Cloud-based gait analysis using a single IMU for parkinson disease

Abstract

Freezing of gait (FOG) is one of the most common disabling symptoms in Parkinson disease (PD), causing a high risk of falling and lost life quality. There is no curative treatment due to a lack of understanding of the pathophysiology. Early detection with a proper customized rehabilitation program can slow the disease's progression and extend their independent living. Furthermore, the objective and real-time monitoring of gait patterns is also important as it can be used to adjust treatment programs and follow up the clinical progress effectively. However, the assessment nowadays is typically depending on a subjective FOQ questionnaire. This paper proposes a low-cost wearable IMU sensor that integrates cloud computing technology to monitor and assess PD patients' gait. The device uses a single IMU sensor, which combines a 3-axis gyroscope and a 3-axis accelerometer, to record dynamic acceleration and perform gravity compensation. The preliminary results from 14 patients show that the proposed device can display freezing episodes and variability or decreased acceleration correlated with falling risk. Moreover, the proposed cloud platform can be applied to other telehealth services.