The development of sensor-based gait training system for locomotive syndrome

The effect of real-time gait feature feedback on gait pattern during treadmill walking

Hiroyuki Honda, Yoshiyuki Kobayashi, Akihiko Murai, Hiroshi Fujimoto

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

    Abstract

    The concept of locomotive syndrome was proposed by the Japanese Orthopedic Association; it typifies the condition of reduced mobility resulting from a locomotive organ disorder related to aging. Although several sensor-based gait training systems, which can feedback the gait features in real-time, have been developed for various musculoskeletal disorders, there are no such systems for locomotive syndrome. In this study, we reported how real-time locomotive syndrome related gait feature feedback effects on gait patterns during treadmill walking. 18 healthy participants were assigned into either intervention- or control-group. During 4 sessions (training-session, pre-intervention-session, intervention-session, and post-intervention-session), gait patterns were measured by a motion-capture system. During the intervention-session of the intervention-group, participants received LS-risk-scores made in this study. Meanwhile, they were asked to minimize the LS-risk-scores by modifying their knee joint motion. A two-way-repeated measure ANOVA was conducted on the LS-risk-scores to examine effects of the intervention. When interaction was found, paired t-tests were conducted on the LS-risk-scores and knee angles between the sessions respectively. As a result, the LS-risk-scores were significantly smaller (p < 0.05) during the post-intervention-session than the pre-intervention-session in the intervention-group. There were no significant differences on the LS-risk-scores between the sessions in the control-group. Further, in the intervention-group, significant differences (p < 0.05) were found between the sessions on the knee angles partially. There were no significant differences between the sessions on the knee angles in the control-group. These results indicate that people can alter their gait pattern if the LS-risk-scores are feedback in real-time.

    Original languageEnglish
    Title of host publicationProceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume I
    Subtitle of host publicationHealthcare Ergonomics
    EditorsSebastiano Bagnara, Yushi Fujita, Riccardo Tartaglia, Sara Albolino, Thomas Alexander
    PublisherSpringer-Verlag
    Pages305-311
    Number of pages7
    ISBN (Print)9783319960975
    DOIs
    Publication statusPublished - 2019 Jan 1
    Event20th Congress of the International Ergonomics Association, IEA 2018 - Florence, Italy
    Duration: 2018 Aug 262018 Aug 30

    Publication series

    NameAdvances in Intelligent Systems and Computing
    Volume818
    ISSN (Print)2194-5357

    Other

    Other20th Congress of the International Ergonomics Association, IEA 2018
    CountryItaly
    CityFlorence
    Period18/8/2618/8/30

    Fingerprint

    Exercise equipment
    Locomotives
    Feedback
    Sensors
    Orthopedics
    Analysis of variance (ANOVA)
    Aging of materials

    Keywords

    • Gait training
    • Locomotive syndrome
    • Real-time visual feedback

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Computer Science(all)

    Cite this

    Honda, H., Kobayashi, Y., Murai, A., & Fujimoto, H. (2019). The development of sensor-based gait training system for locomotive syndrome: The effect of real-time gait feature feedback on gait pattern during treadmill walking. In S. Bagnara, Y. Fujita, R. Tartaglia, S. Albolino, & T. Alexander (Eds.), Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume I: Healthcare Ergonomics (pp. 305-311). (Advances in Intelligent Systems and Computing; Vol. 818). Springer-Verlag. https://doi.org/10.1007/978-3-319-96098-2_40

    The development of sensor-based gait training system for locomotive syndrome : The effect of real-time gait feature feedback on gait pattern during treadmill walking. / Honda, Hiroyuki; Kobayashi, Yoshiyuki; Murai, Akihiko; Fujimoto, Hiroshi.

    Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume I: Healthcare Ergonomics. ed. / Sebastiano Bagnara; Yushi Fujita; Riccardo Tartaglia; Sara Albolino; Thomas Alexander. Springer-Verlag, 2019. p. 305-311 (Advances in Intelligent Systems and Computing; Vol. 818).

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

    Honda, H, Kobayashi, Y, Murai, A & Fujimoto, H 2019, The development of sensor-based gait training system for locomotive syndrome: The effect of real-time gait feature feedback on gait pattern during treadmill walking. in S Bagnara, Y Fujita, R Tartaglia, S Albolino & T Alexander (eds), Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume I: Healthcare Ergonomics. Advances in Intelligent Systems and Computing, vol. 818, Springer-Verlag, pp. 305-311, 20th Congress of the International Ergonomics Association, IEA 2018, Florence, Italy, 18/8/26. https://doi.org/10.1007/978-3-319-96098-2_40
    Honda H, Kobayashi Y, Murai A, Fujimoto H. The development of sensor-based gait training system for locomotive syndrome: The effect of real-time gait feature feedback on gait pattern during treadmill walking. In Bagnara S, Fujita Y, Tartaglia R, Albolino S, Alexander T, editors, Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume I: Healthcare Ergonomics. Springer-Verlag. 2019. p. 305-311. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-319-96098-2_40
    Honda, Hiroyuki ; Kobayashi, Yoshiyuki ; Murai, Akihiko ; Fujimoto, Hiroshi. / The development of sensor-based gait training system for locomotive syndrome : The effect of real-time gait feature feedback on gait pattern during treadmill walking. Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume I: Healthcare Ergonomics. editor / Sebastiano Bagnara ; Yushi Fujita ; Riccardo Tartaglia ; Sara Albolino ; Thomas Alexander. Springer-Verlag, 2019. pp. 305-311 (Advances in Intelligent Systems and Computing).
    @inproceedings{5c8af1aaf38d4ee4838f3a1a3149082e,
    title = "The development of sensor-based gait training system for locomotive syndrome: The effect of real-time gait feature feedback on gait pattern during treadmill walking",
    abstract = "The concept of locomotive syndrome was proposed by the Japanese Orthopedic Association; it typifies the condition of reduced mobility resulting from a locomotive organ disorder related to aging. Although several sensor-based gait training systems, which can feedback the gait features in real-time, have been developed for various musculoskeletal disorders, there are no such systems for locomotive syndrome. In this study, we reported how real-time locomotive syndrome related gait feature feedback effects on gait patterns during treadmill walking. 18 healthy participants were assigned into either intervention- or control-group. During 4 sessions (training-session, pre-intervention-session, intervention-session, and post-intervention-session), gait patterns were measured by a motion-capture system. During the intervention-session of the intervention-group, participants received LS-risk-scores made in this study. Meanwhile, they were asked to minimize the LS-risk-scores by modifying their knee joint motion. A two-way-repeated measure ANOVA was conducted on the LS-risk-scores to examine effects of the intervention. When interaction was found, paired t-tests were conducted on the LS-risk-scores and knee angles between the sessions respectively. As a result, the LS-risk-scores were significantly smaller (p < 0.05) during the post-intervention-session than the pre-intervention-session in the intervention-group. There were no significant differences on the LS-risk-scores between the sessions in the control-group. Further, in the intervention-group, significant differences (p < 0.05) were found between the sessions on the knee angles partially. There were no significant differences between the sessions on the knee angles in the control-group. These results indicate that people can alter their gait pattern if the LS-risk-scores are feedback in real-time.",
    keywords = "Gait training, Locomotive syndrome, Real-time visual feedback",
    author = "Hiroyuki Honda and Yoshiyuki Kobayashi and Akihiko Murai and Hiroshi Fujimoto",
    year = "2019",
    month = "1",
    day = "1",
    doi = "10.1007/978-3-319-96098-2_40",
    language = "English",
    isbn = "9783319960975",
    series = "Advances in Intelligent Systems and Computing",
    publisher = "Springer-Verlag",
    pages = "305--311",
    editor = "Sebastiano Bagnara and Yushi Fujita and Riccardo Tartaglia and Sara Albolino and Thomas Alexander",
    booktitle = "Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume I",

    }

    TY - GEN

    T1 - The development of sensor-based gait training system for locomotive syndrome

    T2 - The effect of real-time gait feature feedback on gait pattern during treadmill walking

    AU - Honda, Hiroyuki

    AU - Kobayashi, Yoshiyuki

    AU - Murai, Akihiko

    AU - Fujimoto, Hiroshi

    PY - 2019/1/1

    Y1 - 2019/1/1

    N2 - The concept of locomotive syndrome was proposed by the Japanese Orthopedic Association; it typifies the condition of reduced mobility resulting from a locomotive organ disorder related to aging. Although several sensor-based gait training systems, which can feedback the gait features in real-time, have been developed for various musculoskeletal disorders, there are no such systems for locomotive syndrome. In this study, we reported how real-time locomotive syndrome related gait feature feedback effects on gait patterns during treadmill walking. 18 healthy participants were assigned into either intervention- or control-group. During 4 sessions (training-session, pre-intervention-session, intervention-session, and post-intervention-session), gait patterns were measured by a motion-capture system. During the intervention-session of the intervention-group, participants received LS-risk-scores made in this study. Meanwhile, they were asked to minimize the LS-risk-scores by modifying their knee joint motion. A two-way-repeated measure ANOVA was conducted on the LS-risk-scores to examine effects of the intervention. When interaction was found, paired t-tests were conducted on the LS-risk-scores and knee angles between the sessions respectively. As a result, the LS-risk-scores were significantly smaller (p < 0.05) during the post-intervention-session than the pre-intervention-session in the intervention-group. There were no significant differences on the LS-risk-scores between the sessions in the control-group. Further, in the intervention-group, significant differences (p < 0.05) were found between the sessions on the knee angles partially. There were no significant differences between the sessions on the knee angles in the control-group. These results indicate that people can alter their gait pattern if the LS-risk-scores are feedback in real-time.

    AB - The concept of locomotive syndrome was proposed by the Japanese Orthopedic Association; it typifies the condition of reduced mobility resulting from a locomotive organ disorder related to aging. Although several sensor-based gait training systems, which can feedback the gait features in real-time, have been developed for various musculoskeletal disorders, there are no such systems for locomotive syndrome. In this study, we reported how real-time locomotive syndrome related gait feature feedback effects on gait patterns during treadmill walking. 18 healthy participants were assigned into either intervention- or control-group. During 4 sessions (training-session, pre-intervention-session, intervention-session, and post-intervention-session), gait patterns were measured by a motion-capture system. During the intervention-session of the intervention-group, participants received LS-risk-scores made in this study. Meanwhile, they were asked to minimize the LS-risk-scores by modifying their knee joint motion. A two-way-repeated measure ANOVA was conducted on the LS-risk-scores to examine effects of the intervention. When interaction was found, paired t-tests were conducted on the LS-risk-scores and knee angles between the sessions respectively. As a result, the LS-risk-scores were significantly smaller (p < 0.05) during the post-intervention-session than the pre-intervention-session in the intervention-group. There were no significant differences on the LS-risk-scores between the sessions in the control-group. Further, in the intervention-group, significant differences (p < 0.05) were found between the sessions on the knee angles partially. There were no significant differences between the sessions on the knee angles in the control-group. These results indicate that people can alter their gait pattern if the LS-risk-scores are feedback in real-time.

    KW - Gait training

    KW - Locomotive syndrome

    KW - Real-time visual feedback

    UR - http://www.scopus.com/inward/record.url?scp=85052004472&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=85052004472&partnerID=8YFLogxK

    U2 - 10.1007/978-3-319-96098-2_40

    DO - 10.1007/978-3-319-96098-2_40

    M3 - Conference contribution

    SN - 9783319960975

    T3 - Advances in Intelligent Systems and Computing

    SP - 305

    EP - 311

    BT - Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume I

    A2 - Bagnara, Sebastiano

    A2 - Fujita, Yushi

    A2 - Tartaglia, Riccardo

    A2 - Albolino, Sara

    A2 - Alexander, Thomas

    PB - Springer-Verlag

    ER -