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Abstract
This study investigates the use of combined voice and facial expression analysis for early Parkinson's disease (PD) detection. Using a smartphone-based system, 371 participants (186 PD patients, 185 controls) underwent simultaneous voice and facial recordings while reading. Nine machine learning classifiers were applied. Integrated features achieved an AUROC of 0.85 in the training cohort and 0.90 in the validation cohort, suggesting that this approach could aid in early PD identification.
Publisher
npj Parkinson’s Disease
Published On
Oct 29, 2022
Authors
Wee Shin Lim, Shu-I Chiu, Meng-Ciao Wu, Shu-Fen Tsai, Pu-He Wang, Kun-Pei Lin, Yung-Ming Chen, Pei-Ling Peng, Yung-Yaw Chen, Jyh-Shing Roger Jang, Chin-Hsien Lin
Tags
Parkinson's disease
voice analysis
facial expression
early detection
machine learning

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