Аннотация к книге "EMG Driven Musculoskeletal Simulation of the Human Lower Body. A Biomechanical and Electromyographyic Study"
Predictive musculoskeletal models have the potential to positively influence the orthopaedic management of movement pathologies. A scalable geometric model of the lower-body was defined from an adult database. A Hill-type EMG driven dynamic computational muscle model was developed and validated against published and new experimental data. A lower-body simulation model was constructed incorporating skeletal joint definitions, musculotendon actuators, passive joint dynamics and ground reactions...
Predictive musculoskeletal models have the potential to positively influence the orthopaedic management of movement pathologies. A scalable geometric model of the lower-body was defined from an adult database. A Hill-type EMG driven dynamic computational muscle model was developed and validated against published and new experimental data. A lower-body simulation model was constructed incorporating skeletal joint definitions, musculotendon actuators, passive joint dynamics and ground reactions forces. A 13-muscle EMG driven inverse-kinetic simulation model of knee flexion-extension contraction was developed and evaluated using dynamometric data covering a wide- range of contraction speeds and modes (isokinetic, isotonic, eccentric, and isometric) for five able- bodied adult male subjects. Both shape and transfer function based Hill-type muscle models were evaluated. For the transfer function-based model, across all subjects the average correlations ranged between r = 0.61-0.77 and average RMS error = 21- 29%. For the shape function-based model, the average correlations ranged between r = 0.76-0.92 and an average RMS error = 25-31%.
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