Let’s draw : detecting and measuring Parkinson’s disease on smartphones
Kuosmanen, Elina; Kan, Valerii; Visuri, Aku; Hosio, Simo; Ferreira, Denzil (2020-04-30)
Elina Kuosmanen, Valerii Kan, Aku Visuri, Simo Hosio, and Denzil Ferreira. 2020. Let’s Draw: Detecting and Measuring Parkinson’s Disease on Smartphones. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI ’20). Association for Computing Machinery, New York, NY, USA, 1–9. DOI:https://doi.org/10.1145/3313831.3376864
© 2020 Copyright held by the owner/author(s). Publication rights licensed to ACM. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, https://doi.org/10.1145/3313831.3376864.
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https://urn.fi/URN:NBN:fi-fe2020050725521
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Abstract
Spiral drawing has been utilized for years as a clinical tool to observe tremors and other abnormal movements in the assessment of different movement disorders. Specifically, in Parkinson’s Disease (PD), patients’ motor functionalities are measured by various tests, and spiral drawing is one of the proven techniques for assessing the severity of PD motor symptoms. Traditionally, this test is performed on pen and paper, and visually assessed by a clinician. There have been successful efforts for digitizing this test on tablets. Here, we describe a smartphone-based digitized version of the spiral drawing test. Moreover, we introduce a square-shaped drawing to solve an identified challenge of a smaller screen estate: finger occlusion while drawing. Both approaches are evaluated with 8 Parkinson’s Disease patients and 6 age-matching control participants. Based on earlier studies and our data, we select suitable motion parameters for quantifying the task. Our results show an observable, statistically difference in performance between users with Parkinson’s Disease and the control group in drawing accuracy.
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