Upper limb wearable transfer robot motion recognition system based on multi-signal fusion

Abstract

The invention relates to the technical field of intention recognition, and provides an upper limb wearable transfer robot motion recognition system based on multi-signal fusion. The upper limb wearable transfer robot motion recognition system comprises a sensor system and a data processing system. The sensor system comprises a surface dry electrode myoelectricity sensor, a six-axis inertial sensorand a silica gel air bag connected with an air pressure sensor. The data processing system is an upper computer integrating a human body physiological information calculation module, an electromyographic signal characteristic value calculation module, an upper limb joint angle calculation module, a four-stage processing module and an impedance regulator. The four-stage processing module comprisesa neural network module, a principal component analysis module, a moving average filtering module and an If-Then decision maker module. The output end of the sensor system is electrically connected with the input end of the data processing system, and the output end of the data processing system is electrically connected with the input end of a robot controller. According to the invention, the individual difference problem of physiological signals can be solved, and the accuracy of intention recognition and the effectiveness and safety of man-machine interaction are improved.

Description

technical field [0001] The invention relates to the technical field of intention recognition, in particular to a motion recognition system for a wearable upper limb carrying robot based on multi-signal fusion. Background technique [0002] Surface electromyography (sEMG) is a one-dimensional time series obtained by guiding, amplifying, recording and displaying biological point changes of the neuromuscular system on the skin surface. The sEMG signal obtained after acquisition contains the superposition of multiple motor unit point activities in time and space, so it can characterize the activity of related muscles, so it is usually used as a control signal for exoskeleton robots, prosthetics and powered orthotics, for example, by amplifying a The myoelectric signals of a group of antagonistic muscles control the flexion and extension of the elbow joint of a single-joint exoskeleton robot; another example is by interpreting the long head of the biceps, the middle head of the t...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the problems existing in the prior art, the present invention provides a motion recognition system based on multi-signal fusion for wearable upper limb handling robots, which can solve the problem of individual differences in physiological signals such as sEGM, improve the accuracy of intent recognition and human-computer interaction effectiveness and safety of

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