Speed adaptation in a powered transtibial prosthesis controlled with a neuromuscular model

Biomechatronics Group, Massachusetts Institute of Technology, 75 Amherst Street, Cambridge, MA 02139, USA.
Philosophical Transactions of The Royal Society B Biological Sciences (Impact Factor: 7.06). 05/2011; 366(1570):1621-31. DOI: 10.1098/rstb.2010.0347
Source: PubMed


Control schemes for powered ankle-foot prostheses would benefit greatly from a means to make them inherently adaptive to different walking speeds. Towards this goal, one may attempt to emulate the intact human ankle, as it is capable of seamless adaptation. Human locomotion is governed by the interplay among legged dynamics, morphology and neural control including spinal reflexes. It has been suggested that reflexes contribute to the changes in ankle joint dynamics that correspond to walking at different speeds. Here, we use a data-driven muscle-tendon model that produces estimates of the activation, force, length and velocity of the major muscles spanning the ankle to derive local feedback loops that may be critical in the control of those muscles during walking. This purely reflexive approach ignores sources of non-reflexive neural drive and does not necessarily reflect the biological control scheme, yet can still closely reproduce the muscle dynamics estimated from biological data. The resulting neuromuscular model was applied to control a powered ankle-foot prosthesis and tested by an amputee walking at three speeds. The controller produced speed-adaptive behaviour; net ankle work increased with walking speed, highlighting the benefits of applying neuromuscular principles in the control of adaptive prosthetic limbs.

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Available from: Ken Endo, Mar 15, 2014
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    • "Thanks to the use of battery-operated servomotors, powered prostheses allow positive net-energy tasks, such as step-overstep stair ambulation [1] and sit-to-stand transitions [2], while restoring more natural walking kinetics and kinematics compared to passive prostheses [3]. In stance phase, prosthesis torque can be regulated to obtain physiological body support and propulsion, [4] possibly reducing the metabolic cost of walking [5]. In swing phase, a biologically accurate movement can be generated to allow the timely placement of the foot in preparation for subsequent heel strike without requiring any additional effort from the user [6]. "
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    ABSTRACT: We present a novel swing phase controller for powered transfemoral prostheses based on minimum jerk theory. The proposed controller allows physiologically appropriate swing movement at any walking speed, regardless of the stance controller action. Preliminary validation in a transfemoral amputee subject demonstrates that the proposed controller provides physiological swing timing, without speed-or patient-specific tuning.
    36th Annual International IEEE EMBS Conference; 08/2014
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    • "Intrinsic controllers for lower-limb prostheses use finite state machines whose transitions are triggered based on onboard sensor data. Such controllers have recently been shown to generate biomimetic and speed-adaptive behavior during over-ground walking [1] [2] but are incapable of transitioning between different terrains or perform adequately during stair ambulation. This severely limits the mobility of lower extremity amputees and has a substantial impact on their quality of life and social independence [3] [4]. "
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    ABSTRACT: Although great advances have been made in the design and control of lower extremity prostheses, walking on different terrains, such as ramps or stairs, and transitioning between these terrains remains a major challenge for the field. In order to generalize biomimetic behaviour of active lower-limb prostheses top-down volitional control is required but has until recently been deemed unfeasible due to the difficulties involved in acquiring an adequate electromyographic (EMG) signal. In this study, we hypothesize that a transtibial amputee can extend the functionality of a hybrid controller, designed for level ground walking, to stair ascent and descent by volitionally modulating powered plantar-flexion of the prosthesis. We here present data illustrating that the participant is able to reproduce ankle push-off behaviour of the intrinsic controller during stair ascent as well as prevent inadvertent push-off during stair descent. Our findings suggest that EMG signal from the residual limb muscles can be used to transition between level-ground walking and stair ascent/descent within a single step and significantly improve prosthesis performance during stair-ambulation.
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    • "Therefore, it is the combined effects of both CPGs and feedbacks that changes the gait properties (such as speed, step length, step duration). It has already been demonstrated that feedbacks acting at the level of the ankle produce such speed-adaptive behaviors (Markowitz et al., 2011). Here we show that this is true regardless of whether the control is applied at the level of proximal or distal muscles. "
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    ABSTRACT: Although the concept of central pattern generators (CPGs) controlling locomotion in vertebrates is widely accepted, the presence of specialized CPGs in human locomotion is still a matter of debate. An interesting numerical model developed in the 90s' demonstrated the important role CPGs could play in human locomotion, both in terms of stability against perturbations, and in terms of speed control. Recently, a reflex-based neuro-musculo-skeletal model has been proposed, showing a level of stability to perturbations similar to the previous model, without any CPG components. Although exhibiting striking similarities with human gaits, the lack of CPG makes the control of speed/step length in the model difficult. In this paper, we hypothesize that a CPG component will offer a meaningful way of controlling the locomotion speed. After introducing the CPG component in the reflex model, and taking advantage of the resulting properties, a simple model for gait modulation is presented. The results highlight the advantages of a CPG as feedforward component in terms of gait modulation.
    Frontiers in Human Neuroscience 06/2014; 8:371. DOI:10.3389/fnhum.2014.00371 · 3.63 Impact Factor
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