Wearable stroke rehabilitation device gives patients the upper hand

AI Summary

Researchers at the University of Massachusetts Amherst developed a wearable wrist device that uses machine learning to track arm impairment after stroke. Continuous monitoring could help clinicians adjust rehabilitation therapy to each patient's progress in real time.

A team led by University of Massachusetts Amherst researchers has developed a wearable wrist device powered by a machine-learning algorithm that can continuously track changes in arm movement impairment after a stroke. Monitoring those changes throughout rehabilitation could allow clinicians to adjust therapy in real time, tailoring care instead of relying on the current one-size-fits-all approach.