DocumentCode :
2681376
Title :
Human walking model predicts joint mechanics, electromyography and mechanical economy
Author :
Endo, Ken ; Herr, Hugh
Author_Institution :
Biomechatronics Group, Massachusetts Inst. of Technol., Cambridge, MA, USA
fYear :
2009
fDate :
10-15 Oct. 2009
Firstpage :
4663
Lastpage :
4668
Abstract :
In this paper, we present an under-actuated model of human walking, comprising only a soleus muscle and flexion/extension monoarticular hip muscles. The remaining muscle groups of the human leg are modeled using quasi-passive, series-elastic clutch elements. We hypothesize that series-elastic clutch units spanning the knee joint in a musculoskeletal arrangement can capture the dominant mechanical behaviors of the human knee in level-ground walking. As an evaluation of the musculoskeletal model, we vary model parameters, or spring constants, and muscle control parameters using an optimization scheme that maximizes walking distance and minimizes the mechanical economy of walking. We used a positive force feedback reflex control for the model´s soleus muscle, and upper body position control for the hip muscles. The model´s clutches were engaged/disengaged using simple state machine controllers. For model evaluation, a forward dynamics simulation was conducted, and the resulting mechanics were compared to human walking data. The model makes qualitative predictions of joint mechanics, electromyography and mechanical economy.
Keywords :
biomechanics; electromyography; force control; force feedback; prosthetics; electromyography; flexion/extension monoarticular hip muscles; forward dynamics simulation; human knee; human walking model; joint mechanics; level-ground walking; mechanical behaviors; mechanical economy; muscle control parameters; musculoskeletal arrangement; musculoskeletal model; positive force feedback reflex control; series-elastic clutch elements; soleus muscle; under-actuated model; Biological system modeling; Electromyography; Hip; Humans; Knee; Leg; Legged locomotion; Muscles; Musculoskeletal system; Predictive models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on
Conference_Location :
St. Louis, MO
Print_ISBN :
978-1-4244-3803-7
Electronic_ISBN :
978-1-4244-3804-4
Type :
conf
DOI :
10.1109/IROS.2009.5354230
Filename :
5354230
Link To Document :
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