Upper limb rehabilitation system based on biological signals

Abstract

The invention discloses an upper limb rehabilitation system based on biological signals. The upper limb rehabilitation system based on the biological signals is characterized in that a brain electric cap is attached to the surface of a brain, brain electric signals can be sensed through the brain electric cap, features of the brain electric signals are extracted and classified sequentially through a CSP feature extraction algorithm and a classifier with an adaptive LDA classification algorithm after amplification, filtering and noise reduction are performed on the brain electric signals, and then the brain electric signals are translated into drive instructions used to control drive motor equipment and pneumatic tendon auxiliary equipment, a system central processing unit fuses and sorts the drive instructions and motion state data collected by a motion state collector, and then feeds the drive instructions and the motion state data, which are fused and sorted, back to the drive motor equipment, the pneumatic tendon auxiliary equipment and a mobile terminal, and therefore a mechanical arm is driven to perform rehabilitation exercise. Work personnel remotely monitor motion and rehabilitation states of patients through the mobile terminal, and the patients also can invoke rehabilitation games in a display platform through a voice input and output device so as to perform auxiliary rehabilitation training. Accordingly, the upper limb rehabilitation system based on the biological signals improves training effectiveness of the patients, and simultaneously guarantees safety and stability in the training.

Description

technical field [0001] The invention belongs to the technical field of computer intelligent control, and more specifically relates to an upper limb rehabilitation system based on biological signals. Background technique [0002] In modern society, upper limb movement disorders caused by stroke, hemiplegia and other brain diseases have brought many difficulties to the lives of many middle-aged and elderly people. They need scientific rehabilitation training to help them restore limb motor function. In this context, the upper limb rehabilitation system based on biosignals has attracted people's attention as an effective device for upper limb rehabilitation training. [0003] There are about 100 billion nerve cells in the human brain, of which there are 14 billion cells in the cerebral cortex, and each nerve cell has 10,000 neural connections at the same time, forming an extremely complex and huge network of nerve cells. Nerve cells are mainly composed of three parts: dendrite...

AI Technical Summary

Problems solved by technology

[0007] 2), the EEG signal is non-linear

[0008] Since the human brain is a nonlinear system with complex structure and functions, the EEG signals generated by it also have nonlinear characteristics, which is very inconvenient for us to analyze and process. The traditional signal processing methods based on linear systems are basically no longer applicable. for processing EEG signals

[0009] 3) The magnitude of the EEG signal is very weak

[0016] However, the traditional rehabilitation system often cannot complete the rehabilitation training independently by the patient, and in the process of rehabilitation exercise, the exercise status cannot be visually displayed and remotely monitored, and the feedback of the patient's movement cannot be fed back to the rehabilitation system in real time to realize the fine-tuning of the rehabilitation system Secondly, the operation process of most of the existing rehabilitation exercise equipment is often boring, which is easy to make the patient feel restless, and is susceptible to power frequency interference from other electronic components on the rehabilitation system, making the collection of EEG signals inaccurate and difficult to perform. effective rehabilitation

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