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Automatic and objective assessment of alternating tapping performance in Parkinson’s disease
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0002-2372-4226
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0002-2752-3712
Department of Neuroscience, Neurology, Uppsala University.
Department of Neuroscience, Neurology, Uppsala University.
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2013 (English)In: Sensors, E-ISSN 1424-8220, Vol. 13, no 12, p. 16965-16984Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
2013. Vol. 13, no 12, p. 16965-16984
Keywords [en]
alternating tapping, touch-pad, handheld computer, telemedicine, Parkinson’s disease, remote monitoring, automatic assessment, objective assessment, visual assessment
National Category
Computer Systems
Research subject
Research Profiles 2009-2020, Complex Systems – Microdata Analysis
Identifiers
URN: urn:nbn:se:du-13473DOI: 10.3390/s131216965ISI: 000330220600061Scopus ID: 2-s2.0-84890107007OAI: oai:DiVA.org:du-13473DiVA, id: diva2:677216
Note

Open Access

Available from: 2013-12-09 Created: 2013-12-09 Last updated: 2022-02-10Bibliographically approved
In thesis
1. Mobile systems for monitoring Parkinson's disease
Open this publication in new window or tab >>Mobile systems for monitoring Parkinson's disease
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

A challenge for the clinical management of Parkinson's disease (PD) is the large within- and between-patient variability in symptom profiles as well as the emergence of motor complications which represent a significant source of disability in patients. This thesis deals with the development and evaluation of methods and systems for supporting the management of PD by using repeated measures, consisting of subjective assessments of symptoms and objective assessments of motor function through fine motor tests (spirography and tapping), collected by means of a telemetry touch screen device.

One aim of the thesis was to develop methods for objective quantification and analysis of the severity of motor impairments being represented in spiral drawings and tapping results. This was accomplished by first quantifying the digitized movement data with time series analysis and then using them in data-driven modelling for automating the process of assessment of symptom severity. The objective measures were then analysed with respect to subjective assessments of motor conditions. Another aim was to develop a method for providing comparable information content as clinical rating scales by combining subjective and objective measures into composite scores, using time series analysis and data-driven methods. The scores represent six symptom dimensions and an overall test score for reflecting the global health condition of the patient. In addition, the thesis presents the development of a web-based system for providing a visual representation of symptoms over time allowing clinicians to remotely monitor the symptom profiles of their patients. The quality of the methods was assessed by reporting different metrics of validity, reliability and sensitivity to treatment interventions and natural PD progression over time.

Results from two studies demonstrated that the methods developed for the fine motor tests had good metrics indicating that they are appropriate to quantitatively and objectively assess the severity of motor impairments of PD patients. The fine motor tests captured different symptoms; spiral drawing impairment and tapping accuracy related to dyskinesias (involuntary movements) whereas tapping speed related to bradykinesia (slowness of movements). A longitudinal data analysis indicated that the six symptom dimensions and the overall test score contained important elements of information of the clinical scales and can be used to measure effects of PD treatment interventions and disease progression. A usability evaluation of the web-based system showed that the information presented in the system was comparable to qualitative clinical observations and the system was recognized as a tool that will assist in the management of patients.

Place, publisher, year, edition, pages
Örebro: Örebro University, 2014. p. 87
Series
Örebro Studies in Technology, ISSN 1650-8580 ; 57
Keywords
automatic assessments, data visualization, data-driven modelling, home assessments, information technology, mobile computing, objective measures, Parkinson’s disease, quantitative assessments, remote monitoring, spirography, symptom severity, tapping tests, telemedicine, telemetry, time series analysis, web technology.
National Category
Computer Systems
Research subject
Research Profiles 2009-2020, Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-13797 (URN)978-91-7668-988-2 (ISBN)
Public defence
2014-02-14, Clas Ohlsonsalen, Tenoren, Skomakargatan 1, Borlänge, 13:00 (English)
Opponent
Supervisors
Available from: 2014-02-13 Created: 2014-02-12 Last updated: 2021-11-12Bibliographically approved

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Memedi, MevludinKhan, TahaWestin, Jerker

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