## 5 Experimental Setup and Results  
The wearable upper limb rehabilitation robot designed in this paper adopts the upper computer-controlled robot to carry out continuous passive rehabilitation training for the affected limb, and adopts two rehabilitation training methods: independent movement of single joint and combined functional movement of multiple joints. The block diagram of the overall control system is shown in Figure 12. The lower computer of the control circuit takes the motion control card and data acquisition card as the core. The information acquisition card is used to complete data collection of 3D gyroscope, motion acceleration and other sensors. The upper computer can select the rehabilitation training mode and set the motion parameters of each joint, and then transmit the related parameters to the motion control card. The data collected by each functional sensor will be transmitted to the data acquisition card. After calculation, the data acquisition card converts the collected data into motion parameters, and then passes the motion control card to the motor rotation information, which is output to each motor driver respectively. Figure 12: Block diagram of rehabilitation robot control system. To realize the precise control of wearable upper limb rehabilitation robots, and reduce the motor torque error between the actual output torque and the theory, and let patients achieve the best effect of rehabilitation, the torque demand larger shoulder joint is designed in this paper. In addition, the drive motor of bending/stretching exercise and elbow flexion/stretch exercise drive motor installed on the dynamic torque sensor based on the basis of the Section 4 results, that is to say, wearable upper limbs rehabilitation robot dynamics analysis results of output torque. The dynamic torque sensor transmits the information to the computer through the data acquisition card. The difference between the theoretical torque and the measured torque is input into the PID controller and then the torque of the motor is adjusted in real time to achieve the optimal control. When designing a control system, it is essential to ensure the stability of the system and the safety of patients. Some control methods and neural network technique have been paid more attention to designing controller for a nonlinear system [40; 41]. In order to prevent excessive output torque of the motor from causing secondary damage to the affected limb, a current detection circuit is adopted to feed the output current of the driver into the motion control card in real time. Once the detected current exceeds the allowable value, the motor will stop immediately. At the same time, the one-key emergency stop function is set so that the system can be stopped immediately when the patient is uncomfortable. Furthermore, gyroscope and linear velocity sensor are used to detect the real-time position, real-time speed and real-time acceleration of the motor, so as to avoid the adverse effect caused by excessive joint rotation and excessive speed on the rehabilitation training. Figure 13 depicts the completed wearable upper limb rehabilitation robot prototype system and rehabilitation training. In the experiment, the time of each degree of freedom of the wearable upper limb rehabilitation robot was set to 25 s, and the range of motion was from the initial position to the extreme position. The test sampling period was 1 s. The experimental results are shown in Figure 14. Specifically, the experiment curves of horizontal, vertical, rotation, and elbow flexion and extension of the upper limb are plotted respectively. The solid red line in the figure is the simulation result, and the blue dotted line is the test result. It can be observed, the actual angle and simulation angle of each joint of the wearable upper limb rehabilitation robot during the movement have certain deviations.