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1- Department of Physical Therapy, Faculty of Allied Health Sciences, Thammasat University, Pathum Thani, Thailand.
2- Department of Physical Therapy, Faculty of Allied Health Sciences, Thammasat University, Pathum Thani, Thailand. , teerapat.l@allied.tu.ac.th
Abstract:   (395 Views)
Background. Movement assessment is vital in physical therapy for injury prevention. Although 3D motion capture provides precise measurements, its high cost and complexity limit practical application. Inertial measurement units (IMUs) present a more feasible alternative; however, their reliability in complex movements, such as the countermovement jump (CMJ), remains underexplored.
Objectives. To assess the reliability and concurrent validity of IMUs in measuring maximum lower limb angles during CMJs compared to 3D motion analysis.
Methods. An observational cross-sectional design was employed with 36 participants (18 males, 18 females; mean age 23.25 years). Participants performed CMJs while fitted with reflective markers for 3D analysis and IMUs. Peak joint angles were measured in the sagittal, frontal, and transverse planes. Reliability was assessed using intraclass correlation coefficients (ICCs), and concurrent validity was determined through Pearson correlation coefficients.
Results. Results indicated moderate to excellent reliability for joint angle measurements, with ICCs ranging from 0.51 to 0.95 across planes. Concurrent validity demonstrated moderate to high correlations, particularly in the sagittal (hip: r=0.74, knee: r=0.73) and frontal planes (ankle: r=0.94). However, lower correlations were noted in the transverse plane for the ankle (r=0.40).
Conclusion. These findings suggested that while IMUs were effective for assessing joint angles during CMJs, caution was warranted when interpreting transverse plane data, particularly for the ankle. This study underscored the potential of IMUs as a practical alternative to 3D motion analysis in clinical and athletic settings
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APPLICABLE REMARKS
  • IMUs were reliable for measuring joint angles in the sagittal and frontal planes, particularly for the knee, but showed limitations in the transverse plane, especially for ankle movements.
  • Accurate sensor placement and secure attachment were essential for improving IMU measurement precision, especially during high-speed movements.
  • IMUs offer practical advantages for field applications due to their portability and real-time data capabilities, making them valuable for dynamic movement analysis in sports and clinical settings.

Type of Study: Original Article | Subject: Sport Biomechanics and its related branches
Received: 2024/09/29 | Accepted: 2024/12/11

References
1. 1. Al-Amri M, Nicholas K, Button K, Sparkes V, Sheeran L, Davies JL. Inertial Measurement Units for Clinical Movement Analysis: Reliability and Concurrent Validity. Sensors (Basel). 2018;18(3). Epub 20180228. [DOI:10.3390/s18030719] [PMID] []
2. Cook CJ, Kilduff LP, Crewther BT, Beaven M, West DJ. Morning based strength training improves afternoon physical performance in rugby :union: players. J Sci Med Sport. 2014;17(3):317-21. Epub 20130523. [DOI:10.1016/j.jsams.2013.04.016] [PMID]
3. Baek SY, Ajdaroski M, Shahshahani PM, Beaulieu ML, Esquivel AO, Ashton-Miller JA. A Comparison of Inertial Measurement Unit and Motion Capture Measurements of Tibiofemoral Kinematics during Simulated Pivot Landings. Sensors (Basel). 2022;22(12). Epub 20220611. [DOI:10.3390/s22124433] [PMID] []
4. Dahl KD, Dunford KM, Wilson SA, Turnbull TL, Tashman S. Wearable sensor validation of sports-related movements for the lower extremity and trunk. Med Eng Phys. 2020;84:144-50. Epub 20200805. [DOI:10.1016/j.medengphy.2020.08.001] [PMID]
5. Prasanth H, Caban M, Keller U, Courtine G, Ijspeert A, Vallery H, et al. Wearable Sensor-Based Real-Time Gait Detection: A Systematic Review. Sensors (Basel). 2021;21(8). Epub 20210413. [DOI:10.3390/s21082727] [PMID] []
6. Shuai Z, Dong A, Liu H, Cui Y. Reliability and Validity of an Inertial Measurement System to Quantify Lower Extremity Joint Angle in Functional Movements. Sensors (Basel). 2022;22(3). Epub 20220123. [DOI:10.3390/s22030863] [PMID] []
7. Cho YS, Jang SH, Cho JS, Kim MJ, Lee HD, Lee SY, et al. Evaluation of Validity and Reliability of Inertial Measurement Unit-Based Gait Analysis Systems. Ann Rehabil Med. 2018;42(6):872-83. Epub 20181228. [DOI:10.5535/arm.2018.42.6.872] [PMID] []
8. Teufl W, Miezal M, Taetz B, Frohlich M, Bleser G. Validity of inertial sensor based 3D joint kinematics of static and dynamic sport and physiotherapy specific movements. PLoS One. 2019;14(2):e0213064. Epub 20190228. [DOI:10.1371/journal.pone.0213064] [PMID] []
9. Struzik A, Konieczny G, Stawarz M, Grzesik K, Winiarski S, Rokita A. Relationship between Lower Limb Angular Kinematic Variables and the Effectiveness of Sprinting during the Acceleration Phase. Appl Bionics Biomech. 2016;2016:7480709. Epub 20160719. [DOI:10.1155/2016/7480709] [PMID] []
10. Radcliffe JC, Farentinos RC. High-powered plyometrics: Human Kinetics; 1999.
11. Sole CJ, Mizuguchi S, Sato K, Moir GL, Stone MH. Phase Characteristics of the Countermovement Jump Force-Time Curve: A Comparison of Athletes by Jumping Ability. The Journal of Strength & Conditioning Research. 2018;32(4):1155-65. [DOI:10.1519/JSC.0000000000001945] [PMID]
12. Kobsar D, Charlton JM, Tse CTF, Esculier JF, Graffos A, Krowchuk NM, et al. Validity and reliability of wearable inertial sensors in healthy adult walking: a systematic review and meta-analysis. J Neuroeng Rehabil. 2020;17(1):62. Epub 20200511. [DOI:10.1186/s12984-020-00685-3] [PMID] []
13. Romijnders R, Warmerdam E, Hansen C, Welzel J, Schmidt G, Maetzler W. Validation of IMU-based gait event detection during curved walking and turning in older adults and Parkinson's Disease patients. J Neuroeng Rehabil. 2021;18(1):28. Epub 20210206. [DOI:10.1186/s12984-021-00828-0] [PMID] []
14. Portney LG, Watkins MP. Foundation of clinical research: Application to practice. 3 ed. London: Pearson/Prentice Hall; 2009.
15. Cohen J. Statistical power analysis for the behavioral sciences. 2 ed: Lawrence Erlbaum Associates; 1988.
16. Markovic G, Mikulic P, Drenjanac M. Biomechanical differences between vertical jump tests. Kinesiology. 2004;36(2):139-45.
17. Winter DA. Biomechanics and motor control of human movement 4ed: John Wiley & Sons; 2009. [DOI:10.1002/9780470549148]
18. Weir JP. Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. J Strength Cond Res. 2005;19(1):231-40. https://doi.org/10.1519/00124278-200502000-00038 [DOI:10.1519/15184.1] [PMID]
19. Hopkins WG. Measures of reliability in sports medicine and science. Sports Med. 2000;30(1):1-15. [DOI:10.2165/00007256-200030010-00001] [PMID]
20. Mukaka MM. Statistics corner: A guide to appropriate use of correlation coefficient in medical research. Malawi Med J. 2012;24(3):69-71.
21. Hall SJ. Basic Biomechanics. 6 ed. NewYork: McGraw Hill; 2012.
22. Warner MB, Chappell PH, Stokes MJ. Measurement of dynamic scapular kinematics using an acromion marker cluster to minimize skin movement artifact. J Vis Exp. 2015(96):e51717. Epub 20150210. [DOI:10.3791/51717-v] [PMID] []

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