Shazhaev, Ilman and Mihaylov, Dimitry and Shafeeg, Abdulla (2022) Digital Biomarker Identification for Parkinson’s Disease Using a Game-Based Approach. Journal of Intelligent Learning Systems and Applications, 14 (04). pp. 89-95. ISSN 2150-8402
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Abstract
Despite the fact that their neurobiological processes and clinical criteria are well-established, early identification remains a significant hurdle to effective, disease-modifying therapy and prolonged life quality. Gaming on computers, gaming consoles, and mobile devices has become a popular pastime and provides valuable data from several sources. High-resolution data generated when users play commercial digital games includes information on play frequency as well as performance data that reflects low-level cognitive and motor processes. In this paper, we review some methods present in the literature that is used for identification of digital biomarkers for Parkinson’s disease. We also present a machine learning method for early identification of problematic digital biomarkers for Parkinson’s disease based on tapping activity from Farcana-Mini players. However, more data is required to reach a complete evaluation of this method. This data is being collected, with their consent, from players who play Farcana-Mini. Data analysis and a full assessment of this method will be presented in future work.
Item Type: | Article |
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Subjects: | Science Global Plos > Engineering |
Depositing User: | Unnamed user with email support@science.globalplos.com |
Date Deposited: | 28 Jan 2023 09:49 |
Last Modified: | 30 Dec 2023 13:32 |
URI: | http://ebooks.manu2sent.com/id/eprint/77 |