A SURFACE EMG DRIVEN MUSCULOSKELETAL MODEL OF THE ELBOW FLEXION-EXTENSION MOVEMENT IN NORMAL SUBJECTS AND IN SUBJECTS WITH SPASTICITY
Spasticity often interferes with function, limits independence and may cause considerable disability. Elbow joint movement is involved in many daily living activities. A surface EMG driven musculoskeletal model was developed to predict joint trajectory and to compare the differences in the model par...
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Published in | Journal of musculoskeletal research Vol. 3; no. 2; pp. 109 - 123 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
World Scientific Publishing Company
01.06.1999
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Subjects | |
Online Access | Get full text |
ISSN | 0218-9577 1793-6497 |
DOI | 10.1142/S0218957799000129 |
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Abstract | Spasticity often interferes with function, limits independence and
may cause considerable disability. Elbow joint movement is involved in
many daily living activities. A surface EMG driven musculoskeletal
model was developed to predict joint trajectory and to compare the
differences in the model parameters between the normal and spastic
subjects. Three musculotendon actuators whose EMG could be assessed
by surface electrodes (biceps, brachioradialis and triceps) were
included in this musculoskeletal model. The proposed model took
several sets of parameters (anthropometric parameters of the skeleton
and muscle parameters) as inputs. Surface EMG signals of the three
muscle groups were rectified, moving-averaged, scaled and
converted to active states. These active states together with the
initial angular position and velocity of the joint were also used as
inputs for the model. The outputs were muscle forces and the
trajectory of the elbow joint. Two groups of parameters, namely,
maximal isometric muscle stress and electromechanical delay were
estimated using the trajectory fitting algorithm. Results indicated
that the model was successful in using the surface EMG as input
signals in the prediction of elbow joint trajectory. The spastic
subjects showed a lower maximum isometric muscle stress and longer
electromechanical delay. |
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AbstractList | Spasticity often interferes with function, limits independence and may cause considerable disability. Elbow joint movement is involved in many daily living activities. A surface EMG driven musculoskeletal model was developed to predict joint trajectory and to compare the differences in the model parameters between the normal and spastic subjects. Three musculotendon actuators whose EMG could be assessed by surface electrodes (biceps, brachioradialis and triceps) were included in this musculoskeletal model. The proposed model took several sets of parameters (anthropometric parameters of the skeleton and muscle parameters) as inputs. Surface EMG signals of the three muscle groups were rectified, moving-averaged, scaled and converted to active states. These active states together with the initial angular position and velocity of the joint were also used as inputs for the model. The outputs were muscle forces and the trajectory of the elbow joint. Two groups of parameters, namely, maximal isometric muscle stress and electromechanical delay were estimated using the trajectory fitting algorithm. Results indicated that the model was successful in using the surface EMG as input signals in the prediction of elbow joint trajectory. The spastic subjects showed a lower maximum isometric muscle stress and longer electromechanical delay. Spasticity often interferes with function, limits independence and may cause considerable disability. Elbow joint movement is involved in many daily living activities. A surface EMG driven musculoskeletal model was developed to predict joint trajectory and to compare the differences in the model parameters between the normal and spastic subjects. Three musculotendon actuators whose EMG could be assessed by surface electrodes (biceps, brachioradialis and triceps) were included in this musculoskeletal model. The proposed model took several sets of parameters (anthropometric parameters of the skeleton and muscle parameters) as inputs. Surface EMG signals of the three muscle groups were rectified, moving-averaged, scaled and converted to active states. These active states together with the initial angular position and velocity of the joint were also used as inputs for the model. The outputs were muscle forces and the trajectory of the elbow joint. Two groups of parameters, namely, maximal isometric muscle stress and electromechanical delay were estimated using the trajectory fitting algorithm. Results indicated that the model was successful in using the surface EMG as input signals in the prediction of elbow joint trajectory. The spastic subjects showed a lower maximum isometric muscle stress and longer electromechanical delay. |
Author | Mak, Arthur F. T. Feng, Connie J. Koo, Terry K. K. |
Author_xml | – sequence: 1 givenname: Connie J. surname: Feng fullname: Feng, Connie J. organization: Rehabilitation Engineering Centre, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, P.R.China – sequence: 2 givenname: Arthur F. T. surname: Mak fullname: Mak, Arthur F. T. organization: Rehabilitation Engineering Centre, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, P.R.China – sequence: 3 givenname: Terry K. K. surname: Koo fullname: Koo, Terry K. K. organization: Rehabilitation Engineering Centre, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, P.R.China |
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Cites_doi | 10.1136/bjsm.18.3.149 10.1098/rspb.1949.0033 10.1243/EMED_JOUR_1979_008_010_02 10.1055/s-2007-1021087 10.1007/BF00199465 10.1007/BF00365524 10.1007/BF00228120 |
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Keywords | Spasticity Joint kinematics Musculoskeletal modelling Elbow EMG |
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References | p_16 p_17 Zajac FE (p_33); 17 p_1 p_4 Ikai M (p_14) 1968; 26 p_25 Jorgensen K (p_15) 1971 p_7 Weijs WA (p_29) 1985; 23 Perry J (p_21) 1981; 7 White SC (p_30) 1986 p_11 |
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Snippet | Spasticity often interferes with function, limits independence and
may cause considerable disability. Elbow joint movement is involved in
many daily living... Spasticity often interferes with function, limits independence and may cause considerable disability. Elbow joint movement is involved in many daily living... |
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Title | A SURFACE EMG DRIVEN MUSCULOSKELETAL MODEL OF THE ELBOW FLEXION-EXTENSION MOVEMENT IN NORMAL SUBJECTS AND IN SUBJECTS WITH SPASTICITY |
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