A new method for estimating subject-specific muscle-tendon parameters of the knee joint actuators: a simulation study
SUMMARYA new method for the estimation of subject‐specific muscle–tendon parameters of the knee actuators based on dynamometry experiments is presented. The algorithm aims at estimating the tendon slack length and the optimal muscle fiber length by minimizing the difference between experimentally re...
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| Published in | International journal for numerical methods in biomedical engineering Vol. 30; no. 10; pp. 969 - 987 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Blackwell Publishing Ltd
01.10.2014
Wiley Subscription Services, Inc |
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| Abstract | SUMMARYA new method for the estimation of subject‐specific muscle–tendon parameters of the knee actuators based on dynamometry experiments is presented. The algorithm aims at estimating the tendon slack length and the optimal muscle fiber length by minimizing the difference between experimentally reproduced and model‐based joint moments. The key innovative features are as follows: (i) the inclusion of a priori physiological knowledge to define a physiologically feasible set, the hot start for the optimization, and constraints for the optimization and (ii) the introduction of a new (affine) transformation of the muscle–tendon parameters, which greatly improves the numerical condition of the optimization.The influence of the initial guess and of measurement noise was studied in a simulation environment, and the performance was compared with that of the method presented earlier by Garner and Pandy for the upper limb. The tendon slack length was estimated for 97.5/63% (extensors/flexors) of all initial guesses within 2% of the ground truth. The optimal fiber length was estimated for 89/90% (extensors/flexors) of all initial guesses within 2% of the ground truth. When 10 Nm measurement noise was added, the mean value of the estimated tendon slack length deviated at most 1.9/1.6% (extensors/flexors) from the ground truth whereas the standard deviations were at most 5.1/3.9%. The mean value of the estimated optimal fiber length deviated at most 4.3/3.0% (extensors/flexors) from the ground truth whereas the standard deviations were at most 10.2/15.5%. In comparison, mean values resulting from the method of Garner and Pandy deviated up to 181% ( ± 123%) and 119% ( ± 30%) from the ground truth for, respectively, optimal fiber length and tendon slack length of rectus femoris.We concluded that the presented method had a low dependency on the initial guess and outperformed the method of Garner and Pandy in terms of accuracy by at least one order of magnitude when parameters were estimated from noisy data. The improvements open new perspectives for subject‐specific modelling of muscles and tendons, which is beneficial for the accuracy of human motion simulations. Copyright © 2014 John Wiley & Sons, Ltd.
Subject‐specific estimation of muscle‐tendon parameters of the knee joint benefits from the inclusion of a priori physiological knowledge. The proposed formulation of the estimation problem substantially improves the numerical efficiency. The method is benchmarked against the method of Garner and Pandy (2003). It resulted that the new method outperformed the benchmark by one order of magnitude in terms of accuracy when measurement noise is taken into account. |
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| AbstractList | A new method for the estimation of subject‐specific muscle–tendon parameters of the knee actuators based on dynamometry experiments is presented. The algorithm aims at estimating the tendon slack length and the optimal muscle fiber length by minimizing the difference between experimentally reproduced and model‐based joint moments. The key innovative features are as follows: (i) the inclusion of
a priori
physiological knowledge to define a physiologically feasible set, the hot start for the optimization, and constraints for the optimization and (ii) the introduction of a new (affine) transformation of the muscle–tendon parameters, which greatly improves the numerical condition of the optimization.
The influence of the initial guess and of measurement noise was studied in a simulation environment, and the performance was compared with that of the method presented earlier by Garner and Pandy for the upper limb. The tendon slack length was estimated for 97.5/63% (extensors/flexors) of all initial guesses within 2% of the ground truth. The optimal fiber length was estimated for 89/90% (extensors/flexors) of all initial guesses within 2% of the ground truth. When 10 Nm measurement noise was added, the mean value of the estimated tendon slack length deviated at most 1.9/1.6% (extensors/flexors) from the ground truth whereas the standard deviations were at most 5.1/3.9%. The mean value of the estimated optimal fiber length deviated at most 4.3/3.0% (extensors/flexors) from the ground truth whereas the standard deviations were at most 10.2/15.5%. In comparison, mean values resulting from the method of Garner and Pandy deviated up to 181% ( ± 123%) and 119% ( ± 30%) from the ground truth for, respectively, optimal fiber length and tendon slack length of rectus femoris.
We concluded that the presented method had a low dependency on the initial guess and outperformed the method of Garner and Pandy in terms of accuracy by at least one order of magnitude when parameters were estimated from noisy data. The improvements open new perspectives for subject‐specific modelling of muscles and tendons, which is beneficial for the accuracy of human motion simulations. Copyright © 2014 John Wiley & Sons, Ltd. SUMMARY A new method for the estimation of subject-specific muscle-tendon parameters of the knee actuators based on dynamometry experiments is presented. The algorithm aims at estimating the tendon slack length and the optimal muscle fiber length by minimizing the difference between experimentally reproduced and model-based joint moments. The key innovative features are as follows: (i) the inclusion of a priori physiological knowledge to define a physiologically feasible set, the hot start for the optimization, and constraints for the optimization and (ii) the introduction of a new (affine) transformation of the muscle-tendon parameters, which greatly improves the numerical condition of the optimization. The influence of the initial guess and of measurement noise was studied in a simulation environment, and the performance was compared with that of the method presented earlier by Garner and Pandy for the upper limb. The tendon slack length was estimated for 97.5/63% (extensors/flexors) of all initial guesses within 2% of the ground truth. The optimal fiber length was estimated for 89/90% (extensors/flexors) of all initial guesses within 2% of the ground truth. When 10 Nm measurement noise was added, the mean value of the estimated tendon slack length deviated at most 1.9/1.6% (extensors/flexors) from the ground truth whereas the standard deviations were at most 5.1/3.9%. The mean value of the estimated optimal fiber length deviated at most 4.3/3.0% (extensors/flexors) from the ground truth whereas the standard deviations were at most 10.2/15.5%. In comparison, mean values resulting from the method of Garner and Pandy deviated up to 181% (±123%) and 119% (±30%) from the ground truth for, respectively, optimal fiber length and tendon slack length of rectus femoris. We concluded that the presented method had a low dependency on the initial guess and outperformed the method of Garner and Pandy in terms of accuracy by at least one order of magnitude when parameters were estimated from noisy data. The improvements open new perspectives for subject-specific modelling of muscles and tendons, which is beneficial for the accuracy of human motion simulations. Copyright © 2014 John Wiley & Sons, Ltd. A new method for the estimation of subject-specific muscle-tendon parameters of the knee actuators based on dynamometry experiments is presented. The algorithm aims at estimating the tendon slack length and the optimal muscle fiber length by minimizing the difference between experimentally reproduced and model-based joint moments. The key innovative features are as follows: (i) the inclusion of a priori physiological knowledge to define a physiologically feasible set, the hot start for the optimization, and constraints for the optimization and (ii) the introduction of a new (affine) transformation of the muscle-tendon parameters, which greatly improves the numerical condition of the optimization. The influence of the initial guess and of measurement noise was studied in a simulation environment, and the performance was compared with that of the method presented earlier by Garner and Pandy for the upper limb. The tendon slack length was estimated for 97.5/63% (extensors/flexors) of all initial guesses within 2% of the ground truth. The optimal fiber length was estimated for 89/90% (extensors/flexors) of all initial guesses within 2% of the ground truth. When 10 Nm measurement noise was added, the mean value of the estimated tendon slack length deviated at most 1.9/1.6% (extensors/flexors) from the ground truth whereas the standard deviations were at most 5.1/3.9%. The mean value of the estimated optimal fiber length deviated at most 4.3/3.0% (extensors/flexors) from the ground truth whereas the standard deviations were at most 10.2/15.5%. In comparison, mean values resulting from the method of Garner and Pandy deviated up to 181% ( ± 123%) and 119% ( ± 30%) from the ground truth for, respectively, optimal fiber length and tendon slack length of rectus femoris. We concluded that the presented method had a low dependency on the initial guess and outperformed the method of Garner and Pandy in terms of accuracy by at least one order of magnitude when parameters were estimated from noisy data. The improvements open new perspectives for subject-specific modelling of muscles and tendons, which is beneficial for the accuracy of human motion simulations. SUMMARYA new method for the estimation of subject‐specific muscle–tendon parameters of the knee actuators based on dynamometry experiments is presented. The algorithm aims at estimating the tendon slack length and the optimal muscle fiber length by minimizing the difference between experimentally reproduced and model‐based joint moments. The key innovative features are as follows: (i) the inclusion of a priori physiological knowledge to define a physiologically feasible set, the hot start for the optimization, and constraints for the optimization and (ii) the introduction of a new (affine) transformation of the muscle–tendon parameters, which greatly improves the numerical condition of the optimization.The influence of the initial guess and of measurement noise was studied in a simulation environment, and the performance was compared with that of the method presented earlier by Garner and Pandy for the upper limb. The tendon slack length was estimated for 97.5/63% (extensors/flexors) of all initial guesses within 2% of the ground truth. The optimal fiber length was estimated for 89/90% (extensors/flexors) of all initial guesses within 2% of the ground truth. When 10 Nm measurement noise was added, the mean value of the estimated tendon slack length deviated at most 1.9/1.6% (extensors/flexors) from the ground truth whereas the standard deviations were at most 5.1/3.9%. The mean value of the estimated optimal fiber length deviated at most 4.3/3.0% (extensors/flexors) from the ground truth whereas the standard deviations were at most 10.2/15.5%. In comparison, mean values resulting from the method of Garner and Pandy deviated up to 181% ( ± 123%) and 119% ( ± 30%) from the ground truth for, respectively, optimal fiber length and tendon slack length of rectus femoris.We concluded that the presented method had a low dependency on the initial guess and outperformed the method of Garner and Pandy in terms of accuracy by at least one order of magnitude when parameters were estimated from noisy data. The improvements open new perspectives for subject‐specific modelling of muscles and tendons, which is beneficial for the accuracy of human motion simulations. Copyright © 2014 John Wiley & Sons, Ltd. Subject‐specific estimation of muscle‐tendon parameters of the knee joint benefits from the inclusion of a priori physiological knowledge. The proposed formulation of the estimation problem substantially improves the numerical efficiency. The method is benchmarked against the method of Garner and Pandy (2003). It resulted that the new method outperformed the benchmark by one order of magnitude in terms of accuracy when measurement noise is taken into account. A new method for the estimation of subject-specific muscle-tendon parameters of the knee actuators based on dynamometry experiments is presented. The algorithm aims at estimating the tendon slack length and the optimal muscle fiber length by minimizing the difference between experimentally reproduced and model-based joint moments. The key innovative features are as follows: (i) the inclusion of a priori physiological knowledge to define a physiologically feasible set, the hot start for the optimization, and constraints for the optimization and (ii) the introduction of a new (affine) transformation of the muscle-tendon parameters, which greatly improves the numerical condition of the optimization. The influence of the initial guess and of measurement noise was studied in a simulation environment, and the performance was compared with that of the method presented earlier by Garner and Pandy for the upper limb. The tendon slack length was estimated for 97.5/63% (extensors/flexors) of all initial guesses within 2% of the ground truth. The optimal fiber length was estimated for 89/90% (extensors/flexors) of all initial guesses within 2% of the ground truth. When 10 Nm measurement noise was added, the mean value of the estimated tendon slack length deviated at most 1.9/1.6% (extensors/flexors) from the ground truth whereas the standard deviations were at most 5.1/3.9%. The mean value of the estimated optimal fiber length deviated at most 4.3/3.0% (extensors/flexors) from the ground truth whereas the standard deviations were at most 10.2/15.5%. In comparison, mean values resulting from the method of Garner and Pandy deviated up to 181% ( ± 123%) and 119% ( ± 30%) from the ground truth for, respectively, optimal fiber length and tendon slack length of rectus femoris. We concluded that the presented method had a low dependency on the initial guess and outperformed the method of Garner and Pandy in terms of accuracy by at least one order of magnitude when parameters were estimated from noisy data. The improvements open new perspectives for subject-specific modelling of muscles and tendons, which is beneficial for the accuracy of human motion simulations.A new method for the estimation of subject-specific muscle-tendon parameters of the knee actuators based on dynamometry experiments is presented. The algorithm aims at estimating the tendon slack length and the optimal muscle fiber length by minimizing the difference between experimentally reproduced and model-based joint moments. The key innovative features are as follows: (i) the inclusion of a priori physiological knowledge to define a physiologically feasible set, the hot start for the optimization, and constraints for the optimization and (ii) the introduction of a new (affine) transformation of the muscle-tendon parameters, which greatly improves the numerical condition of the optimization. The influence of the initial guess and of measurement noise was studied in a simulation environment, and the performance was compared with that of the method presented earlier by Garner and Pandy for the upper limb. The tendon slack length was estimated for 97.5/63% (extensors/flexors) of all initial guesses within 2% of the ground truth. The optimal fiber length was estimated for 89/90% (extensors/flexors) of all initial guesses within 2% of the ground truth. When 10 Nm measurement noise was added, the mean value of the estimated tendon slack length deviated at most 1.9/1.6% (extensors/flexors) from the ground truth whereas the standard deviations were at most 5.1/3.9%. The mean value of the estimated optimal fiber length deviated at most 4.3/3.0% (extensors/flexors) from the ground truth whereas the standard deviations were at most 10.2/15.5%. In comparison, mean values resulting from the method of Garner and Pandy deviated up to 181% ( ± 123%) and 119% ( ± 30%) from the ground truth for, respectively, optimal fiber length and tendon slack length of rectus femoris. We concluded that the presented method had a low dependency on the initial guess and outperformed the method of Garner and Pandy in terms of accuracy by at least one order of magnitude when parameters were estimated from noisy data. The improvements open new perspectives for subject-specific modelling of muscles and tendons, which is beneficial for the accuracy of human motion simulations. |
| Author | Van Campen, Anke De Schutter, Joris Jonkers, Ilse Pipeleers, Goele De Groote, Friedl |
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| Keywords | estimation motion simulation muscle-tendon parameters optimization subject specific |
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| Snippet | SUMMARYA new method for the estimation of subject‐specific muscle–tendon parameters of the knee actuators based on dynamometry experiments is presented. The... A new method for the estimation of subject‐specific muscle–tendon parameters of the knee actuators based on dynamometry experiments is presented. The algorithm... A new method for the estimation of subject-specific muscle-tendon parameters of the knee actuators based on dynamometry experiments is presented. The algorithm... SUMMARY A new method for the estimation of subject-specific muscle-tendon parameters of the knee actuators based on dynamometry experiments is presented. The... |
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| SubjectTerms | Algorithms Computer Simulation estimation Humans Knee Joint - physiology Models, Biological Motion motion simulation Muscle Fibers, Skeletal - cytology Muscle Fibers, Skeletal - physiology Muscle, Skeletal - physiology muscle-tendon parameters optimization subject specific Tendons - anatomy & histology Tendons - physiology |
| Title | A new method for estimating subject-specific muscle-tendon parameters of the knee joint actuators: a simulation study |
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