Journal
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
Volume 59, Issue 9, Pages 2642-2649Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TBME.2012.2208746
Keywords
Assistive technologies; electromyography (EMG); knee joint; musculoskeletal modeling
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Funding
- National Institutes of Health, U.S. [R01EB009351-01A2]
- National Health and Medical Research Council, Australia [628850, 334151]
- Western Australia Medical and Health Research Infrastructure Council
- CARIPARO Foundation, Italy
- University of Padova
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In this paper, we use motion capture technology together with an EMG-driven musculoskeletal model of the knee joint to predict muscle behavior during human dynamic movements. We propose a muscle model based on infinitely stiff tendons and show this allows speeding up 250 times the computation of muscle force and the resulting joint moment calculation with no loss of accuracy with respect to the previously developed elastictendon model. We then integrate our previously developed method for the estimation of 3-D musculotendon kinematics in the proposed EMG-driven model. This new code enabled the creation of a standalone EMG-driven model that was implemented and run on an embedded system for applications in assistive technologies such as myoelectrically controlled prostheses and orthoses.
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