Robotic-Assisted Rehabilitation Trainer Improves Balance Function in Stroke Survivors

Abstract

Nerve injury after stroke leads to disorders of locomotion and a declining balance function, which increases the risk of falling. Restriction of pelvic motions can hinder successful rehabilitation, hence a robotic-assisted rehabilitation trainer (RART) is proposed to assist patients in controlling the pelvic motions via force field. The mechanical design, kinetic framework, and the intention-based controller of the RART are introduced in this paper. Based on an intention-based control strategy, the robot generates force field that affects the pelvic motions (vertical and lateral motion, rotation, and obliquity) via a compliant pelvic brace while the patient is walking on ground. A control experiment with 16 hemiplegic patients is carried out to examine the effects on recovery of the balance function. Clinical evaluations and gait analysis are performed before and after the treatment. The experimental results show that the proposed control method is effective in motion recognition, and significant improvements of the balance function, gait speed, stride, stride frequency, Fugl-Meyer assessment, peak knee, and hip flexion angle during swing phase for their affected side are observed in the comparisons within the RART group. These preliminary results demonstrate that the proposed robot with force field and visual feedback may be effective in improving the balance function.