Stroke Rehabilitation based on Intelligence Interaction System

Abstract

Stroke rehabilitation is an important requirement of patient treatment after recovering from stroke disease. However, a physical therapist can only observe once a patient at a time. Moreover, it takes a lot of time to suggest and evaluate the correction. From this problem, this research will develop the new rehabilitation guidance systems that assist the physical therapist and medical doctor. The intelligence interaction system is proposed for detection and monitoring the rehabilitation of the stroke patient who stays on the bed. The proposed system detects a stroke patient by using a 3D camera, which is the Intel Realsense D415, to place at the end of the patient bed for extracting the patient from the bed by measuring the distance between the patient and bed. From the segmentation result of the patient, the proposed system evaluates the rehab posture of the patient by detection from the simulated skeleton to calculate from the changing degree of the shoulder joint, elbow joint, and wrist joint. In addition, the proposed system uses the capabilities of artificial intelligence to check the accuracy of physiotherapy patients and show to the patients how to perform physical therapy correctly. From the experiment results, the proposed system represents the effective monitoring and evaluation of the stroke rehabilitation that the program can accurately count the arm flexion gesture therapy. Therefore, the intelligence interaction system can usefully help the physical therapist to monitor and evaluate the rehabilitation of stroke on the bed. © 2020 IEEE.