Inertial-based gait analysis applied to patients with Parkinson disease

People with Parkinson’s disease have a high incidence of falls due to motor difficulties. Recent studies have shown that PD patients can receive benefit from motor therapy based on cueing and feedback. This study describes a system based on a foot-mounted IMU for the calculation of gait parameters applied to different datasets of healthy elderly people, geriatric patients and patients with PD, in order to integrate it into a real-time acquisition system with application for tactile cueing. This system is divided into different steps: the identification of gait cycles and their events, the estimation of the path of the foot, which includes the estimation of the orientation of the foot, the application of methods to correct the error derived from the double integration of acceleration such as ZUPT, and finally the estimation of the different gait metrics. The results show that the algorithm developed is an accurate method for stride segmentation and is considered adequate to assess the gait metrics for gait evaluation of patients with motor difficulties.