The development of sensor-based gait training system for locomotive syndrome: The effect of real-time gait feature feedback on gait pattern during treadmill walking

The concept of locomotive syndrome was proposed by the Japanese Orthopedic Association; it typifies the condition of reduced mobility resulting from a locomotive organ disorder related to aging. Although several sensor-based gait training systems, which can feedback the gait features in real-time, have been developed for various musculoskeletal disorders, there are no such systems for locomotive syndrome. In this study, we reported how real-time locomotive syndrome related gait feature feedback effects on gait patterns during treadmill walking. 18 healthy participants were assigned into either intervention- or control-group. During 4 sessions (training-session, pre-intervention-session, intervention-session, and post-intervention-session), gait patterns were measured by a motion-capture system. During the intervention-session of the intervention-group, participants received LS-risk-scores made in this study. Meanwhile, they were asked to minimize the LS-risk-scores by modifying their knee joint motion. A two-way-repeated measure ANOVA was conducted on the LS-risk-scores to examine effects of the intervention. When interaction was found, paired t-tests were conducted on the LS-risk-scores and knee angles between the sessions respectively. As a result, the LS-risk-scores were significantly smaller (p < 0.05) during the post-intervention-session than the pre-intervention-session in the intervention-group. There were no significant differences on the LS-risk-scores between the sessions in the control-group. Further, in the intervention-group, significant differences (p < 0.05) were found between the sessions on the knee angles partially. There were no significant differences between the sessions on the knee angles in the control-group. These results indicate that people can alter their gait pattern if the LS-risk-scores are feedback in real-time.