Consistency evaluation of iKcare<sup>®</sup> grading system and Brunnstrom staging on motor function of upper and lower extremities in stroke patients_West China Medical Journal

Authors：

ZHAO Kehong ^1,2 , WANG Tingting ^1,2 ,  QU Yun ^1,2

1. Department of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R. China;
2. Key Laboratory of Rehabilitation Medicine in Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R. China;

Corresponding author：

QU Yun, Email: dr_yunqu@163.com

Keywords：

Stroke; remote rehabilitation; Brunnstrom staging; rehabilitation assessment

DOI：

10.7507/1002-0179.202204114

Video：

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Objective To explore the consistency between the iKcare^® grading system and Brunnstrom staging in evaluating upper and lower limb motor function in stroke patients. Methods From May 2018 to May 2020, stroke patients who met the standards in 34 medical institutions in China were recruited. The iKcare^® grading system and Brunnstrom staging were used to evaluate the motor function of the upper and lower limbs of the subjects, respectively. The Kappa consistency test was used to evaluate the consistency between the two evaluation methods. Results A total of 340 eligible subjects were included, including 230 males and 110 females, with an average age of (61.44±12.77) years old, and an average course of disease of (62.96±42.53) days. The results showed that the Kappa evaluated for upper limb staging was 0.597 (P<0.001), and the Kappa evaluated for lower limb staging was 0.514 (P<0.001). Conclusions The evaluation results of iKcare^® grading and Brunnstrom staging have moderate consistency. The iKcare^® grading system can be used as an assessment tool for remote rehabilitation of motor function in stroke patients, but there is still room for improvement.

Citation： ZHAO Kehong, WANG Tingting, QU Yun. Consistency evaluation of iKcare^® grading system and Brunnstrom staging on motor function of upper and lower extremities in stroke patients. West China Medical Journal, 2023, 38(5): 694-697. doi: 10.7507/1002-0179.202204114 Copy

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11.	Tchero H, Tabue Teguo M, Lannuzel A, et al. Telerehabilitation for stroke survivors: systematic review and meta-analysis. J Med Internet Res, 2018, 20(10): e10867.
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21.	Lin KH, Chen CH, Chen YY, et al. Bidirectional and multi-user telerehabilitation system: clinical effect on balance, functional activity, and satisfaction in patients with chronic stroke living in long-term care facilities. Sensors (Basel), 2014, 14(7): 12451-12466.
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24.	李静, 余茜. 成都市社区脑卒中后遗症期患者跌倒情况调查及相关因素分析. 中国康复医学杂志, 2020, 35(1): 69-72.
25.	刘洪红, 都天慧, 王婷婷, 等. 远程康复设备梯度式运动功能自动评定系统在脑卒中患者中的应用. 中国医疗器械杂志, 2018, 42(2): 88-91.
26.	Lee SI, Adans-Dester CP, O’Brien AT, et al. Predicting and monitoring upper-limb rehabilitation outcomes using clinical and wearable sensor data in brain injury survivors. IEEE Trans Biomed Eng, 2021, 68(6): 1871-1881.
27.	王景丽, 李亮, 郁磊, 等. 基于遗传算法和极限学习机的 Fugl-Meyer 量表自动评估. 计算机应用, 2014, 34(3): 907-910, 914.

1. Feigin VL, Forouzanfar MH, Krishnamurthi R, et al. Global and regional burden of stroke during 1990-2010: findings from the Global Burden of Disease Study 2010. Lancet, 2014, 383(9913): 245-254.
2. Zhou M, Wang H, Zeng X, et al. Mortality, morbidity, and risk factors in China and its provinces, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet, 2019, 394(10204): 1145-1158.
3. Wang W, Jiang B, Sun H, et al. Prevalence, incidence, and mortality of stroke in china: results from a nationwide population-based survey of 480 687 adults. Circulation, 2017, 135(8): 759-771.
4. 《中国脑卒中防治报告 2018》编写组. 我国脑卒中防治仍面临巨大挑战—《中国脑卒中防治报告 2018》概要. 中国循环杂志, 2019, 34(2): 105-119.
5. Rathore SS, Hinn AR, Cooper LS, et al. Characterization of incident stroke signs and symptoms: findings from the atherosclerosis risk in communities study. Stroke, 2002, 33(11): 2718-2721.
6. Defebvre L, Krystkowiak P. Movement disorders and stroke. Rev Neurol (Paris), 2016, 172(8/9): 483-487.
7. Langhorne P, Coupar F, Pollock A. Motor recovery after stroke: a systematic review. Lancet Neurol, 2009, 8(8): 741-754.
8. 王英, 龙纳, 王凤英, 等. 脑卒中患者社区康复现状及我国实践探索. 实用医院临床杂志, 2019, 16(4): 276-279.
9. 陈颖. 脑卒中经济负担研究方法及应用进展. 预防医学, 2019, 31(6): 578-581, 585.
10. Dellifraine JL, Dansky KH. Home-based telehealth: a review and meta-analysis. J Telemed Telecare, 2008, 14(2): 62-66.
11. Tchero H, Tabue Teguo M, Lannuzel A, et al. Telerehabilitation for stroke survivors: systematic review and meta-analysis. J Med Internet Res, 2018, 20(10): e10867.
12. Cramer SC, Dodakian L, Le V, et al. Efficacy of home-based telerehabilitation vs in-clinic therapy for adults after stroke: a randomized clinical trial. JAMA Neurol, 2019, 76(9): 1079-1087.
13. Chen J, Jin W, Dong WS, et al. Effects of home-based telesupervising rehabilitation on physical function for stroke survivors with hemiplegia: a randomized controlled trial. Am J Phys Med Rehabil, 2017, 96(3): 152-160.
14. Chen J, Jin W, Zhang XX, et al. Telerehabilitation approaches for stroke patients: systematic review and meta-analysis of randomized controlled trials. J Stroke Cerebrovasc Dis, 2015, 24(12): 2660-2668.
15. 中华医学会神经病学分会, 中华医学会神经病学分会脑血管病学组. 中国脑出血诊治指南(2014). 中华神经科杂志, 2015, 48(6): 435-444.
16. 中华医学会神经病学分会, 中华医学会神经病学分会脑血管病学组. 中国急性缺血性脑卒中诊治指南 2018. 中华神经科杂志, 2018, 51(9): 666-682.
17. 孟琳, 都天慧, 范晶晶, 等. 基于微型传感器的可穿戴远程康复设备的设计. 中国医疗器械杂志, 2017, 41(3): 189-192.
18. Dong L, Wu J, Bao X. A hybrid hmm/kalman filter for tracking hip angle in gait cycle. IEICE Trans Inf Syst, 2006, 89(7): 2319-2323.
19. 王玉龙. 康复功能评定学. 北京: 人民卫生出版社, 2015: 379-382.
20. 闫岩, 华琳, 张建. 对诊断一致性 kappa 系数及评价指标的探讨. 中国卫生统计, 2007, 24(3): 313-315.
21. Lin KH, Chen CH, Chen YY, et al. Bidirectional and multi-user telerehabilitation system: clinical effect on balance, functional activity, and satisfaction in patients with chronic stroke living in long-term care facilities. Sensors (Basel), 2014, 14(7): 12451-12466.
22. Held JP, Ferrer B, Mainetti R, et al. Autonomous rehabilitation at stroke patients home for balance and gait: safety, usability and compliance of a virtual reality system. Eur J Phys Rehabil Med, 2018, 54(4): 545-553.
23. 王跃, 郁磊, 傅建明, 等. 基于极限学习机的脑卒中上肢康复 Brunnstrom 远程智能评定系统. 生物医学工程学杂志, 2014, 31(2): 251-256.
24. 李静, 余茜. 成都市社区脑卒中后遗症期患者跌倒情况调查及相关因素分析. 中国康复医学杂志, 2020, 35(1): 69-72.
25. 刘洪红, 都天慧, 王婷婷, 等. 远程康复设备梯度式运动功能自动评定系统在脑卒中患者中的应用. 中国医疗器械杂志, 2018, 42(2): 88-91.
26. Lee SI, Adans-Dester CP, O’Brien AT, et al. Predicting and monitoring upper-limb rehabilitation outcomes using clinical and wearable sensor data in brain injury survivors. IEEE Trans Biomed Eng, 2021, 68(6): 1871-1881.
27. 王景丽, 李亮, 郁磊, 等. 基于遗传算法和极限学习机的 Fugl-Meyer 量表自动评估. 计算机应用, 2014, 34(3): 907-910, 914.

West China Medical Journal

Consistency evaluation of iKcare^® grading system and Brunnstrom staging on motor function of upper and lower extremities in stroke patients

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West China Medical Journal

Consistency evaluation of iKcare® grading system and Brunnstrom staging on motor function of upper and lower extremities in stroke patients

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Consistency evaluation of iKcare^® grading system and Brunnstrom staging on motor function of upper and lower extremities in stroke patients