In-socket sensory system with an adaptive neuro-based fuzzy inference system for active transfemoral prosthetic legs
Document Type
Article
Publication Date
1-1-2018
Abstract
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.
Keywords
adaptive neurofuzzy inference system, controller, in-socket sensory system, prosthetic knee joint, transfemoral leg
Divisions
fac_eng
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
Publication Title
Journal of Electronic Imaging
Volume
28
Issue
2
Publisher
Society of Photo-optical Instrumentation Engineers