Haptic feedback system for postural adaptation during robotic rehabilitation of upper limb

Abstract

Although trunk compensation during stroke rehabilitation is widely studied, the proposed solutions primarily include a trunk constraint, which has several disadvantages. In this study, we have proposed a haptic feedback-based system for postural training during upper-limb motor rehabilitation. We have tested the proposed system on six healthy people in this preliminary study. Participants performed a simple 1-dimensional reaching task while their posture was being monitored. They received haptic feedback based on their trunk posture. Preliminary results revealed a significant decline in postural error (p<0.05) after the haptic-based training. The reduction in error was maintained even after haptic feedback was turned off. This study shows that haptic feedback could be a viable alternative to the traditional constraint-based methods for postural adaptation. Additional studies need to be conducted to further evaluate the influence of using such feedback strategies.