The Effect of IoT-based Upper and Lower Extremity Rehabilitation Medical Device Training on Gait in Chronic Stroke Survivor: A Case Study

Abstract

Purpose: For stroke survivors, abnormal gait patterns lead to a significant risk of falls. We have recently developed an IoT-based Upper and Lower Extremity Rehabilitation Medical Device (RoBoGat) that enables continuous passive motion (CPM) training, squat training (ST), and gait training (GT). The purpose of this study was to test the effectiveness of RoBoGat on gait in a chronic stroke survivor. Methods: In this study, an individual with right-side chronic hemiparesis post-stroke participated. The participant underwent 14 days of RoBoGat training that involved continuous passive motion training, squat training, and gait training. During the training, knee and hip joint angles were adjusted within the range where the subject felt no pain. We assessed gait, timed up and go test, and visual analog scale at baseline and after first and final interventions. Results: After the intervention, positive changes were observed such as stride, gait velocity, and loading phase. Improvements were also observed in timed up and go tests. However, there was no significant change in VAS, which assessed pain in training and daily life. Conclusion: The main finding of this case-control study is that robot-based upper and lower extremity training may be a feasible approach in the neurorehabilitation field. It can be concluded that repetitive and continuous robot rehabilitation exercises have a positive effect on improving the physical function of chronic stroke survivors.