Neural networks : the official journal of the International Neural Network Society
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The human ankle varies impedance and delivers net positive work during the stance period of walking. In contrast, commercially available ankle-foot prostheses are passive during stance, causing many clinical problems for transtibial amputees, including non-symmetric gait patterns, higher gait metabolism, and poorer shock absorption. In this investigation, we develop and evaluate a myoelectric-driven, finite state controller for a powered ankle-foot prosthesis that modulates both impedance and power output during stance. ⋯ We find that the amputee can robustly transition between the finite state controllers through direct muscle activation, allowing rapid transitioning from level-ground to stair walking patterns. Additionally, we find that the proposed finite state controllers result in a more biomimetic ankle response, producing net propulsive work during level-ground walking and greater shock absorption during stair descent. The results of this study highlight the potential of prosthetic leg controllers that exploit neural signals to trigger terrain-appropriate, local prosthetic leg behaviors.