As most electromyography prosthesis controller systems are based on a threshold to control hand’s opening and closing, with poor operational flexibility, it is proposed to use ARM in the system. A STM32 ARM core processor is used as the main chip. It collects the flxor carpi ulnaris and flexor carpi radialis electomyography signals with 2 A/D signal converters, and extractes 4 kinds of characteristic values both in the time and frequency domains. By using a BP neural network classification algorithm, the system realizes real-time online identification of 5 kinds of palm action modes. Experimental results show that the system’s online recognition rate for the 5 actions is up to 97%, meeting the real-time requirements of prosthetic hand control.
BU Feng, LI Chuan-jiang, CHEN Jia-jia, LI Huan, GUO Wei-hai
. Design of Electromyography Prosthesis Controller Based on ARM[J]. Journal of Shanghai University, 2014
, 20(4)
: 442
-449
.
DOI: 10.3969/j.issn.1007-2861.2014.01.042
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