Document Detail


Estimation of elbow-induced wrist force with EMG signals using fast orthogonal search.
MedLine Citation:
PMID:  17405375     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In many studies and applications that include direct human involvement-such as human-robot interaction, control of prosthetic arms, and human factor studies-hand force is needed for monitoring or control purposes. The use of inexpensive and easily portable active electromyogram (EMG) electrodes and position sensors would be advantageous in these applications compared to the use of force sensors, which are often very expensive and require bulky frames. Multilayer perceptron artificial neural networks (MLPANN) have been used commonly in the literature to model the relationship between surface EMG signals and muscle or limb forces for different anatomies. This paper investigates the use of fast orthogonal search (FOS), a time-domain method for rapid nonlinear system identification, for elbow-induced wrist force estimation. It further compares the forces estimated using FOS with the forces estimated by MLPANN for the same human anatomy under an ensemble of operational conditions. In this paper, the EMG signal readings from upper arm muscles involved in elbow joint movement and sensed elbow angular position and velocity are utilized as inputs. A single degree-of-freedom robotic experimental testbed has been constructed and used for data collection, training and validation.
Authors:
Farid Mobasser; J Mikael Eklund; Keyvan Hashtrudi-Zaad
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Publication Detail:
Type:  Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't; Validation Studies    
Journal Detail:
Title:  IEEE transactions on bio-medical engineering     Volume:  54     ISSN:  0018-9294     ISO Abbreviation:  IEEE Trans Biomed Eng     Publication Date:  2007 Apr 
Date Detail:
Created Date:  2007-04-04     Completed Date:  2007-04-24     Revised Date:  2009-11-11    
Medline Journal Info:
Nlm Unique ID:  0012737     Medline TA:  IEEE Trans Biomed Eng     Country:  United States    
Other Details:
Languages:  eng     Pagination:  683-93     Citation Subset:  IM    
Affiliation:
Invenium Technologies Corp., Toronto, ON M2N 6K1, Canada. farid.mobasser@invenium.ca
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Computer Simulation
Elbow Joint / physiology*
Electromyography / methods*
Humans
Models, Biological*
Muscle Contraction / physiology*
Muscle, Skeletal / physiology*
Neural Networks (Computer)*
Stress, Mechanical
Torque
Wrist Joint / physiology*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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