A neuromusculoskeletal model of the human lower limb: Towards EMG-driven actuation of multiple joints in powered orthoses
Author(s)
Sartori, Massimo
Reggiani, Monica
Lloyd, David G
Pagello, Enrico
Griffith University Author(s)
Year published
2011
Metadata
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This paper presents a novel neuromusculoskeletal (NMS) model of the human lower limb that uses the electromyographic (EMG) signals from 16 muscles to estimate forces generated by 34 musculotendon actuators and the resulting joint moments at the hip, knee and ankle joints during varied contractile conditions. Our proposed methodology allows overcoming limitations on force computation shown by currently available NMS models, which constrain the operation of muscles to satisfy joint moments about one single degree of freedom (DOF) only (i.e. knee flexion-extension). The design of advanced human machine interfaces can benefit ...
View more >This paper presents a novel neuromusculoskeletal (NMS) model of the human lower limb that uses the electromyographic (EMG) signals from 16 muscles to estimate forces generated by 34 musculotendon actuators and the resulting joint moments at the hip, knee and ankle joints during varied contractile conditions. Our proposed methodology allows overcoming limitations on force computation shown by currently available NMS models, which constrain the operation of muscles to satisfy joint moments about one single degree of freedom (DOF) only (i.e. knee flexion-extension). The design of advanced human machine interfaces can benefit from the application of our proposed multi-DOF NMS model. The better estimates of the human internal state it provides with respect to single-DOF NMS models, will allow designing more intuitive human-machine interfaces for the simultaneous EMG-driven actuation of multiple joints in lower limb powered orthoses.
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View more >This paper presents a novel neuromusculoskeletal (NMS) model of the human lower limb that uses the electromyographic (EMG) signals from 16 muscles to estimate forces generated by 34 musculotendon actuators and the resulting joint moments at the hip, knee and ankle joints during varied contractile conditions. Our proposed methodology allows overcoming limitations on force computation shown by currently available NMS models, which constrain the operation of muscles to satisfy joint moments about one single degree of freedom (DOF) only (i.e. knee flexion-extension). The design of advanced human machine interfaces can benefit from the application of our proposed multi-DOF NMS model. The better estimates of the human internal state it provides with respect to single-DOF NMS models, will allow designing more intuitive human-machine interfaces for the simultaneous EMG-driven actuation of multiple joints in lower limb powered orthoses.
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Conference Title
2011 IEEE INTERNATIONAL CONFERENCE ON REHABILITATION ROBOTICS (ICORR)
Volume
2011
Subject
Biomechanical Engineering
Biomechanics