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
Let’s draw : detecting and measuring Parkinson’s disease on smartphones
|Author:||Kuosmanen, Elina1; Kan, Valerii1; Visuri, Aku1;|
1Center for Ubiquitous Computing, University of Oulu, Oulu, Finland
|Online Access:||PDF Full Text (PDF, 1.5 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2020050725521
Association for Computing Machinery,
|Publish Date:|| 2020-05-07
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.
CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
ACM SigChi Annual Conference on Human Factors in Computing Systems
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
113 Computer and information sciences
This work is partially funded by the Academy of Finland (Grants 313224-STOP, 316253-SENSATE, 320089-SENSATE and 318927-6Genesis Flagship), and personal research grants awarded by the Finnish Parkinson Foundation, Tauno Tönning Foundation, Jenny and Antti Wihuri Foundation and Nokia Foundation.
|Academy of Finland Grant Number:||
313224 (Academy of Finland Funding decision)
316253 (Academy of Finland Funding decision)
320089 (Academy of Finland Funding decision)
318927 (Academy of Finland Funding decision)
© 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.