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A method for measuring Parkinson's disease related temporal irregularity in spiral drawings
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.
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0003-0403-338X
2016 (English)In: 2016 IEEE International Conference on Biomedical and Health Informatics, 2016, 410-413 p.Conference 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.

Place, publisher, year, edition, pages
2016. 410-413 p.
National Category
Computer Systems Signal Processing
Research subject
Complex Systems – Microdata Analysis, FLOAT - Flexible Levodopa Optimizing Assistive Technology
Identifiers
URN: urn:nbn:se:du-21183DOI: 10.1109/BHI.2016.7455921ISI: 000381398000102ISBN: 978-150902455-1OAI: oai:DiVA.org:du-21183DiVA: diva2:908008
Conference
Biomedical and Health Informatics 2016, Las Vegas, 24-27 February
Available from: 2016-03-01 Created: 2016-03-01 Last updated: 2016-10-13Bibliographically approved

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Publisher's full texthttp://emb.citengine.com/event/bhi-2016/paper-details?pdID=7687

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