Smart Sensing System for the Detection of Specific Human Motion Symptoms of the Parkinsonźs Disease

We propose two different wearable wireless sensing systems based on Inertial Measurement Units for the home monitoring of specific symptoms of the Parkinson’s disease. In one configuration just one sensor is inserted in a headset, in the other configuration two sensors are positioned on the patient’s shins. They recognize and classify noticeable motion disorders potentially dangerous for patients and give an audio feedback. The systems use dedicated algorithms for real time processing of the raw signals from accelerometers and gyroscopes, one of which is based on an artificial neural network and another on a time-based analysis. The headset system detects satisfactorily a wide class of motion irregularities including the trunk disorders, but is poorly reliable on Parkinson’s patients. The other system with sensors on the shins provides an early detection of the freezing of gait with excellent performance in terms of sensitivity and precision, and timely provides a rhythmic auditory stimulation to the patient for releasing the involuntary block state.