The wearable power-assisted robot is a typical auxiliary rehabilitation robot. It is an exoskeleton power-assisted device that helps people to expand their lower limb movement capabilities. Its basic principle is to obtain the motion intention information of the human body through the perception system. Control the DC servo motor installed at the hip joint and the knee joint to drive the movement of the link, so as to achieve the purpose of providing assistance to the human body. In order to improve the dynamic response frequency of the wearable robotic perception system, a sensor signal based on time series analysis is proposed. The online prediction algorithm, which can perform single-step or multistep prediction under the premise of ensuring certain accuracy, can multiply the dynamic response frequency of the wearable-assisted robot sensing system to ensure the real-time performance of the whole system. In order to realize the sensor signal prediction algorithm, we design the corresponding software and hardware system to realize the prediction algorithm. The whole sensor signal prediction algorithm implementation system can be divided into two parts: lower computer and upper computer. The lower computer includes amplification circuit, signal conditioning circuit, and acquisition. The signal processing software part of the circuit and the corresponding MCU and the upper computer mainly include the data acquisition and prediction algorithm implementation, and the upper computer adopts the mixed programming technology of Vc++ and MATLAB to complete the software part of the upper computer. Aiming at the control part of the wearable robotic sensing system, the first generation of DC servo motor embedded motion controller is designed. The motion controller adopts the design concept of embedded motion controller, which has small size, is light weight, and has good expandability. And the motion controller can communicate and debug with the host computer through the serial port, which lays a foundation for the design of the entire embedded control system.
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