Assessment of elbow rehabilitation using single dof robotic exoskeleton

Abstract

Stroke is a leading cause of permanent disability or inconvenient movements among adults worldwide. Due to strokes, the ability to make quality movements has been reduced. Researchers have introduced rehabilitation processes to restore the quality of movement and improve the quality of life of patients. To assist and evaluate stroke patients, robotic devices have been introduced. These devices can improve the effectiveness of the process and reduce time. This research proposes a robotic system that can perform stroke evaluation and support the rehabilitation process. This research is divided into three stages. In the first stage, the torque of the patient’s elbow joint was calculated using the kinematics of the system and the dynamic model of the arm. The torque estimation model has three main functions: inertia parameters were calculated using research, motor torque was computed using motor current, and kinematics data were captured using IMU (Inertia Motion Unit) sensors. In the second stage, muscle activation was calculated using an optimization algorithm. An optimization algorithm was developed using the musculoskeletal properties of the human arm and hill-type muscle models. Muscle activation based on the optimization algorithm is compared with EMG to identify the correlation of the data. In the third stage, a quantitative assessment of spasticity was performed using the Tonic Stretch Reflex Threshold (TSRT) estimation. Experiments were carried out in healthy subjects with voluntary participation. TSRT and biomechanical measurements are used to classify stroke patients. The estimated muscle activation was validated using captured EMG signal profiles.