A sensor fusion approach for inertial sensors based 3D kinematics and pathological gait assessments: toward an adaptive control of stimulation in post-stroke subjects

Abstract

Pathological gait assessment and assistive control based on functional electrical stimulation (FES) in post-stroke individuals, brings out a common need to robustly quantify kinematics facing multiple constraints. This study proposes a novel approach using inertial sensors to compute dorsiflexion angles and spatio-temporal parameters, in order to be later used as inputs for online close-loop control of FES. 26 post-stroke subjects were asked to walk on a pressure mat equipped with inertial measurement units (IMU) and passive reflective markers. A total of 930 strides were individually analyzed and results between IMU-based algorithms and reference systems compared. Mean absolute (MA) errors of dorsiflexion angles were found to be less than 4°, while stride lengths were robustly segmented and estimated with a MA error less than 10 cm. These results open new doors to rehabilitation using adaptive FES closed-loop control strategies in "foot drop" syndrome correction.