可穿戴设备在肌少症中的应用范围综述
A Review of the Application Scope of Wearable Devices in Sarcopenia
摘要: 目的：文章综述了可穿戴设备在肌少症中的应用，包括步态分析、肌电图(EMG)传感器和多传感器融合技术等，探讨了其在日常活动监测、个性化康复训练和远程医疗中的具体应用。方法：系统检索中国知网、万方、维普、SinoMed、PubMed、Web of Science等国内外数据库，检索时间为建库至2025年1月，收集可穿戴设备在肌少症应用中的相关研究。结果：可穿戴设备通过嵌入式传感器和计算技术，能够实时监测和评估肌肉质量、功能及活动水平，为肌少症的检测、管理和干预提供了新的解决方案。结论：尽管可穿戴设备在数据准确性、设备舒适性和用户依从性等方面仍面临挑战，但随着技术的进步，其在肌少症管理中的应用前景广阔。
Abstract: Objective: This article reviews the application of wearable devices in sarcopenia, including gait analysis, electromyography (EMG) sensors, and multi-sensor fusion technology, and discusses their specific applications in daily activity monitoring, personalized rehabilitation training, and telemedicine. Methods: The system retrieved relevant studies on the application of wearable devices in sarcopenia from domestic and foreign databases such as CNKI, Wanfang, VIP, SinoMed, PubMed, and Web of Science. The retrieval time spanned from the establishment of the databases to January 2025. Results: Wearable devices, through embedded sensors and computing technology, can monitor and assess muscle mass, function, and activity levels in real time, providing new solutions for the detection, management, and intervention of sarcopenia. Conclusion: Although wearable devices still face challenges in terms of data accuracy, device comfort, and user compliance, their application in the management of sarcopenia is promising as technology advances.
文章引用：穆茂容, 王健翔, 殷小焦, 高云. 可穿戴设备在肌少症中的应用范围综述[J]. 临床医学进展, 2025, 15(3): 1911-1919. https://doi.org/10.12677/acm.2025.153820

参考文献

[1] Frontera, W.R., Hughes, V.A., Fielding, R.A., Fiatarone, M.A., Evans, W.J. and Roubenoff, R. (2000) Aging of Skeletal Muscle: A 12-yr Longitudinal Study. Journal of Applied Physiology, 88, 1321-1326. [Google Scholar] [CrossRef] [PubMed]
[2] 麻玉梅, 马黎娜, 郭海云, 等. 智能可穿戴设备在加速康复外科中的应用综述[J]. 医疗卫生装备, 2023, 44(5): 102-108.
[3] Chen, L., Woo, J., Assantachai, P., Auyeung, T., Chou, M., Iijima, K., et al. (2020) Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. Journal of the American Medical Directors Association, 21, 300-307.E2. [Google Scholar] [CrossRef] [PubMed]
[4] Beaudart, C., Rizzoli, R., Bruyère, O., Reginster, J. and Biver, E. (2014) Sarcopenia: Burden and Challenges for Public Health. Archives of Public Health, 72, Article No. 45. [Google Scholar] [CrossRef] [PubMed]
[5] 国务院办公厅印发《关于推动公立医院高质量发展的意见》[J]. 中国数字医学, 2021, 16(6): 52.
[6] Tankisi, H., Burke, D., Cui, L., de Carvalho, M., Kuwabara, S., Nandedkar, S.D., et al. (2020) Standards of Instrumentation of Emg. Clinical Neurophysiology, 131, 243-258. [Google Scholar] [CrossRef] [PubMed]
[7] Stavropoulos, T.G., Papastergiou, A., Mpaltadoros, L., Nikolopoulos, S. and Kompatsiaris, I. (2020) IoT Wearable Sensors and Devices in Elderly Care: A Literature Review. Sensors, 20, Article 2826. [Google Scholar] [CrossRef] [PubMed]
[8] 殷芮, 张雨晴, 史维霞, 等. 表面肌电在针刺治疗脑卒中肢体功能障碍中的应用研究进展[J]. 中医康复, 2024, 1(9): 6-10.
[9] 罗志成, 田宁, 杨光, 等. 面向瘫痪肢体功能康复的无线多通道混合数据采集系统[J]. 物联网学报, 2024, 8(2): 103-115.
[10] 郑杨, 强威, 张四聪. 脑-运动单元功能耦合估计方法[J]. 西安交通大学学报, 2024, 58(12): 111-118.
[11] 冯玉竹, 魏剑南, 马玉鑫, 等. 基于物联网的可穿戴设备及生命体征监测系统[J]. 工业技术创新, 2023, 10(5): 106-115.
[12] Fang, C., He, B., Wang, Y., Cao, J. and Gao, S. (2020) EMG-Centered Multisensory Based Technologies for Pattern Recognition in Rehabilitation: State of the Art and Challenges. Biosensors, 10, Article 85. [Google Scholar] [CrossRef] [PubMed]
[13] Tam, W., Alajlani, M. and Abd-alrazaq, A. (2023) An Exploration of Wearable Device Features Used in UK Hospital Parkinson Disease Care: Scoping Review. Journal of Medical Internet Research, 25, e42950. [Google Scholar] [CrossRef] [PubMed]
[14] Argent, R., Bourke, A.K., Brom, M., Caulfield, B., Greene, B.R., Muaremi, A., et al. (2022) Validity and Reliability of A Body-Worn Biomechanical Sensor Platform for Gait Analysis. Osteoarthritis and Cartilage, 30, S148-S149. [Google Scholar] [CrossRef] 
[15] 李楠, 徐磊, 刘丽妍, 等. 老年人健康监测可穿戴设备的应用研究[J]. 针织工业, 2022(6): 60-3.
[16] 张敏, 王飞, 赵祥欣, 等. 基于足底力传感器的脑卒中患者下肢运动感知获取方法[J]. 机械设计与研究, 2024, 40(3): 240-244.
[17] 陶幸, 俞帆山, 宋越杰, 等. 基于惯性传感器的免对准动作的人体上肢运动捕捉方法[J]. 飞控与探测, 2024, 7(2): 28-35.
[18] 陈玲, 江红霞, 刘基宏. 基于可穿戴传感器的躯干参考点选取分析[J]. 丝绸, 2022, 59(4): 52-58.
[19] 王冰飞, 蒋睿, 何思源, 等. 浅谈社区老年人对便携式可穿戴设备的需求——以智能手环为例中国老年[J]. 保健医学, 2020, 18(4): 21-6.
[20] Yang, C. and Hsu, Y. (2010) A Review of Accelerometry-Based Wearable Motion Detectors for Physical Activity Monitoring. Sensors, 10, 7772-7788. [Google Scholar] [CrossRef] [PubMed]
[21] Benson, L.C., Räisänen, A.M., Clermont, C.A. and Ferber, R. (2022) Is This the Real Life, or Is This Just Laboratory? A Scoping Review of Imu-Based Running Gait Analysis. Sensors, 22, Article 1722. [Google Scholar] [CrossRef] [PubMed]
[22] Roberts, L.M., Jaeger, B.C., Baptista, L.C., Harper, S.A., Gardner, A.K., Jackson, E.A., et al. (2019) Wearable Technology to Reduce Sedentary Behavior and CVD Risk in Older Adults: A Pilot Randomized Clinical Trial. Clinical Interventions in Aging, 14, 1817-1828. [Google Scholar] [CrossRef] [PubMed]
[23] Majumder, S., Aghayi, E., Noferesti, M., Memarzadeh-Tehran, H., Mondal, T., Pang, Z., et al. (2017) Smart Homes for Elderly Healthcare—Recent Advances and Research Challenges. Sensors, 17, Article 2496. [Google Scholar] [CrossRef] [PubMed]
[24] Mao, Q., Zhang, J., Yu, L., Zhao, Y., Luximon, Y. and Wang, H. (2024) Effectiveness of Sensor-Based Interventions in Improving Gait and Balance Performance in Older Adults: Systematic Review and Meta-Analysis of Randomized Controlled Trials. Journal of NeuroEngineering and Rehabilitation, 21, Article No. 85. [Google Scholar] [CrossRef] [PubMed]
[25] 季稳, 黄宽明, 陈家冲, 等. 可穿戴设备在帕金森病患者围手术期运动功能检测中的应用[J]. 中国医学工, 2024, 32(6): 5-9.
[26] 何杨柳青, 梁芬荣, 王艺明, 等. 可穿戴设备在抑郁症监测与干预领域中的应用进展[J]. 中国医疗器械杂志, 2024, 48(4): 407-412.
[27] Argañarás, J.G., Wong, Y.T., Begg, R. and Karmakar, N.C. (2021) State-of-the-Art Wearable Sensors and Possibilities for Radar in Fall Prevention. Sensors, 21, Article 6836. [Google Scholar] [CrossRef] [PubMed]
[28] 林毅, 毛永, 王向东, 等. 老年运动人群可穿戴设备认知及使用行为研究[J]. 老龄科学研究, 2023, 11(4): 34-47.
[29] 谢美莲, 张志云, 董屿, 等. 可穿戴设备在卫生健康领域生命体征监测中的应用及展望[J]. 生物医学工程与临床, 2024, 28(5): 735-741.

为你推荐