以质量求发展，以服务铸品牌

Journal of Nursing ›› 2024, Vol. 31 ›› Issue (24): 44-50.doi: 10.16460/j.issn1008-9969.2024.24.044

Previous Articles     Next Articles

Application effect of sensor technology-based intelligent devices in gait rehabilitation of stroke patients: a Meta-analysis

ZHOU Chun-xiang1, RAO Yuan2, CUI Meng-jiao3, SHANG Zhi-ying4, ZHANG Tian-lan5, QIU Xi-chenhui6, QIN Yan-ping1   

  1. 1. Dept. of Neurological Surgery, Lishui District People's Hospital, Nanjing 211200, China;
    2. Female Drug Rehab Center of Hunan Province, Changsha 410208, China;
    3. Dept. of Emergency, Nanjing Drum Tower Hospital, Nanjing 210000, China;
    4. School of Nursing, Nanjing Medical University, Nanjing 211266, China;
    5. Drum Tower Clinical Medical College Affiliated to Jiangsu University, Nanjing 210000, China;
    6. School of Nursing, Shenzhen University Medical School, Shenzhen 518055, China
  • Received:2024-08-04 Online:2024-12-25 Published:2025-01-09

PDF (PC)

19

Like

Abstract: Objective To evaluate the intervention effect of sensor technology-based intelligent devices on gait rehabilitation in stroke patients, and to provide evidence for clinical nursing of stroke patients. Methods Randomized controlled trials (RCTs) on sensor technology-based intelligent devices for gait rehabilitation in stroke patients were retrieved from CNKI, VIP, Wanfang, PubMed, Web of Science, CINAHL, Cochrane Library, and Embase and the retrieval time spanned from the inception to August 2024. After deduplication using Endnote software, two researchers with evidence-based nursing training screened the literature, extracted the data, and assessed the risk of bias in included studies independently. Statistical analysis was conducted using RevMan 5.4 software. Results A total of 10 original studies were included, with 329 stroke patients. Meta-analysis Results showed that sensor technology was conducive to gait rehabilitation of stroke patients, and could improve patients' balance control ability[SMD=0.74, 95%CI（0.23, 1.25）, P<0.05], walking ability[SMD=0.67, 95%CI（0.26, 1.09）, P<0.05], gait function [SMD=0.47, 95%CI (0.15, 0.79), P<0.05]. However, there was no significant difference in the impact on walking rate [SMD=1.13, 95%CI (-0.31, 2.57), P=0.12]. Conclusion Sensor technology facilitates gait rehabilitation in stroke patients, including balance control, walking ability, and gait function. However, the impact on gait speed remains unclear, requiring further high-quality research to verify the conclusion.

Key words: sensor, stroke, rehabilitation, nursing, Meta-analysis

CLC Number: 

  • R473.74
[1] Johnson CO, Nguyen M, Roth GA,et al.Global, regional, and national burden of stroke, 1990-2016: a systematic analysis for the Global Burden of disease study 2016[J].Lancet Neurol,2019,18(5).439-458.DOI:10.1016/S1474-4422(19)30034-1.
[2] Mehrholz J, Thomas S, Elsner B.Treadmill training and body weight support for walking after stroke[J].Cochrane Database Syst,2017, 8(8):CD002840.DOI:10.1002/14651858.CD002840.pub4.
[3] Van Criekinge T, Heremans C, Burridge J, et al.Standardized measurement of balance and mobility post-stroke: consensus-based core recommendations from the third Stroke Recovery and Rehabilitation Roundtable[J]. Neurorehabil Neural Repair,2024,38(1):41-51. DOI:10.1177/15459683231209154.
[4] Pournajaf S, Goffredo M, Agosti M,et al.Italian study group on implementation of stroke care (ISC Study). Community ambulation of stroke survivors at 6 months follow-up: an observational study on sociodemographic and sub-acute clinical indicators[J]. Eur J Phys Rehabil Med, 2019,55(4):433-441. DOI:10.23736/S1973-9087.18.05489-8.
[5] Huang X, Xue Y, Ren S, et al.Sensor-based wearable systems for monitoring humanmotion and posture: a review[J]. Sensors (Basel),2023 ,23(22):9047. DOI:10.3390/s23229047.
[6] Peters DM, O'Brien ES, Kamrud KE, et al. Utilization of wearable technology to assess gait and mobility post-stroke: a systematic review[J]. J Neuroeng Rehabil,2021,18(1):67. DOI: 10.1186/s12984-021-00863-x.
[7] 胡雁. 循证护理学[M].北京:人民卫生出版社,2012:112.
[8] Wright A, Stone K, Martinelli L,et al.Effect of combined home-based, overground robotic-assisted gait training and usual physiotherapy on clinical functional outcomes in people with chronic stroke: a randomized controlled trial[J]. Clin Rehabil, 2021,35(6):882-893. DOI:10.1177/0269215520984133.
[9] Yoo D, Son Y, Kim D, et al.Technology-assisted ankle rehabilitation improves balance and gait performance in stroke survivors: a randomized controlled study with 1-month follow-up[J]. IEEE Trans Neural Syst Rehabil Eng, 2018,26(12):2315-2323.DOI:10.1109/TNSRE.2018.2879783.
[10] Yoo D, Kim DH, Seo KH, et al.The effects of technology-assisted ankle rehabilitation on balance control in stroke survivors[J]. IEEE Trans Neural Syst Rehabil Eng, 2019,27(9):1817-1823.DOI:10.1109/TNSRE.2019.2934930.
[11] Ghedira M, Albertsen, IM, Mardale V, et al. Wireless, accelerometry-triggered functional electrical stimulation of the peroneal nerve in spastic paresis: a randomized, controlled pilot study[J]. Assist Technol, 2017,29(2):99-105.DOI:10.1080/10400435.2016.1214933.
[12] Ribeiro TS,Silva E,Silva I, et al.Effects of treadmill training with load addition on non-paretic lower limb on gait parameters after stroke: a randomized controlled clinical trial[J]. Gait Posture, 2017(54):229-235. DOI:10.1016/j.gaitpost.2017.03.00.
[13] Ribeiro TS, Gomesde S, Regalado I,et al.Effects of load addition during gait training on weight-bearing and temporal asymmetry after stroke: a randomized clinical trial[J]. Am J Phys Med Rehabil, 2020, 99(3):250-256.DOI:10.1097/PHM.0000000000001314.
[14] Zhang H, Li X, Gong Y, et al.Three-dimensional gait analysis and semg measures for robotic-assisted gait training in subacute stroke: a randomized controlled trial[J]. Biomed Res Int, 2023(2023):7563802. DOI:10.1155/2023/7563802.
[15] 蒋祎萌,董静.下肢康复机器人训练在急性脑卒中患者康复治疗中的应用效果[J]. 养生大世界,2021(6):197.
[16] Lee YH, Ko LW, Hsu CY, et al.Therapeutic effects of robotic-exoskeleton-assisted gait rehabilitation and predictive factors of significant improvements in stroke patients: a randomized controlled trial[J].Bioengineering(Basel), 2023,10(5):585.DOI:10.3390/bioengineering10050585.
[17] Zhang Y, Zhao W, Wan C, et al.Exoskeleton rehabilitation robot training for balance and lower limb function in sub-acute stroke patients: a pilot, randomized controlled trial. J Neuroeng Rehabil[J]. 2024,21(1):98.DOI:10.1186/s12984-024-01391-0.
[18] Beyaert C, Vasa R, Frykberg GE.Gait post-stroke: Pathophysiology and rehabilitation strategies[J].Neurophysiol Clin,2015,45(4-5):335-355.DOI:10.1016/j.neucli.2015.09.005.
[19] Liang M,Wei Z,Xie R,et al.A Meta-analysis of the effectiveness of virtual reality training for improving balance and walking after a stroke[J]. Chin J Phys Med Rehabil,2020,42(7):632-639.DOI:10.2196/31051.
[20] Tao Q, Liu S, Zhang J,et al.Clinical applications of smart wearable sensors[J]. iScience,2023 ,26(9):107485. DOI:10.1016/j.isci.2023.107485.
[21] Kim WS,Cho S,Ku J,et al.Clinical application of virtual reality for upper limb motor rehabilitation in stroke: review of technologies and clinical evidence[J]. J Clin Med,2020,9(10):3369.DOI:10.3390/jcm9103369.
[22] Jakob I, Kollreider A, Germanotta M,et al.Robotic and sensor technology for upper limb rehabilitation[J].PM R, 2018,10(9 Suppl 2):S189-S197. DOI:10.1016/j.pmrj.2018.07.011.
[23] 周雯露,余姜璇,王俊杰,等.完全沉浸式虚拟现实技术对脑卒中患者肢体功能影响的Meta分析[J].中华护理杂志,2023, 58(17):2158-2165. DOI:10.3761/j.issn.0254-1769.2023.17.015.
[24] Einstad MS, Saltvedt I, Lydersen S,et al.Associations between post-stroke motor and cognitive function: a cross-sectional study[J]. BMC Geriatr,2021,21(1):103. DOI:10.1186/s12877-021-02055-7.
[25] Liang S, Hong ZQ,Cai Q,et al.Effects of robot-assisted gait training on motor performance of lower limb in poststroke survivors: a systematic review with Meta-analysis[J]. Eur Rev Med Pharmacol Sci,2024, 28(3):879-898.DOI:10.26355/eurrev_202402_35325.
[26] Bernhardt J,Godecke E,Johnson L,et al.Early rehabilitation after stroke[J].Curr Opin Neurol,2017,30(1):48-54.DOI:10.1097/WCO.0000000000000404.
[27] Zhang BH,Li D,Liu Y, et al.Virtual reality for limb motor function,balance,gait,cognition and daily function of stroke patients:a systematic review and Meta-analysis[J]. J Adv Nurs,2021,77(8):3255-3273.DOI:10.1111/jan.14800.
[28] Koch G,Bonnì S,Casula EP,et al.Effect of cerebellar stimulation on gait and balance recovery in patients with hemiparetic stroke:a randomized clinical trial[J]. JAMA Neurol,2019,76(2):170-178.DOI:10.1001/jamaneurol.2018.3639.
[29] Leddy JJ,Cox JL,Baker JG,et al.Exercise treatment for post concussion syndrome:a pilot study of changes in functional magnetic resonance imaging activation, physiology, and symptoms[J].J Head Trauma Rehabil,2013,28(4):241-249.DOI:10.1097/HTR.0b013e31826da964.
[30] Gordt K, Gerhardy T, Najafi B, et al.Effects of wearable sensor-based balance and gait training on balance, gait, and functional performance in healthy and patient populations: a systematic review and Meta-analysis of randomized controlled trials[J]. Gerontology,2018,64(1):74-89. DOI:10.1159/000481454.
[31] Rose DK,Nadeau SE,Wu SS,et al.Locomotor training and strength and balance exercises for walking recovery after stroke: response to number of training sessions[J]. Phys Ther,2017,97(11):1066-1074.DOI:10.1093/ptj/pzx079.
[32] Cho KH, Park SJ.Effects of joint mobilization and stretching on the range of motion for ankle joint and spatiotemporal gait variables in stroke patients[J]. J Stroke Cerebrovasc Dis,2020, 29(8):104933.DOI:10.1016/j.jstrokecerebrovasdis.2020.104933.
[1] LIU Lu, ZHU Yu, CAO Yi, ZHANG Hua, PENG Yu-na. Effect of target temperature management strategy on intraoperative temperature management in patients undergoing hyperthermic intraperitoneal chemotherapy [J]. Journal of Nursing, 2025, 32(4): 59-63.
[2] GONG Zu-hua, SUN Li, TAN Xuan, ZHANG Yue, SHI Dan, CHENG Juan-juan. Effect of basic sign collection-comparison-recognition model for occult change after hepatobiliary surgery [J]. Journal of Nursing, 2025, 32(4): 74-78.
[3] LI Miao-miao, XIONG Li-juan, QI Lei, LI Min, XIANG Yu-ting. Application of diagnosis-related group based on Ridit analysis and rank sum ratio method in nursing performance management [J]. Journal of Nursing, 2025, 32(3): 22-26.
[4] CHEN En-lin, MO Feng-ling, ZHUANG Ze-ming, ZHANG Ming-zhe, ZHOU Jia-kun, HUANG Li-fang, JI Long-fei, ZHANG Li-fang. Assessment tools for unilateral spatial neglect after stroke: a scoping review [J]. Journal of Nursing, 2025, 32(3): 43-49.
[5] LI Ruo-Yu, LIU Xin, LIN Ping, CHEN Dan, LIN Hua. Best evidence summary for medication safety management for discharged patients [J]. Journal of Nursing, 2025, 32(3): 50-55.
[6] YANG Xiao-juan, MAO Xiao-rong, WANG Jing, JIANG Hua, LI Rong, FAN Yu, WEN Qing, LI Lin-zhang, CHEN Xiao-rong. Best evidence summary for early enteral nutrition management in adults with severe burns [J]. Journal of Nursing, 2025, 32(3): 56-61.
[7] ZHU Tian-shun, ZHU Ke-ke, XUE Hui-yuan, JIAO Cong-cong, WEI Chang-hui, WANG He. Application of message framing theory in health management: a scoping review [J]. Journal of Nursing, 2025, 32(2): 44-49.
[8] LIU Shuo-yi, XIONG Li-juan, LI Ling, WANG Yu-mei, HE Jia, LI Xin, YUAN Shi-lei, GUO Xue-qin, WANG Yang-jing, ZHANG Hui-juan. Quality evaluation and content analysis of clinical practice guidelines for prevention and management of frailty in elderly hospitalized patients [J]. Journal of Nursing, 2025, 32(2): 50-55.
[9] SUN Juan, LI Ya-li, MA An-na, WANG Hua, ZHANG Hui-min. Experience of nursing postgraduates on ideological and political teaching in community nursing practice: a qualitative study [J]. Journal of Nursing, 2025, 32(1): 19-23.
[10] LI Ge-ge, WANG Wan-er, PU Jiang-feng, XIE Zhang-hao, YANG Niu, HUANG Hui-gen. Evaluation of allocation of nursing human resource in Guangdong Province based on entropy weight TOPSIS combined with RSR method [J]. Journal of Nursing, 2025, 32(1): 29-33.
[11] LI Ke, HE Yu-qiong, LI Yu-wei, CHANG Ying. Intervention programs for fear of falling in stroke patients: a scoping review [J]. Journal of Nursing, 2025, 32(1): 50-55.
[12] HE Fang, WEN Xiu-lan, LIN Yan, SUN Li, WANG Xiao-jie, YU Xin, LIU Hui, GUO Xiao-ping, ZHOU Yan. Establishment and practice of online neonatal nursing consultation clinic based on mobile healthcare [J]. Journal of Nursing, 2024, 31(9): 20-23.
[13] CHEN Jie, MENG Qing-tong, LIU Jing-jin, WU Yan-ni. Development of guideline-based exercise rehabilitation handbook for patients with chronic heart failure [J]. Journal of Nursing, 2024, 31(9): 36-41.
[14] FU Lu-lu, XIE Yi-xuan, WANG Yue, WEI Wei, ZHANG Chuan-ying, ZHU Yu. Evidence summary for auditory stimulation intervention for procedural pain in neonates [J]. Journal of Nursing, 2024, 31(9): 42-47.
[15] LI Ding-ding, WANG Shuai-you, ZHU Shan-shan, GUO Xin, ZHANG Hui-min, WANG Hong-ru, PAN Qin. Supportive care needs assessment tools for stroke patients: a scoping review [J]. Journal of Nursing, 2024, 31(9): 48-53.
Viewed
Full text


Abstract

Cited
  Shared   
No Suggested Reading articles found!