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A new computer method for assessing drawing impairment in Parkinson's disease
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0003-0403-338X
Dalarna University, School of Technology and Business Studies, Computer Engineering.
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0002-2372-4226
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2010 (English)In: Journal of Neuroscience Methods, ISSN 0165-0270, E-ISSN 1872-678X, Vol. 190, no 1, p. 143-148Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
2010. Vol. 190, no 1, p. 143-148
National Category
Health Sciences
Research subject
Complex Systems – Microdata Analysis, E-MOTIONS, Beslutsstöd för Parkinsonbehandling
Identifiers
URN: urn:nbn:se:du-10481DOI: 10.1016/j.jneumeth.2010.04.027ISI: 000279888800019Scopus ID: 2-s2.0-77953725166OAI: oai:DiVA.org:du-10481DiVA, id: diva2:542770
Available from: 2012-08-03 Created: 2012-08-03 Last updated: 2021-11-12Bibliographically 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
Complex Systems – Microdata Analysis, PAULINA - Uppföljning av Parkinsonsymptom från hemmet
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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Westin, JerkerMemedi, Mevludin

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