Analysis of Indoor Rowing Motion using Wearable Inertial Sensors

S. Bosch, M. Shoaib, Stephen Geerlings, Lennart Buit, Nirvana Meratnia, Paul J.M. Havinga

    Research output: Contribution to journalArticleAcademicpeer-review

    3 Citations (Scopus)
    147 Downloads (Pure)

    Abstract

    In this exploratory work the motion of rowers is analyzed while rowing on a rowing machine. This is performed using inertial sensors that measure the orientation at several positions on the body. Using these measurements, this work provides a preliminary analysis of the differences between experienced and novice rowers, or between a good and a bad technique. The analysis shows that the measured postural angles show no clear trend that would set apart experienced and novice rowers or a bad and a good technique. However, there are clear differences in absolute postural angle’s consistency and timing consistency of strokes between novice and experienced rowers. We also applied a machine learning technique to the data to find the similarities between different rowers and an experienced reference rower. The results can be used to compare the quality of the rowing technique with respect to a reference. In this paper, we present our initial results as well as the challenges that need to be further explored.
    Original languageEnglish
    Article numbere1
    Number of pages7
    JournalEAI Endorsed Transactions on Internet of Things
    Volume2
    Issue number6
    DOIs
    Publication statusPublished - 14 Dec 2015
    Event10th EAI International Conference on Body Area Networks 2015 - Menzies Hotel Sydney, Sydney, Australia
    Duration: 28 Sep 201530 Sep 2015
    Conference number: 10
    http://archive.bodynets.org/2015/show/home

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    Exercise equipment
    Learning systems
    Sensors

    Keywords

    • EWI-26606
    • METIS-315112
    • IR-99021

    Cite this

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    title = "Analysis of Indoor Rowing Motion using Wearable Inertial Sensors",
    abstract = "In this exploratory work the motion of rowers is analyzed while rowing on a rowing machine. This is performed using inertial sensors that measure the orientation at several positions on the body. Using these measurements, this work provides a preliminary analysis of the differences between experienced and novice rowers, or between a good and a bad technique. The analysis shows that the measured postural angles show no clear trend that would set apart experienced and novice rowers or a bad and a good technique. However, there are clear differences in absolute postural angle’s consistency and timing consistency of strokes between novice and experienced rowers. We also applied a machine learning technique to the data to find the similarities between different rowers and an experienced reference rower. The results can be used to compare the quality of the rowing technique with respect to a reference. In this paper, we present our initial results as well as the challenges that need to be further explored.",
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    Analysis of Indoor Rowing Motion using Wearable Inertial Sensors. / Bosch, S.; Shoaib, M.; Geerlings, Stephen; Buit, Lennart; Meratnia, Nirvana; Havinga, Paul J.M.

    In: EAI Endorsed Transactions on Internet of Things, Vol. 2, No. 6, e1, 14.12.2015.

    Research output: Contribution to journalArticleAcademicpeer-review

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    AU - Bosch, S.

    AU - Shoaib, M.

    AU - Geerlings, Stephen

    AU - Buit, Lennart

    AU - Meratnia, Nirvana

    AU - Havinga, Paul J.M.

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