In this study, a four-axis platform capable of rolling, pitch, and yaw rotation was created for rehabilitation and exercise. Based on this, a virtual coach and a virtual reality game system were developed. The virtual coach is a 3D person model created with the Unity program that allows the user to exercise in the correct posture with the virtual coach, and recognizes the correct posture with the Kinect. Additionally, a virtual reality game has been developed, and in conjunction with this, the actual platform also moves to increase the rehabilitation effect. The upper body and lower body movement and plantar pressure measurement were used to associate with the four-axis platform to maintain strength and balance the body.

In this paper, a prosthetic robot hand was designed and fabricated and experimental evaluation of the realization of basic gripping motions was performed. As a first step, a robot finger was designed with same structural configuration of the human hand and the movement of the finger was evaluated via kinematic analysis. Electromyogram (EMG) signals for hand motions were measured using commercial wearable EMG sensors and classification of hand motions was achieved by applying the artificial neural network (ANN) algorithm. After training and testing for three kinds of gripping motions via ANN, it was observed that high classification accuracy can be obtained. A prototype of the proposed robot hand is manufactured through 3D printing and servomotors are included for position control of fingers. It was demonstrated that effective realization of gripping motions of the proposed prosthetic robot hand can be achieved by using EMG measurement and machine learning-based classification under a real-time environment.