Parkinson’s Predicted From Smartwatch Data

Scientists at Cardiff University have discovered a way to accurately predict the occurrence of Parkinson’s disease years before clinical symptoms show up by analyzing motion data available from common smartwatches. They showed that a type of machine learning trained on wrist-worn accelerometer data was able to accurately determine Parkinson’s risk up to 7 years prior to clinical diagnosis.

Parkinson’s disease affects more than 10 million people worldwide. The disease is characterized by a sharp loss of dopamine-producing neurons in the substantia nigra, a structure in the lower brain….