A RESPONSIVE MYOELECTRIC CONTROL SIGNAL PROCESSING TECHNIQUE USING MUSCLE EXCITATION-CONTRACTION MODELING
DOI:
https://doi.org/10.57922/mec.2496Abstract
Existing myoelectric controllers operate in a sequential fashion and use a state machine architecture to select grip postures. Direct control interfaces that seek to map individual muscles with joints in a prosthesis can provide a greater ability to perform individuated movements but require users to selectively activate their muscles to prevent unintended motion from natural muscle co-activations. Musculoskeletal modeling offers a possibility to estimate joint motion from muscle co-activation patterns themselves but require significant computational resources to run in real time. A major source of delay in a myoelectric system that reduces the amount of time available for advanced signal decoding schemes such as a musculoskeletal model is the low-pass filtering of rectified EMG signals. To minimize these delays, we explore the low-pass filtering properties of skeletal muscle using a simplified excitation-contraction dynamics model, applying a thresholded EMG signal and the rectified EMG profile itself as model inputs. Our results indicate that passing these signals through a biomechanical model of muscle can produce a usable myoelectric control signal while introducing a physiologically appropriate amount of delay between EMG onset and muscle force estimation.
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Published
2024-08-15
How to Cite
[1]
B. Murali and R. Weir, “A RESPONSIVE MYOELECTRIC CONTROL SIGNAL PROCESSING TECHNIQUE USING MUSCLE EXCITATION-CONTRACTION MODELING”, MEC Symposium, Aug. 2024.
Conference Proceedings Volume
Section
Myoelectric Control Algorithms
