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Updated: Sep 19, 2025

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
Published on: July 24, 2019
Wrist accelerometry and machine learning sensitively capture disease progression in prodromal Parkinson's disease
Anoopum S Gupta1, Siddharth Patel2
1Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. agupta@mgh.harvard.edu.
None:
Sensitive motor measures are needed to support trials in Parkinson's disease (PD). Wrist sensor data was collected continuously at home from 269 individuals with PD (106 with prodromal PD). Submovements were smaller, slower, and less variable in PD and prodromal PD. A machine-learned composite measure captured disease progression in prodromal PD more sensitively than the MDS-UPDRS Part III motor score. Wearable sensor-based measures may be useful in upcoming clinical trials.
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