期刊
JOURNAL OF BIOMECHANICS
卷 39, 期 6, 页码 1107-1115出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jbiomech.2005.02.010
关键词
musculoskeletal modeling; dynamic simulation; optimization; control; gait
资金
- EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH &HUMAN DEVELOPMENT [R01HD038962, R01HD033929, R41HD045109] Funding Source: NIH RePORTER
- NICHD NIH HHS [HD38962, HD45109, HD33929] Funding Source: Medline
The objective of this study was to develop an efficient methodology for generating muscle-actuated simulations of human walking that closely reproduce experimental measures of kinematics and ground reaction forces. We first introduce a residual elimination algorithm (REA) to compute pelvis and low back kinematic trajectories that ensure consistency between whole-body dynamics and measured ground reactions. We then use a computed muscle control (CMC) algorithm to vary muscle excitations to track experimental joint kinematics within a forward dynamic simulation. CMC explicitly accounts for delays in muscle force production resulting from activation and contraction dynamics while using a general static optimization framework to resolve muscle redundancy. CMC was used to compute muscle excitation patterns that drove a 21-degrees-of-freedom, 92 muscle model to track experimental gait data of 10 healthy young adults. Simulated joint kinematics closely tracked experimental quantities (mean root mean-squared errors generally less than 1 degrees), and the time histories of muscle activations were similar to electromyographic recordings. A simulation of a half-cycle of gait could be generated using approximately 30 min of computer processing time. The speed and accuracy of REA and CMC make it practical to generate subject-specific simulations of gait. (c) 2005 Elsevier Ltd. All rights reserved.
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