Wearable Sensor Configurations for Effective Tremor Assessment in Parkinson's Disease

Smartwatches play an increasingly vital role in health monitoring, offering practical solutions for patients to manage their conditions in daily life. This is particularly significant for Parkinson's Disease (PD) patients, as tremors, a notable symptom, significantly impact their quality of life. Our research addresses unanswered questions about the optimal configurations for these devices, considering factors such as the placement of the smartwatch, the type of sensor used (accelerometer vs. gyroscope), and the sampling frequency. Employing a gradient tree-boosting approach, we analyze data from the wrist and ankle sensors of 24 PD subjects engaged in daily living activities. The findings highlight a cost-effective, practical, and resource-friendly configuration: utilizing accelerometer wrist data sampled at 32 Hz demonstrates a robust correlation between the estimations of total tremors (0.82) and rest tremors (0.84) compared to their clinical ground-truth values. This underlines the significant potential of employing smartwatches in a natural environment for clinicians to monitor their patients efficiently, minimizing the necessity for costly, inconvenient in-clinic assessments.