Bot fit: A novel approach to assessing lower limb muscular strength

This study introduces Bot Fit, an innovative hip-joint exoskeleton designed for the objective assessment of lower limb muscular strength and exercise performance. A total of 25 participants underwent baseline strength assessments using conventional fitness equipment before performing resistance exercises under two controlled conditions: a 10-second test without speed restrictions and a 30-second test at a constant speed. Bot Fit recorded motor signals and performance metrics, capturing key indicators such as repetitions and movement patterns. To analyze the relationship between muscle parameters and exercise performance, we employed correlation analysis, hierarchical cluster analysis (HCA), and regression analysis. The results demonstrated strong associations between lower limb strength and key exercises, including squats, knee-ups, and reverse lunges, particularly in short-duration and constant-speed conditions. HCA successfully clustered participants based on three exercise-related metrics with an accuracy of 0.89, while the regression model achieved a correlation coefficient of 0.86, indicating high statistical power. These findings suggest that Bot Fit provides a reliable, data-driven method for muscular strength assessment, offering valuable insights for optimizing exercise programs, preventing injuries, and enhancing physical performance. The integration of wearable robotic technology into health and fitness monitoring enables personalized exercise interventions and supports evidence-based decision-making in sports science, rehabilitation, and performance enhancement.

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Publication Details

Journal
PLoS ONE
Published
2026-03-26
DOI
https://doi.org/10.1371/journal.pone.0339187
Primary Topic
Prosthetics and Rehabilitation Robotics
Type
article
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article

Bot fit: A novel approach to assessing lower limb muscular strength

Byungmun Kang, YoonMyung Kim, Kyunghwan Jung, Hyung-Gyu Jeon et al.
PLoS ONE
Prosthetics and Rehabilitation Robotics
article

Bot fit: A novel approach to assessing lower limb muscular strength

Byungmun Kang, YoonMyung Kim, Kyunghwan Jung, Hyung-Gyu Jeon, Hwang-Jae Lee, DaeEun Kim, Dongwoo Kim, Changmin Lee, Dokwan Lee
article en

Abstract

This study introduces Bot Fit, an innovative hip-joint exoskeleton designed for the objective assessment of lower limb muscular strength and exercise performance. A total of 25 participants underwent baseline strength assessments using conventional fitness equipment before performing resistance exercises under two controlled conditions: a 10-second test without speed restrictions and a 30-second test at a constant speed. Bot Fit recorded motor signals and performance metrics, capturing key indicators such as repetitions and movement patterns. To analyze the relationship between muscle parameters and exercise performance, we employed correlation analysis, hierarchical cluster analysis (HCA), and regression analysis. The results demonstrated strong associations between lower limb strength and key exercises, including squats, knee-ups, and reverse lunges, particularly in short-duration and constant-speed conditions. HCA successfully clustered participants based on three exercise-related metrics with an accuracy of 0.89, while the regression model achieved a correlation coefficient of 0.86, indicating high statistical power. These findings suggest that Bot Fit provides a reliable, data-driven method for muscular strength assessment, offering valuable insights for optimizing exercise programs, preventing injuries, and enhancing physical performance. The integration of wearable robotic technology into health and fitness monitoring enables personalized exercise interventions and supports evidence-based decision-making in sports science, rehabilitation, and performance enhancement.

PLoS ONEVol. 21(3)
Yonsei University (KR), Samsung (South Korea) (KR), Soonchunhyang University (KR)
Peace, Justice and strong institutions
Openalex Percentile: Top 8%
Prosthetics and Rehabilitation Robotics
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Bot fit: A novel approach to assessing lower limb muscular strength — Byungmun Kang, YoonMyung Kim, et al. · PLoS ONE (2026) | TGRS Research Map | TGRS