Machine learning leads to novel way to track tremor severity in Parkinson’s patients

Physical exams only provide a snapshot of a Parkinson’s patient’s daily tremor experience. Scientists have developed algorithms that, combined with wearable sensors, can continuously monitor patients at home or elsewhere to estimate the severity rating of their tremors based on the way that it manifests itself in movement patterns. This approach has the potential to provide clinicians with a full spectrum of their patients’ tremors and medication response to effectively manage and treat this disorder.