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• W2050318530 abstract "During human walking there exists a functional neural coupling between arms and legs, and between cervical and lumbosacral pattern generators. Here we present a novel approach for associating the electromyographic (EMG) activity from upper limb muscles with leg kinematics. Our methodology takes advantage of the high involvement of shoulder muscles in most locomotor-related movements and of the natural coordination between arms and legs. Nine healthy subjects were asked to walk at different constant and variable speeds (3-5 km/h), while EMG activity of shoulder (deltoid) muscles and the kinematics of walking were recorded. To ensure a high level of EMG activity in deltoid, the subjects performed slightly larger arm swinging than they usually do. The temporal structure of the burst-like EMG activity was used to predict the spatiotemporal kinematic pattern of the forthcoming step. A comparison of actual and predicted stride leg kinematics showed a high degree of correspondence (r>0.9). This algorithm has been also implemented in pilot experiments for controlling avatar walking in a virtual reality setup and an exoskeleton during overground stepping. The proposed approach may have important implications for the design of human-machine interfaces and neuroprosthetic technologies such as those of assistive lower limb exoskeletons." @default.
• W2050318530 created "2016-06-24" @default.
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• W2050318530 date "2014-10-20" @default.
• W2050318530 modified "2023-09-26" @default.
• W2050318530 title "Control of Leg Movements Driven by EMG Activity of Shoulder Muscles" @default.
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• W2050318530 doi "https://doi.org/10.3389/fnhum.2014.00838" @default.
• W2050318530 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4202724" @default.
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