Measuring Parkinson’s disease motor symptoms with smartphone-based drawing tasks |
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Author: | Kuosmanen, Elina1; Kan, Valerii1; Visuri, Aku1; |
Organizations: |
1Center for Ubiquitous Computing, University of Oulu Oulu, Finland |
Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 1.4 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2019100932060 |
Language: | English |
Published: |
Association for Computing Machinery,
2019
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Publish Date: | 2019-10-09 |
Description: |
AbstractIn Parkinson’s disease (PD), patients’ motor functionalities are measured by various tests. Spiral drawing is one of the proven techniques for assessing the severity of PD motor symptoms. Commonly the test is performed with pen and paper, with the following visual observation by a clinician. This paper describes the implementation of the digitized version of the spiral drawing test for Android devices. Moreover, the application extends the spiral test and utilizes square-shape drawing accordingly. This artifact was tested in a trial with 8 PD patients and 6 age matching controls. The results have shown the observable difference in performance between PD and non-PD users in drawing accuracy and speed. see all
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ISBN: | 978-1-4503-6869-8 |
Pages: | 1182 - 1185 |
DOI: | 10.1145/3341162.3344833 |
OADOI: | https://oadoi.org/10.1145/3341162.3344833 |
Host publication: |
Proceeding UbiComp/ISWC '19 Adjunct Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers |
Conference: |
ACM International Joint Conference on Pervasive and Ubiquitous Computing and the ACM International Symposium |
Type of Publication: |
A4 Article in conference proceedings |
Field of Science: |
113 Computer and information sciences |
Subjects: | |
Funding: |
This work is partially funded by the Academy of Finland (Grants 313224-STOP, 316253-SENSATE, 320089-SENSATE and 318927-6Genesis Flagship), and a personal research grant awarded by the Finnish Parkinson Foundation. |
Academy of Finland Grant Number: |
313224 316253 320089 318927 |
Detailed Information: |
313224 (Academy of Finland Funding decision) 316253 (Academy of Finland Funding decision) 320089 (Academy of Finland Funding decision) 318927 (Academy of Finland Funding decision) |
Copyright information: |
© 2019 Association for Computing Machinery. 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 Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers (UbiComp/ISWC '19 Adjunct), https://doi.org/10.1145/3341162.3344833. |