基于模糊逻辑算法的智能膝关节假肢步态相位识别

doi:10.3969/j.issn.1006-9771.2023.08.005

Abstract

Abstract:

Objective Aiming at the need of control strategy switching of intelligent above-knee prosthetic, taking the plantar pressure of human walking as the research object, and based on fuzzy logic algorithm, a gait phase division method based on plantar pressure of prosthetic is proposed.
Methods Three flexible force sensors installed on the soles of the false feet were used to collect the plantar pressure information of the test object under three different walking modes (walking on the flat road, walking downhill and walking down the stairs). After data fusion processing, it was sent to the fuzzy logic controller, and the recognition results were output according to the IF-THEN rule, the scale and sensitivity factor.
Results Through the testing of five healthy people as substitute, the results showed that the accuracy of gait phase recognition for walking on the flat road, walking down the stairs and walking downhill were (95.3±2.4)%, (81.5±6.3)% and (90.7±3.5)%, respectively.
Conclusion The accuracy of recognition basically meets the requirements in this project. This method can be applied in the gait phase recognition of intelligent above-knee prosthetic.

Key words: above-knee prostheses, gait detection, ground reaction force, fuzzy logic, gait phase

CLC Number:

R496

ZHANG Yibin, LÜ Jie, YU Hongliu. Gait phase recognition in intelligent above-knee prosthesis based on fuzzy logic algorithm[J]. 《Chinese Journal of Rehabilitation Theory and Practice》, 2023, 29(8): 896-902.

Figures/Tables 10

References 16

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步态相位	FSR₁	FSR₂	FSR₃
HS	weak	weak	strong
MS	strong	strong	strong
PSw	strong	strong	weak
Sw	weak	weak	weak

编号	性别	年龄/岁	身高/m	体质量/kg	大腿长/m	小腿长/m	步幅/m
1	男	53	1.70	70	0.42	0.48	0.63
2	男	43	1.65	61	0.40	0.47	0.61
3	男	29	1.78	75	0.44	0.51	0.66
4	女	41	1.52	55	0.37	0.43	0.56
5	女	55	1.60	57	0.39	0.46	0.59
平均		44.2±10.45	1.65±0.10	63.6±8.59	0.404±0.03	0.47±0.03	0.61±0.04

Gait phase recognition in intelligent above-knee prosthesis based on fuzzy logic algorithm

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