Deep Learning for hand tracking in Parkinson's Disease video-based assessment: Current and future perspectives

Gianluca Amprimo, Giulia Masi, Gabriella Olmo, Claudia Ferraris

Abstract: Highlights•Assessment of hand impairment is crucial for monitoring Parkinson’s disease over time.•Hand tracking methods based on Deep Learning enable objective video-based assessment.•This narrative review does an in-depth evaluation of the state-of-the-art since 2017.•OpenPose, DeepLabCut and MediaPipe result the most popular frameworks in this domain.•Larger datasets, technical validation, and multihand-interactions are often missing.