Using wearable sensors and machine learning to measure upper limb function in Huntington's disease

We are excited to announce the publication of our paper, which establishes the initial clinical validity of using wearable sensors and machine learning to measure upper limb function in Huntington's disease (HD).

Published yesterday in Communications Medicine, our study explores how HD impacts hand movements during daily activities, including in the prodromal stage. Our findings demonstrate that the PAMSys ULM sensor can effectively differentiate individuals with HD from those at risk, and healthy controls. We also presented machine learning-based models to predict disease severity and clinical scores. This research underscores the potential of wearable technology for monitoring HD progression and evaluating treatment effects in clinical trials. Read the full article by clicking here.