A Parkinson's disease (PD) sensor system, including multiple inertial sensors and a heart rate monitor, may be used to detect PD symptoms, including Freezing of Gait (FoG). The PD sensor system may include a wrist-mounted accelerometer and heart rate monitor, and additional inertial sensors at other parts of the patient's body. The FoG detection classifier is implemented as an on-device neural network that will analyze data collected from the inertial sensors and the patient's heart rate to detect FoG events, and simultaneously uses the data to update the FoG event detection specific to the patient's PD symptoms. This self-learning neural network enables a personalized and optimized solution specific to each patient's PD symptoms and disease progression. Once a FoG event is detected, the sensor system may notify a concerned party or may activate an emergency response request.
