of wooden railway sleepers2010Ingår i: Multimedia Computing and Information Technology (MCIT), 2010 International Conference on Multimedia Computing and Information Technology, Sharjah, 2010, s. 61-64Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper summarises the results of using a pattern recognition approach for classifying the condition of wooden railway sleepers. Railway sleeper inspections are currently done manually; visual inspection being the most common approach, with some deeper examination using an axe to judge the condition. Digital images of the sleepers were acquired to compensate for the human visual capabilities. Appropriate image analysis techniques were applied to further process the images and necessary features such as number of cracks, crack length etc have been extracted. Finally a pattern recognition and classification approach has been adopted to further classify the condition of the sleeper into classes (good or bad). A Support Vector Machine (SVM) using a Gaussian kernel has achieved good classification rate (86%) in the current case.

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