Abstract
Powered ankle-foot prostheses assist users through plantarflexion during stance and dorsiflexion during swing. Provision of motor power permits faster preferred walking speeds than passive devices, but use of active motor power raises the issue of control. While several commercially available algorithms provide torque control for many intended activities and variations of terrain, control approaches typically exhibit no inherent adaptation. In contrast, muscles adapt instantaneously to changes in load without sensory feedback due to the intrinsic property that their stiffness changes with length and velocity. We previously developed a “winding filament” hypothesis (WFH) for muscle contraction that accounts for intrinsic muscle properties by incorporating the giant titin protein. The goals of this study were to develop a WFH-based control algorithm for a powered prosthesis and to test its robustness during level walking and stair ascent in a case study of two subjects with 4–5 years of experience using a powered prosthesis. In the WFH algorithm, ankle moments produced by virtual muscles are calculated based on muscle length and activation. Net ankle moment determines the current applied to the motor. Using this algorithm implemented in a BiOM T2 prosthesis, we tested subjects during level walking and stair ascent. During level walking at variable speeds, the WFH algorithm produced plantarflexion angles (range = −8 to −19°) and ankle moments (range = 1 to 1.5 Nm/kg) similar to those produced by the BiOM T2 stock controller and to people with no amputation. During stair ascent, the WFH algorithm produced plantarflexion angles (range −15 to −19°) that were similar to persons with no amputation and were ~5 times larger on average at 80 steps/min than those produced by the stock controller. This case study provides proof-of-concept that, by emulating muscle properties, the WFH algorithm provides robust, adaptive control of level walking at variable speed and stair ascent with minimal sensing and no change in parameters.
Highlights
The development of prostheses is expanding rapidly, resulting in a new generation of robotic devices that behave like the limbs they are designed to replace (Aaron et al, 2006; LeMoyne, 2016)
The goals of the present study were to develop a control algorithm based on the winding filament hypothesis (WFH), to implement the algorithm using the powered BiOM T2 foot-ankle prosthesis as a platform, and to test its robustness by comparing performance during level walking at variable speed and stair ascent
We describe the methods used to compare the performance of the winding filament” hypothesis (WFH) and BiOM stock controllers during level walking and stair ascent, and lastly we describe methods for statistical analysis of data
Summary
The development of prostheses is expanding rapidly, resulting in a new generation of robotic devices that behave like the limbs they are designed to replace (Aaron et al, 2006; LeMoyne, 2016). Despite the demonstrable success of the new technologies, significant challenges remain. State-ofthe-art powered prostheses are limited in terms of their speed and adaptability. Adaptation to changing conditions or variation in terrain remains a significant issue (Farrell and Herr, 2011; Sinitski et al, 2012; Tkach and Hargrove, 2013; Kannape and Herr, 2014). Advances in prosthesis development have been driven largely by technology (e.g., light-weight materials, long-life batteries, programmable electronics, and wireless communication), rather than by advances in understanding of the biological principles underlying human movement
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