Machine Learning based Real Time Detection of Freezing of Gait of Parkinson Patients Running on a Body Worn Device

For those who have Parkinson's disease, one of the most incapacitating symptoms is Freezing of Gait (FOG). Gait impairment and disruptions limit everyday activities and reduce quality of daily life along with the increase in the risk of falling [1]. Thanks to recent advancement in embedded electronics and sensors as well as their adaptation in the wearable device market, low power devices are becoming more and more capable running neural networks. This enables researchers to implement complex models on wearable devices that capture and analyze sensor data to detect FOGin real-time.