The cartilage-generated bioelectric potentials induced by dynamic joint movement; an exploratory study

Abstract Background Excessive loading can damage knee cartilage, making it essential to assess and measure joint load effectively. Despite its importance, real-time monitoring of cartilage load in clinical settings remains challenging due to significant technical constraints. Electroarthrography, a...

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Main Authors: Jae-Hyun Lee, Ye-Seul Jang, Won-Du Chang
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Musculoskeletal Disorders
Subjects:
Online Access:https://doi.org/10.1186/s12891-025-08939-8
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author Jae-Hyun Lee
Ye-Seul Jang
Won-Du Chang
author_facet Jae-Hyun Lee
Ye-Seul Jang
Won-Du Chang
author_sort Jae-Hyun Lee
collection DOAJ
description Abstract Background Excessive loading can damage knee cartilage, making it essential to assess and measure joint load effectively. Despite its importance, real-time monitoring of cartilage load in clinical settings remains challenging due to significant technical constraints. Electroarthrography, a recently introduced non-invasive technique, offers a promising solution by detecting load-generated potentials in joint cartilage through surface electrodes. While previous studies have primarily focused on static load applications, such as standing weight shift task or simple isometric contraction, our study explores its potential in dynamic loading scenarios. Methods We analyzed data from 20 knees in 20 subjects, using eight surface electrodes placed around each knee to capture electrical signals during three activities: active knee extension in a seated position, passive range of motion exercise in a decubitus position, and restricted squats. The recorded signals were processed into potential-time graphs, decomposed according to movement states, and analyzed through a deep neural network. Results The results showed that cartilage-generated potentials were significantly higher during active extension compared to passive extension (1.62 mV vs. 0.87 mV; p < 0.05), with the deep neural network achieving an average classification accuracy of 98.77%. Conclusion These findings highlight the feasibility of measuring and classifying cartilage-generated potentials during dynamic physical activities, providing valuable insights into load-related differences. This approach establishes a solid foundation for applications in rehabilitation medicine by facilitating the determination of appropriate exercise intensities, assessing risks associated with daily activities, and classifying physical activities. Further studies focusing on diverse biomechanical conditions will enhance its clinical utility.
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spelling doaj-art-d258a202440445819cf34e3dda5cc83a2025-08-20T03:45:43ZengBMCBMC Musculoskeletal Disorders1471-24742025-07-0126111410.1186/s12891-025-08939-8The cartilage-generated bioelectric potentials induced by dynamic joint movement; an exploratory studyJae-Hyun Lee0Ye-Seul Jang1Won-Du Chang2Department of Artificial Intelligence Convergence, Pukyong National UniversityDepartment of System Integration Engineering, Faculty of Engineering, University of YamanashiDepartment of Artificial Intelligence Convergence, Pukyong National UniversityAbstract Background Excessive loading can damage knee cartilage, making it essential to assess and measure joint load effectively. Despite its importance, real-time monitoring of cartilage load in clinical settings remains challenging due to significant technical constraints. Electroarthrography, a recently introduced non-invasive technique, offers a promising solution by detecting load-generated potentials in joint cartilage through surface electrodes. While previous studies have primarily focused on static load applications, such as standing weight shift task or simple isometric contraction, our study explores its potential in dynamic loading scenarios. Methods We analyzed data from 20 knees in 20 subjects, using eight surface electrodes placed around each knee to capture electrical signals during three activities: active knee extension in a seated position, passive range of motion exercise in a decubitus position, and restricted squats. The recorded signals were processed into potential-time graphs, decomposed according to movement states, and analyzed through a deep neural network. Results The results showed that cartilage-generated potentials were significantly higher during active extension compared to passive extension (1.62 mV vs. 0.87 mV; p < 0.05), with the deep neural network achieving an average classification accuracy of 98.77%. Conclusion These findings highlight the feasibility of measuring and classifying cartilage-generated potentials during dynamic physical activities, providing valuable insights into load-related differences. This approach establishes a solid foundation for applications in rehabilitation medicine by facilitating the determination of appropriate exercise intensities, assessing risks associated with daily activities, and classifying physical activities. Further studies focusing on diverse biomechanical conditions will enhance its clinical utility.https://doi.org/10.1186/s12891-025-08939-8KneeCartilageBiomechanicsKinematics and kineticsRehabilitation
spellingShingle Jae-Hyun Lee
Ye-Seul Jang
Won-Du Chang
The cartilage-generated bioelectric potentials induced by dynamic joint movement; an exploratory study
BMC Musculoskeletal Disorders
Knee
Cartilage
Biomechanics
Kinematics and kinetics
Rehabilitation
title The cartilage-generated bioelectric potentials induced by dynamic joint movement; an exploratory study
title_full The cartilage-generated bioelectric potentials induced by dynamic joint movement; an exploratory study
title_fullStr The cartilage-generated bioelectric potentials induced by dynamic joint movement; an exploratory study
title_full_unstemmed The cartilage-generated bioelectric potentials induced by dynamic joint movement; an exploratory study
title_short The cartilage-generated bioelectric potentials induced by dynamic joint movement; an exploratory study
title_sort cartilage generated bioelectric potentials induced by dynamic joint movement an exploratory study
topic Knee
Cartilage
Biomechanics
Kinematics and kinetics
Rehabilitation
url https://doi.org/10.1186/s12891-025-08939-8
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