Biodynamic verification of an estimated muscular activity model for orthosis prescription support systems

Jun Inoue, Kazuya Kawamura, Masakatsu G. Fujie

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    In this paper, we performed biodynamic verification of a muscular activity model using Bayes estimation. In creating this model, we aimed to enable quantitative selection of lower foot orthoses based on a patient's muscular activity in the lower foot. Because physical models require the use of large-scale measurement systems, which cannot be used clinically, they are not suitable for making these measurements. Therefore, we chose Bayes estimation to construct a model for estimating the muscular activity from parameters that can be measured easily, such as joint angle and sole pressure. This model allows for not only the estimation of muscle activity, but also another closely related parameter through the change in muscular activity, which is a parent node to the muscle activity node. The three advantages of our model are that it 1) reports the influences on muscle activity, which change throughout the gait cycle, by using 10% level nodes for each factor; 2) expresses the influence of those factors, which are different at low and high muscular activity levels; and 3) compensates for missed predictions by estimating muscle activity in 10% increments. Here, we verify the biodynamic validity of the model parent node for four foot muscles.

    Original languageEnglish
    Title of host publicationProceedings of the IASTED International Conference on Biomedical Engineering, BioMed 2014
    PublisherActa Press
    Pages260-266
    Number of pages7
    DOIs
    Publication statusPublished - 2014
    EventIASTED International Conference on Biomedical Engineering, BioMed 2014 - Zurich
    Duration: 2014 Jun 232014 Jun 25

    Other

    OtherIASTED International Conference on Biomedical Engineering, BioMed 2014
    CityZurich
    Period14/6/2314/6/25

    Fingerprint

    Muscle
    Bayes Estimation
    Model
    Vertex of a graph
    Gait
    Large-scale Systems
    Physical Model
    Measurement System
    Increment
    Express
    Choose
    Verify
    Cycle
    Angle
    Prediction
    Influence

    Keywords

    • Bayesian network
    • EMG
    • Gait analysis
    • Lower leg orthosis

    ASJC Scopus subject areas

    • Modelling and Simulation

    Cite this

    Inoue, J., Kawamura, K., & Fujie, M. G. (2014). Biodynamic verification of an estimated muscular activity model for orthosis prescription support systems. In Proceedings of the IASTED International Conference on Biomedical Engineering, BioMed 2014 (pp. 260-266). Acta Press. https://doi.org/10.2316/P.2014.818-028

    Biodynamic verification of an estimated muscular activity model for orthosis prescription support systems. / Inoue, Jun; Kawamura, Kazuya; Fujie, Masakatsu G.

    Proceedings of the IASTED International Conference on Biomedical Engineering, BioMed 2014. Acta Press, 2014. p. 260-266.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Inoue, J, Kawamura, K & Fujie, MG 2014, Biodynamic verification of an estimated muscular activity model for orthosis prescription support systems. in Proceedings of the IASTED International Conference on Biomedical Engineering, BioMed 2014. Acta Press, pp. 260-266, IASTED International Conference on Biomedical Engineering, BioMed 2014, Zurich, 14/6/23. https://doi.org/10.2316/P.2014.818-028
    Inoue J, Kawamura K, Fujie MG. Biodynamic verification of an estimated muscular activity model for orthosis prescription support systems. In Proceedings of the IASTED International Conference on Biomedical Engineering, BioMed 2014. Acta Press. 2014. p. 260-266 https://doi.org/10.2316/P.2014.818-028
    Inoue, Jun ; Kawamura, Kazuya ; Fujie, Masakatsu G. / Biodynamic verification of an estimated muscular activity model for orthosis prescription support systems. Proceedings of the IASTED International Conference on Biomedical Engineering, BioMed 2014. Acta Press, 2014. pp. 260-266
    @inproceedings{c1dd698878f042e39f3651b746f4862a,
    title = "Biodynamic verification of an estimated muscular activity model for orthosis prescription support systems",
    abstract = "In this paper, we performed biodynamic verification of a muscular activity model using Bayes estimation. In creating this model, we aimed to enable quantitative selection of lower foot orthoses based on a patient's muscular activity in the lower foot. Because physical models require the use of large-scale measurement systems, which cannot be used clinically, they are not suitable for making these measurements. Therefore, we chose Bayes estimation to construct a model for estimating the muscular activity from parameters that can be measured easily, such as joint angle and sole pressure. This model allows for not only the estimation of muscle activity, but also another closely related parameter through the change in muscular activity, which is a parent node to the muscle activity node. The three advantages of our model are that it 1) reports the influences on muscle activity, which change throughout the gait cycle, by using 10{\%} level nodes for each factor; 2) expresses the influence of those factors, which are different at low and high muscular activity levels; and 3) compensates for missed predictions by estimating muscle activity in 10{\%} increments. Here, we verify the biodynamic validity of the model parent node for four foot muscles.",
    keywords = "Bayesian network, EMG, Gait analysis, Lower leg orthosis",
    author = "Jun Inoue and Kazuya Kawamura and Fujie, {Masakatsu G.}",
    year = "2014",
    doi = "10.2316/P.2014.818-028",
    language = "English",
    pages = "260--266",
    booktitle = "Proceedings of the IASTED International Conference on Biomedical Engineering, BioMed 2014",
    publisher = "Acta Press",

    }

    TY - GEN

    T1 - Biodynamic verification of an estimated muscular activity model for orthosis prescription support systems

    AU - Inoue, Jun

    AU - Kawamura, Kazuya

    AU - Fujie, Masakatsu G.

    PY - 2014

    Y1 - 2014

    N2 - In this paper, we performed biodynamic verification of a muscular activity model using Bayes estimation. In creating this model, we aimed to enable quantitative selection of lower foot orthoses based on a patient's muscular activity in the lower foot. Because physical models require the use of large-scale measurement systems, which cannot be used clinically, they are not suitable for making these measurements. Therefore, we chose Bayes estimation to construct a model for estimating the muscular activity from parameters that can be measured easily, such as joint angle and sole pressure. This model allows for not only the estimation of muscle activity, but also another closely related parameter through the change in muscular activity, which is a parent node to the muscle activity node. The three advantages of our model are that it 1) reports the influences on muscle activity, which change throughout the gait cycle, by using 10% level nodes for each factor; 2) expresses the influence of those factors, which are different at low and high muscular activity levels; and 3) compensates for missed predictions by estimating muscle activity in 10% increments. Here, we verify the biodynamic validity of the model parent node for four foot muscles.

    AB - In this paper, we performed biodynamic verification of a muscular activity model using Bayes estimation. In creating this model, we aimed to enable quantitative selection of lower foot orthoses based on a patient's muscular activity in the lower foot. Because physical models require the use of large-scale measurement systems, which cannot be used clinically, they are not suitable for making these measurements. Therefore, we chose Bayes estimation to construct a model for estimating the muscular activity from parameters that can be measured easily, such as joint angle and sole pressure. This model allows for not only the estimation of muscle activity, but also another closely related parameter through the change in muscular activity, which is a parent node to the muscle activity node. The three advantages of our model are that it 1) reports the influences on muscle activity, which change throughout the gait cycle, by using 10% level nodes for each factor; 2) expresses the influence of those factors, which are different at low and high muscular activity levels; and 3) compensates for missed predictions by estimating muscle activity in 10% increments. Here, we verify the biodynamic validity of the model parent node for four foot muscles.

    KW - Bayesian network

    KW - EMG

    KW - Gait analysis

    KW - Lower leg orthosis

    UR - http://www.scopus.com/inward/record.url?scp=84906975533&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84906975533&partnerID=8YFLogxK

    U2 - 10.2316/P.2014.818-028

    DO - 10.2316/P.2014.818-028

    M3 - Conference contribution

    AN - SCOPUS:84906975533

    SP - 260

    EP - 266

    BT - Proceedings of the IASTED International Conference on Biomedical Engineering, BioMed 2014

    PB - Acta Press

    ER -