IMU-Based Bilateral Kinematic Waveform Analysis Associated with Shoulder Pain History in Competitive Swimmers.
- 1Bioengineering Department, University of the Pacific, 3601 Pacific Ave, Stockton, CA 95211, USA.
Abstract
Shoulder injuries are one of the most common overuse problems in competitive swimming, yet objective, field-deployable methods for quantifying pain-related movement alterations remain limited. This study investigates whether bilateral IMU sensors placed on the upper humerus can identify kinematic bilateral waveform similarities tied to a history of shoulder pain in swimmers. In this study, thirty-four NCAA Division 1 collegiate swimmers and water polo players completed a standardized swimming test and were classified into moderate/severe pain (n = 22) and none/mild pain (n = 12) groups based on self-reported shoulder pain scores. Kinematic features were extracted and evaluated using statistical tests and machine learning classification. The none/mild pain group showed a higher peak left-right shoulder cross-correlation across all axes (0.85 vs. 0.78, p = 0.002). The best-performing model Classification accuracy for distinguishing between moderate/severe pain and none/mild pain conditions achieved a balanced accuracy of 70.6% (24/34 participants), with a balanced accuracy of 69.7% (95% CI [52.7-85.2%]) and an ROC AUC of 0.731 (95% CI [0.557-0.890]), suggesting that personalized machine learning approaches may be necessary to improve individual-level classification performance. Further investigation of intra-subject associations between shoulder pain history and kinematic bilateral waveform similarities is warranted to better understand their relationship and determine potential causal mechanisms.
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BibTeX
@article{gronbach2026imubased,
title = {{IMU-Based Bilateral Kinematic Waveform Analysis Associated with Shoulder Pain History in Competitive Swimmers.}},
author = {Ben Gronbach and Kyle Capili and Seyedeh Fatemeh Khatami Firoozabadi},
journal = {Sensors (Basel, Switzerland)},
year = {2026},
month = oct,
doi = {10.3390/s26206565},
url = {https://europepmc.org/article/MED/42944428},
note = {CC BY},
}
RIS
TY - JOUR
TI - IMU-Based Bilateral Kinematic Waveform Analysis Associated with Shoulder Pain History in Competitive Swimmers.
AU - Ben Gronbach
AU - Kyle Capili
AU - Seyedeh Fatemeh Khatami Firoozabadi
PY - 2026
DA - 2026/10/16
JO - Sensors (Basel, Switzerland)
DO - 10.3390/s26206565
UR - https://europepmc.org/article/MED/42944428
AB - Shoulder injuries are one of the most common overuse problems in competitive swimming, yet objective, field-deployable methods for quantifying pain-related movement alterations remain limited. This study investigates whether bilateral IMU sensors placed on the upper humerus can identify kinematic bilateral waveform similarities tied to a history of shoulder pain in swimmers. In this study, thirty-four NCAA Division 1 collegiate swimmers and water polo players completed a standardized swimming test and were classified into moderate/severe pain (n = 22) and none/mild pain (n = 12) groups based on self-reported shoulder pain scores. Kinematic features were extracted and evaluated using statistical tests and machine learning classification. The none/mild pain group showed a higher peak left-right shoulder cross-correlation across all axes (0.85 vs. 0.78, p = 0.002). The best-performing model Classification accuracy for distinguishing between moderate/severe pain and none/mild pain conditions achieved a balanced accuracy of 70.6% (24/34 participants), with a balanced accuracy of 69.7% (95% CI [52.7-85.2%]) and an ROC AUC of 0.731 (95% CI [0.557-0.890]), suggesting that personalized machine learning approaches may be necessary to improve individual-level classification performance. Further investigation of intra-subject associations between shoulder pain history and kinematic bilateral waveform similarities is warranted to better understand their relationship and determine potential causal mechanisms.
SN - 1424-8220
ER -