.png){kind=icon}
.png){kind=icon}
Return
Parkinson's Disease detection through multimodal data analysis
.png){kind=icon}
PRE
AI
DOI：10.1016/j.smhl.2025.100618.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Parkinson's disease (PD) is a slowly progressive neurodegenerative disease which still lacks objective tools for diagnosis. According to recent research results, misdiagnosis of PD may reach up to 25%. In this article, we report on the medical decision support system based on wearable sensors and video cameras with consequent multimodal data analysis using Machine Learning (ML) methods. For data collection reasons 169 subjects performed eleven exercises recommended by the neurologists. The proposed smart system is assessed through ML metrics and outperform the state-of-the-art solutions by achieving precision 98.6%, recall 98.1%, and F1-micro 98.3%. This decision support system opens wide vista for its application in hospitals as well as at home settings for controlling the undergoing therapy.
Keywords:
Decision support
Deep learning
Machine learning
Parkinson's disease
Wearable sensing
Journal
S
IF:
0
Papers:
28
Citations:
0