Quantitative Analysis of Abnormal and Normal Gait based on Inertial Sensors

Abstract

Quantitative gait research is an effective auxiliary means to provide effective clinic diagnosis and surgery guidance for patients mobility. The traditional gait analysis carried out in the laboratory cannot be easily applied into the clinical medicine due to its complexity and high operating costs. To overcome this limitation, inertial sensors fixed on the ankle could perform out-of-lab measurements on subjects walking patterns. In this paper, a low-cost and intelligent wearable gait analysis system based on the inertial sensors is proposed, which can measure spatiotemporal gait parameters and help clinicians with diagnosis. The paper solves sensor drift problem by gradient descent method and zero velocity update algorithm. Using the gait analysis system, we conducted the contrast test of the gait parameters between the patients with abnormal gait and normal person. By contrasting two group of volunteers, it could be found that there is a significant difference about most spatiotemporal gait parameters. These results also indicate that our gait analysis system has potential to be used for out-of-lab gait analysis and can effectively detect the gait disorders and provide the reference for clinicians.