Fuzzy Neural Network (FNN) Control for Restoration System of Wrist Joint Movement by Functional Electrical Stimulation (FES)

2023 International Seminar on Intelligent Technology and Its Applications (ISITIA)(2023)

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摘要
Stroke is the second leading cause of death and the third leading cause of disability around the world. WHO show that 70% of strokes and 87% of strokes that lead to death or disability happen in countries in the second and third world. Motor function is messed up after a stroke, which makes it hard to move joints. Hand moves, especially in the wrists, will get weaker. Functional Electrical Stimulation (FES) is a way to get joint function back to normal. A Fuzzy Neural Network is used to control the system. Based on the results of this study, it was found that 48V is the best voltage to use for the movement in this test. In the open loop test, a frequency of 15kHz and a 10% duty cycle are used to make this voltage. The average RMSE number for fast radial/ulnar flexion is 3.61, for slow radial/ulnar flexion it is 2.91, for fast dorsi/palmar flexion it is 5.22, and for slow dorsi/palmar flexion it is 4.36. So, the controller used can work better than the controller used in Fuzzy-PID tests done in the past.
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关键词
Stroke,Functional Electrical Stimulation (FES),Gyroscope,Accelerometer,Wrist,Fuzzy Neural Network
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