In-socket sensory system with an adaptive neuro-based fuzzy inference system for active transfemoral prosthetic legs

Mohd Yusof, Nur Hidayah and Hamzaid, Nur Azah and Jasni, Farahiyah and Lai, Khin Wee (2018) In-socket sensory system with an adaptive neuro-based fuzzy inference system for active transfemoral prosthetic legs. Journal of Electronic Imaging, 28 (2). 021002. ISSN 1017-9909, DOI

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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.

Item Type: Article
Funders: University Malaya through Postgraduate Research Fund (PPP) Project No: PG125-2015B, Ministry of Higher Education through Fundamental Research Grant Scheme Grant Project No: FP047-2014B
Uncontrolled Keywords: adaptive neurofuzzy inference system; controller; in-socket sensory system; prosthetic knee joint; transfemoral leg
Subjects: R Medicine
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 10 Mar 2020 04:15
Last Modified: 10 Mar 2020 04:15

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