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ORIGINAL RESEARCH article

Front. Bioeng. Biotechnol.
Sec. Biomechanics
Volume 12 - 2024 | doi: 10.3389/fbioe.2024.1431015
This article is part of the Research Topic Assessment and Monitoring of Human Movement View all 30 articles

Multivariable Analysis for Predicting Lower Limb Muscular Strength with a Hip-Joint Exoskeleton

Provisionally accepted
Byungmun Kang Byungmun Kang 1DaeEun Kim DaeEun Kim 1*Changmin Lee Changmin Lee 2Dongwoo Kim Dongwoo Kim 3Hwang-Jae Lee Hwang-Jae Lee 3Dokwan Lee Dokwan Lee 3Hyung G. Jeon Hyung G. Jeon 4Yoonmyung Kim Yoonmyung Kim 5
  • 1 Biological Cybernetics Lab, School of Electrical and Electronic Engineering, Yonsei University, Seoul, Seoul, Republic of Korea
  • 2 Research Institute of Future City and Society, Yonsei University, Seoul, Republic of Korea
  • 3 Robot Business Team, Samsung Electronics, Samsung Electronics, Suwon, Republic of Korea
  • 4 Sports Rehabilitation lab, Department of physical education, Yonsei University, Seoul, Republic of Korea
  • 5 University College, Yonsei University International Campus, Incheon, Republic of Korea

The final, formatted version of the article will be published soon.

    We propose a novel approach to measuring muscular strength in young, healthy individuals using Bot Fit, a hip-joint exoskeleton, during resistance exercises. In this study, we introduced performance metrics to evaluate exercise performance during both short and extended durations of three resistance exercises: squats, knee-ups, and reverse lunges. These metrics, derived from the robot’s motor signals and sEMG data, include initial exercise speed, the number of repetitions, and muscle engagement. We compared these metrics against baseline muscular strength, measured using standard fitness equipment such as one-repetition maximum (1RM) and isometric contraction tests, conducted with 30 participants aged 23 to 30 years. Our results revealed that initial exercise speed and the number of repetitions were significant predictors of baseline muscular strength. Using statistical multivariable analysis, we developed a highly accurate model (R = 0.884, adj. R2 = 0.753, p-value < 0.001) and an efficient model (with all models achieving R > 0.87) with strong explanatory power. This model, focusing on a single exercise (squat) and a key performance metric (initial speed), accurately represents the muscular strength of Bot Fit users across all three exercises. This study expands the application of hip-joint exoskeleton robots, enabling efficient estimation of lower limb muscle strength through resistance exercises with Bot Fit.

    Keywords: Bot Fit, Hip-joint exoskeleton, Muscular strength, Multivariable analysis, Resistance exercise

    Received: 11 May 2024; Accepted: 10 Oct 2024.

    Copyright: © 2024 Kang, Kim, Lee, Kim, Lee, Lee, Jeon and Kim. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: DaeEun Kim, Biological Cybernetics Lab, School of Electrical and Electronic Engineering, Yonsei University, Seoul, 03722, Seoul, Republic of Korea

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.