%0 Journal Article
%T Digital Biomarker Identification for Parkinson¡¯s Disease Using a Game-Based Approach
%A Ilman Shazhaev
%A Dimitry Mihaylov
%A Abdulla Shafeeg
%J Journal of  Intelligent Learning Systems and Applications
%P 89-95
%@ 2150-8410
%D 2022
%I Scientific Research Publishing
%R 10.4236/jilsa.2022.144007
%X 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.
%K Machine Learning
%K Biomarker
%K Parkinson¡¯s Disease
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=121033