Reliability and validity of the three-dimensional motion capture analysis system COFT-Motion<sup>?</sup> in evaluating the active range of motion of upper limbs in healthy subjects_West China Medical Journal

Authors：

CONG Yangyang , QIU Xiao , JIANG Liujun , ZHANG Anjing ,  BAI Yulong

Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai 200040, P. R. China;

Corresponding?author：

BAI Yulong, Email: dr_baiyl@fudan.edu.cn

Keywords：

Joint active range of motion; rehabilitation assessment; reliability; validity

DOI：

10.7507/1002-0179.202308051

Video：

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Objective To evaluate the reliability and validity of the three-dimensional motion capture analysis system COFT-Motion^? in evaluating the active range of motion of upper limbs in healthy subjects, and provide objective basis for its clinical application. Methods From January to March 2022, healthy subjects were publicly recruited for enrollment. The evaluator applied the three-dimensional motion capture analysis system COFT-Motion^? and angle ruler to evaluate the active range of motion of the shoulder joint (flexion, extension, adduction, abduction) and elbow joint (flexion, extension) in healthy subjects. Pearson correlation analysis was used to evaluate validity, and intraclass correlation coefficient (ICC) was used to evaluate reliability. Results There was a positive correlation between the measurements of COFT-Motion^? and the angle ruler of the active range of motion of upper limbs in healthy subjects. The Pearson correlation coefficients for active range of motion of the shoulder joint (flexion, extension, adduction, abduction) and elbow joint (flexion, extension) were 0.913, 0.964, 0.961, 0.941, 0.864, and 0.919, respectively (P<0.05). The results of using COFT-Motion^? by different evaluators to evaluate the active range of motion of healthy subjects’ shoulder joints (flexion, extension, adduction, abduction) and elbow joints (flexion, extension) showed that the ICC values were 0.892, 0.942, 0.961, 0.988, 0.989, and 0.928, respectively (P<0.05). The results of repeated evaluations by the same evaluator showed that the ICC values were 0.795, 0.916, 0.900, 0.868, 0.918, and 0.911, respectively (P<0.05). Conclusion The application of the three-dimensional motion capture analysis system COFT-Motion^? in healthy subjects has good validity and reliability. However, due to the limited sample size and subject of the study, further promotion and application of the system still need to be further explored.

Citation： CONG Yangyang, QIU Xiao, JIANG Liujun, ZHANG Anjing, BAI Yulong. Reliability and validity of the three-dimensional motion capture analysis system COFT-Motion^? in evaluating the active range of motion of upper limbs in healthy subjects. West China Medical Journal, 2023, 38(10): 1517-1521. doi: 10.7507/1002-0179.202308051 Copy

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1. Felipe FA, de Carvalho FO, Silva éR, et al. Evaluation instruments for physical therapy using virtual reality in stroke patients: a systematic review. Physiotherapy, 2020, 106: 194-210.
2. 張文波, 瞿暢, 周建萍, 等. 基于 Azure Kinect 骨骼追蹤的腕關節活動度測量方法. 中國康復理論與實踐, 2022, 28(8): 981-988.
3. 柯技, 單良, 王樹法, 等. 脛骨平臺骨折傷殘鑒定的回顧性研究. 中國刑警學院學報, 2020(2): 114-118.
4. Brosseau L, Tousignant M, Budd J, et al. Intratester and intertester reliability and criterion validity of the parallelogram and universal goniometers for active knee flexion in healthy subjects. Physiother Res Int, 1997, 2(3): 150-166.
5. Leightley D, McPhee JS, Yap MH. Automated analysis and quantification of human mobility using a depth sensor. IEEE J Biomed Health Inform, 2017, 21(4): 939-948.
6. Ballesteros J, Urdiales C, Martinez AB, et al. Automatic assessment of a rollator-user’s condition during rehabilitation using the i-walker platform. IEEE Trans Neural Syst Rehabil Eng, 2017, 25(11): 2009-2017.
7. Delrobaei M, Baktash N, Gilmore G, et al. Using wearable technology to generate objective parkinson's disease dyskinesia severity score: possibilities for home monitoring. IEEE Trans Neural Syst Rehabil Eng, 2017, 25(10): 1853-1863.
8. Motiian S, Pergami P, Guffey K, et al. Automated extraction and validation of children's gait parameters with the Kinect. Biomed Eng Online, 2015, 14: 112.
9. Albert JA, Owolabi V, Gebel A, et al. Evaluation of the pose tracking performance of the azure kinect and kinect v2 for gait analysis in comparison with a gold standard: a pilot study. Sensors (Basel), 2020, 20(18): 5104.
10. da Cunha Neto JS, Rebou?as Filho PP, Silva G, et al. Dynamic evaluation and treatment of the movement amplitude using Kinect sensor. IEEE Access, 2018(99): 1.
11. 李培豐, 林愉添, 朱君毅, 等. 一種新的智能手機應用程序 AR 尺子測量腕關節活動度的可靠性和同時效度評估. 中華手外科雜志, 2020, 36(6): 425-429.
12. Kennedy DL, Kemp HI, Ridout D, et al. Reliability of conditioned pain modulation: a systematic review. Pain, 2016, 157(11): 2410-2419.
13. van Trijffel E, van de Pol RJ, Oostendorp RA, et al. Inter-rater reliability for measurement of passive physiological movements in lower extremity joints is generally low: a systematic review. J Physiother, 2010, 56(4): 223-235.
14. van de Pol RJ, van Trijffel E, Lucas C. Inter-rater reliability for measurement of passive physiological range of motion of upper extremity joints is better if instruments are used: a systematic review. J Physiother, 2010, 56(1): 7-17.
15. Gajdosik RL. Comparison and reliability of three goniometric methods for measuring forearm supination and pronation. Percept Mot Skills, 2001, 93(2): 353-355.
16. 陶莉, 戴昂, 郭險峰. 多功能脊柱穩定性康復系統評估模塊對于軀干肌力評估的效度和信度研究. 中國康復醫學雜志, 2020, 35(10): 1217-1220.
17. de Sire A, Losco L, Cigna E, et al. Three-dimensional laser scanning as a reliable and reproducible diagnostic tool in breast cancer related lymphedema rehabilitation: a proof-of-principle study. Eur Rev Med Pharmacol Sci, 2020, 24(8): 4476-4485.
18. Lee WW, Yen SC, Tay A, et al. A smartphone-centric system for the range of motion assessment in stroke patients. IEEE J Biomed Health Inform, 2014, 18(6): 1839-1847.
19. 王杰. 關節活動度評定系統的設計與實現. 保定: 河北大學, 2017: 68.
20. 王偉偉, 郭遠其, 高卉, 等. 基于深度圖像的關節活動度測量及其結果評價. 中國醫學物理學雜志, 2016, 33(3): 262-269.
21. 瞿暢, 丁晨, 王君澤, 等. 基于 Kinect 體感交互技術的上肢關節活動度測量方法. 中國生物醫學工程學報, 2014, 33(1): 16-21.
22. 張艷, 徐瑞璟, 李卓穎. 基于 3D 建模指關節活動度測量的研發及應用. 循證護理, 2023, 9(12): 2278-2280.
23. 嚴廣斌. 關節活動度(Range of motion, ROM). 中華關節外科雜志(電子版), 2014(3): 409.
24. Wagner ER, Conti Mica M, Shin AY. Smartphone photography utilized to measure wrist range of motion. J Hand Surg Eur Vol, 2018, 43(2): 187-192.
25. Kurillo G, Han JJ, Obdr?álek S, et al. Upper extremity reachable workspace evaluation with Kinect. Stud Health Technol Inform, 2013, 184: 247-253.

West China Medical Journal

Reliability and validity of the three-dimensional motion capture analysis system COFT-Motion^? in evaluating the active range of motion of upper limbs in healthy subjects

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West China Medical Journal

Reliability and validity of the three-dimensional motion capture analysis system COFT-Motion? in evaluating the active range of motion of upper limbs in healthy subjects

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Reliability and validity of the three-dimensional motion capture analysis system COFT-Motion^? in evaluating the active range of motion of upper limbs in healthy subjects