Musculoskeletal modelling and EMG driven simulation of the human lower body
By: by Alan R. Morris.
Published: 2006
Language: eng
Number of pages: 244
ISBN-13: 9780494157336
Subjects: Musculoskeletal system -- Mathematical models.; Biomechanics -- Mathematical models.
Description: Predictive musculoskeletal models have the potential to positively influence the orthopaedic management of movement pathologies such as those for children with cerebral palsy. Quantitative measurement of movement and muscle activity is routinely used in various rehabilitation centres to gain insight into the origins of case-specific dynamic movement pathologies, yet these analyses are subjectively interpreted by a clinical team to assist in musculotendon and skeletal surgery decision-making. Predictive musculoskeletal models need to be capable of "virtually testing" particular surgical interventions through the use of computer software and thus decrease the subjectivity of the current approach. Such musculoskeletal models will need to be scaled to the anatomical dimensions of individual subjects, be able to predict gross movements from physiological signals of muscle recruitment, and be able to predict the alteration of such physiological signals due to orthopaedic interventions.This thesis is directed at the development of a preliminary scalable, modifiable electromyographically-driven musculoskeletal model. To realize the model, various components have been investigated and performance of a subset of the model has been evaluated using acquired subject data. A scalable geometric model of musculotendon actuators covering the lower-body was defined from and adult database. A new phenomenological Hill-type EMG-driven dynamic computational muscle model has been developed and validated against published and new experimental data, and compared to the existing best model. Furthermore a complete lower-body simulation model was constructed incorporating skeletal joint definitions, musculotendon actuators, passive joint dynamics and ground reactions forces.An EMG-driven inverse-kinetic simulation model of dynamometer knee flexion-extension contraction incorporating thirteen muscles was developed and evaluated using dynamometric data from tests covering a wide-range of contraction modes (isokinetic, isotonic, eccentric, and isometric) and speeds 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%.
Notes: Source: Dissertation Abstracts International, Volume: 67-06, Section: B, page: 3271.

Thesis (Ph.D.)--University of Toronto, 2006.

Includes bibliographical references.

Electronic version licensed for access by U. of T. users.