In-socket sensory system with an adaptive neuro-based fuzzy inference system for active transfemoral prosthetic legs
An in-socket sensory system enables the monitoring of transfemoral amputee movement for a microprocessor-controlled prosthetic leg. User movement recognition from an in-socket sensor allows a powered prosthetic leg to actively mimic healthy ambulation, thereby reducing an amputee's metabolic en...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English English |
| Published: |
SPIE
2019
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/79692/ http://irep.iium.edu.my/79692/ http://irep.iium.edu.my/79692/ http://irep.iium.edu.my/79692/1/79692_In-socket%20sensory%20system_MYRA.pdf http://irep.iium.edu.my/79692/2/79692_In-socket%20sensory%20system_SCOPUS.pdf http://irep.iium.edu.my/79692/3/79692_In-socket%20sensory%20system_WOS.pdf |
| Summary: | An in-socket sensory system enables the monitoring of transfemoral amputee movement for a microprocessor-controlled prosthetic leg. User movement recognition from an in-socket sensor allows a powered prosthetic leg to actively mimic healthy ambulation, thereby reducing an amputee's metabolic energy consumption. This study established an adaptive neurofuzzy inference system (ANFIS)-based control input framework from an in-socket sensor signal for gait phase classification to derive user intention as read by in-socket sensor arrays. Particular gait phase recognition was mapped with the cadence and torque control output of a knee joint actuator. The control input framework was validated with 30 experimental gait samples of the in-socket sensory signal of a transfemoral amputee walking at fluctuating speeds of 0 to 2 km · h- 1. The physical simulation of the controller presented a realistic simulation of the actuated knee joint in terms of a knee mechanism with 95% to 99% accuracy of knee cadence and 80% to 90% accuracy of torque compared with those of normal gait. The ANFIS system successfully detected the seven gait phases based on the amputee's in-socket sensor signals and assigned accurate knee joint torque and cadence values as output. © 2018 SPIE and IS&T. |
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