运动智能可穿戴设备的关键技术与应用前沿进展

乔玉成

doi:10.14036/j.cnki.cn11-4513.2025.04.002

PDF(1930 KB)

首都体育学院学报 ›› 2025, Vol. 37 ›› Issue (4) : 364-374. DOI: 10.14036/j.cnki.cn11-4513.2025.04.002

体育科技创新

运动智能可穿戴设备的关键技术与应用前沿进展

乔玉成

作者信息 +

Key Technologies and Frontline Applications of Intelligent Wearable Devices for Sports

QIAO Yucheng

Author information +

文章历史 +

摘要

随着数字化时代的到来，运动智能可穿戴设备的研究与运用为智慧体育的创新发展提供了理论与实践参考。运用文献研究法与系统分析法，聚焦于传感技术、人机交互技术、无线通信与物联网技术、供电与能源管理技术，探讨柔性电子、新型材料、人工智能等前沿技术突破及其在体育教学、竞技训练、大众健康与运动康复等领域的应用现状与潜力。研究发现：1）在技术层面，运动智能可穿戴设备发展重点在于新一代高精度微型传感器、以虚拟现实为代表的沉浸式交互技术、5G与物联网的深度融合以及基于摩擦纳米发电机的能量自给技术；2）在应用层面，运动智能可穿戴设备已广泛赋能运动表现的实时优化、个性化健康指导、远程康复监护等场景；3）当前有关运动智能可穿戴设备的研究仍面临若干关键瓶颈，包括多源异构数据的高效实时融合、续航能力与佩戴舒适性的平衡、数据安全与用户隐私信息保护，以及行业标准体系构建。研究认为：运动智能可穿戴设备是推动智慧体育发展的关键引擎，但其技术生态与应用广度仍有待完善，亟需在核心技术自主创新、多学科交叉融合、行业标准体系构建等方面实现突破。

Abstract

With the advent of the digital age, the research and application of sports intelligent wearable equipment provides a theoretical and practical reference for the innovation and development of intelligent sports. Employing a methodology of literature review and systematic analysis, the study first focuses on four core technologies: sensing, human-computer interaction, wireless communication & the Internet of Things (IoT), and power supply & energy management. It then explores frontier technological breakthroughs-such as flexible electronics, novel materials, and artificial intelligence-and examines their current applications and potentials in the fields of physical education, competitive training, public health, and athletic rehabilitation.Results: The study finds that:(1) On the technological front, the development focus is on next-generation high-precision miniature sensors, immersive interactive technologies represented by virtual reality, the deep integration of 5G and the IoT, and energy self-sufficiency technologies based on triboelectric nanogenerators (TENGs).(2) In terms of application, these devices are now widely empowering scenarios such as the real-time optimization of athletic performance, personalized health guidance, and remote rehabilitation monitoring.(3) Regarding challenges, its development still faces several key bottlenecks, including the efficient real-time fusion of multi-source heterogeneous data, the balance between battery life and wearing comfort, data security and user privacy protection, and the lack of an industry-wide standards system.Conclusion: Intelligent wearable sports equipment is a key engine driving the development of smart sports; however, its technological ecosystem and breadth of application still require maturation. In the future, breakthroughs are urgently needed in areas such as indigenous innovation in core technologies, interdisciplinary integration, and the establishment of an industry-wide standards system in order to empower the comprehensive and in-depth development of the field.

导出引用

乔玉成. 运动智能可穿戴设备的关键技术与应用前沿进展[J]. 首都体育学院学报. 2025, 37(4): 364-374 https://doi.org/10.14036/j.cnki.cn11-4513.2025.04.002

QIAO Yucheng. Key Technologies and Frontline Applications of Intelligent Wearable Devices for Sports[J]. Journal of Capital University of Physical Education and Sports. 2025, 37(4): 364-374 https://doi.org/10.14036/j.cnki.cn11-4513.2025.04.002

中图分类号： G80-05 (体育与其他学科的关系) 学科代码：040302

参考文献

列表( 原文顺序 | 文献年度倒序 | 文中引用次数倒序 ) 可视化分析

[1]	2024年智能穿戴行业发展前景分析[Z/OL]. (2024-05-31)[2025-02-31]. https://www.chinabgao.com/freereport/93942.html. https://www.chinabgao.com/freereport/93942.html 本文引用 [2]

[2]	CHEN H, ZHUO F, ZHOU J, et al. Advances in graphene-based flexible and wearable strain sensors[J]. Chem Eng J, 2023, 464:142576. 本文引用 [1]

[3]	ZHAO X, ZHOU J. Fast recognition algorithm for human motion posture using multimodal bioinformation fusion[J]. Mathematical Problems In Engineering, 2022(1):9538295. 本文引用 [1]

[4]	赵诗凡, 沈雷. 多模态交互的老年高血压人群智能可穿戴研究[J]. 针织工业, 2024(4):65-70. 本文引用 [1]

[5]	LI M, SUN M, WANG L. Application analysis of smart wearable devices in students’ physical activity under the background of big data[J]. Journal of Physics: Conference Series, 2021, 1757(1): 12124. 本文引用 [1]

[6]

孙祯锋. 运动员可穿戴设备中个人数据隐私的法律保护[J]. 沈阳体育学院学报, 2022, 41(4):104-110.

https://doi.org/10.12163/j.ssu.20211135

本文引用 [1] 摘要

以物联网技术为基础的可穿戴设备普遍而迅速地介入到职业体育运动之中,其对运动员个人数据的大规模处理已经触发运动员的数据隐私危机,能够兼顾数据利用和隐私安全的法律保护模式亟待研究。通过比较分析发现,既有的个人数据隐私保护的赋权模式和定责模式存在诸多局限,而场景化模式针对不同场景中的数据隐私风险设置相应的隐私保护举措可以最大限度地契合运动员的合理隐私期待,进而实现对运动员个人数据权利的切实保障。这一进路也符合运动员作为体育从业者和技术应用对象的弱势方的现实境况。研究建议:充分考虑运动员可穿戴设备中个人数据的特殊性,结合不同场景和不同数据类型设计整全式的隐私保护模式。

[7]	YANG L, AMIN O, SHIHADA B. Intelligent wearable systems: Opportunities and challenges in health and sports[J]. ACM Computing Surveys, 2024, 56(7):1-42. 本文引用 [6]

[8]	DU L. Application of smart wearable devices in sports performance analysis and enhancement[J]. Applied Mathematics and Nonlinear Sciences, 2024, 9(1):1-15. 本文引用 [5]

[9]	DU X J, MING W T, GUO S S, et al. Self-powered and self-sensing energy textile system for flexible wearable applications[J]. ACS Applied Materials & Interfaces, 2020, 12(50):55876-55883. 本文引用 [1]

[10]	霍波, 李彦锋, 高腾, 等. 体育人工智能领域关键技术的研究现状和发展方向[J]. 首都体育学院学报, 2023, 35(3):233-256. 本文引用 [4]

[11]	STEFANA E, MARCIANO F, ROSSI D, et al. Wearable devices for ergonomics: A systematic literature review[J]. Sensors (Basel), 2021, 21(3):777. 本文引用 [1]

[12]	刘丰, 韩京龙, 齐骥, 等. 智能可穿戴设备的研究和应用进展[J]. 分析化学, 2021, 49(2):159-171. 本文引用 [1]

[13]	GLAROS C, FOTIADIS D I, LIKAS A, et al. A wearable intelligent system for monitoring health condition and rehabilitation of running athletes[C]// 4th International IEEE EMBS Special Topic Conference on Information Technology Applications in Biomedicine. New York: IEEE, 2003: 276-279. 本文引用 [1]

[14]

QIU

, WANG

, XIE

. A survey on smart wearables in the application of fitness[C]// 2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th Intl Conf on Pervasive Intelligence and Computing, 3rd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress (DASC/PiCom/DataCom/CyberSciTech). New York: IEEE, 2017: 303-307.

本文引用 [1]

[15]	SUN Y, FAN T. Construction of wearable physical exercise management system based on artificial intelligence technology[C]// 2023 International Conference on Applied Intelligence and Sustainable Computing (ICAISC). New York: IEEE,2023:1-6. 本文引用 [3]

[16]	LIU X. Intelligent physical training data processing based on wearable devices[J]. Comput Intell Neurosci, 2022(1):1207457. 本文引用 [2]

[17]	刘忱怡. 智能可穿戴设备在竞技体育中的作用和未来发展趋势[C]// 国际班迪联合会(FIB),国际体能协会(ISCA),中国班迪协会(CBF). 2024年第二届国际体育科学大会论文集. 北京: 北京体育大学,2024:979-985. 本文引用 [1]

[18]	韦哲, 石恒兵, 曹彤, 等. 国内外智能可穿戴设备的研究进展[J]. 中国医学装备, 2020, 17(10):18-21. 本文引用 [1]

[19]	邓俊杰, 刘红, 阳小兰, 等. 可穿戴智能设备的现状及未来发展趋势展望[J]. 黑龙江科技信息, 2015(28):135. 本文引用 [1]

[20]	OLYANASAB A, ANNABESTANI M. Leveraging machine learning for personalized wearable biomedical devices: A review[J]. Journal of Personalized Medicine, 2024, 14(2):203. 本文引用 [2]

[21]	XIE D D. Development and evaluation methods of smart wearable clothing[J]. Journal of Physics: Conference Series, 2021, 1790(1):12018. 本文引用 [1]

[22]

YANG

, DENG

, CHU

, et al. Hierarchically microstructure-bioinspired flexible piezoresistive bioelectronics[J]. ACS Nano, 2021, 15(7):11555-11563.

https://doi.org/10.1021/acsnano.1c01606

https://www.ncbi.nlm.nih.gov/pubmed/34128640

本文引用 [1] 摘要

The naturally microstructure-bioinspired piezoresistive sensor for human-machine interaction and human health monitoring represents an attractive opportunity for wearable bioelectronics. However, due to the trade-off between sensitivity and linear detection range, obtaining piezoresistive sensors with both a wide pressure monitoring range and a high sensitivity is still a great challenge. Herein, we design a hierarchically microstructure-bioinspired flexible piezoresistive sensor consisting of a hierarchical polyaniline/polyvinylidene fluoride nanofiber (HPPNF) film sandwiched between two interlocking electrodes with microdome structure. Ascribed to the substantially enlarged 3D deformation rates, these bioelectronics exhibit an ultrahigh sensitivity of 53 kPa, a pressure detection range from 58.4 to 960 Pa, a fast response time of 38 ms, and excellent cycle stability over 50 000 cycles. Furthermore, this conformally skin-adhered sensor successfully demonstrates the monitoring of human physiological signals and movement states, such as wrist pulse, throat activity, spinal posture, and gait recognition. Evidently, this hierarchically microstructure-bioinspired and amplified sensitivity piezoresistive sensor provides a promising strategy for the rapid development of next-generation wearable bioelectronics.

[23]	BIJALWAN V, SEMWAL V B, GUPTA V. Wearable sensor-based pattern mining for human activity recognition: Deep learning approach[J]. Industrial Robot: the international journal of robotics research and application, 2022, 49(1):21-33. 本文引用 [1]

[24]	AROGANAM G, MANIVANNAN N, HARRISON D. Review on wearable technology sensors used in consumer sport applications[J]. Sensors, 2019, 19(9):1983. 本文引用 [1]

[25]	SELVAN S, JAYARAMAN S, VARADHARAJAN S, et al. Smart shoes for fitness and performance analysis of sportsmen[C]// 2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT), New York: IEEE 2024, 5:552-557. 本文引用 [1]

[26]	ZHAO S, LIU J, GONG Z, et al. Wearable physiological monitoring system based on electrocardiography and electromyography for upper limb rehabilitation training[J]. Sensors, 2020, 20(17):4861. 本文引用 [1]

[27]	颜延, 邹浩, 周林, 等. 可穿戴技术的发展[J]. 中国生物医学工程学报, 2015, 34(6):644-653. 本文引用 [1]

[28]	SECKIN A C, ATE S B, SECKIN M. Review on wearable technology in sports: Concepts, challenges and opportunities[J]. Applied Sciences, 2023, 13(18):10399. 本文引用 [1]

[29]	孙效华, 冯泽西. 可穿戴设备交互设计研究[J]. 装饰, 2014(2):28-33. 本文引用 [1]

[30]	朱旭, 穆存远. 智能穿戴设备交互与展示设计[J]. 设计, 2017(17):44-45. 本文引用 [1]

[31]	JIANG M, TIAN Z, YU C, et al. Intelligent 3D garment system of the human body based on deep spiking neural network[J]. Virtual Reality & Intelligent Hardware, 2024, 6(1):43-55. 本文引用 [1]

[32]	LAMBERTI F, MANURI F, PARAVATI G, et al. Using semantics to automatically generate speech interfaces for wearable virtual and augmented reality applications[J]. IEEE Transactions on Human-Machine Systems, 2016, 47(1):152-164. 本文引用 [1]

[33]	POLLINI A. Meaningful control loops in tomorrow human-centred automation[C]// Congress of the International Association of Societies of Design Research. Singapore: Springer Nature Singapore,2021:3078-3094. 本文引用 [1]

[34]	严欣怡. 可穿戴设备与物联网技术在体育科学的运用对人们生活方式的影响[C]// 北京大学. 体育社会学与社会变革中的挑战——2014年世界体育社会学大会暨中国体育社会科学年会论文集. 北京: 北京体育大学,2014:32-33. 本文引用 [1]

[35]	LI Y, WAN L, ZHANG H. Communication network for sports activity monitoring systems[J]. Complexity, 2021(1): 9971605. 本文引用 [1]

[36]	梁鹏. 可穿戴设备和体育数据科学的融合及热点趋势[C]// 国际班迪联合会(FIB),国际体能协会(ISCA),中国班迪协会(CBF). 第四届国际体育科学大会论文集. 罗州: 韩国东新大学研究生院,2024:4. 本文引用 [2]

[37]	CANDELL R, LIU Y, KASHEF M, et al. Smart Manufacturing testbed for the advancement of wireless adoption in the factory[C]// IFIP International Conference on Product Lifecycle Management. Cham: Springer International Publishing, 2020: 176-189. 本文引用 [1]

[38]	LIU J, ZHANG G, SUN R, et al. A blockchain-based conditional privacy-preserving traffic data sharing in cloud[C]// ICC 2020-2020 IEEE International Conference on Communications (ICC). New York: IEEE, 2020: 1-6. 本文引用 [2]

[39]	LIANG J, HE Q. Application of artificial intelligence wearable devices based on neural network algorithm in mass sports activity evaluation[J]. Soft Computing, 2023, 27(14):10177-10188. 本文引用 [7]

[40]	向指航, 徐卫林, 段吉海, 等. 应用于可穿戴式设备的超低功耗SAR ADC研究与设计[J]. 电子器件, 2018, 41(3):808-812. 本文引用 [1]

[41]	薛俊伟, 黄岳山, 杜欣, 等. 蓝牙低功耗可穿戴血氧监测设备的设计[J]. 中国生物医学工程学报, 2015, 34(6):701-707. 本文引用 [1]

[42]	肖志达. 柔性压电复合材料的结构设计及电输出性能研究[D]. 长沙: 中南大学, 2023. 本文引用 [1]

[43]	LUO J, GAO W, WANG Z L. The triboelectric nanogenerator as an innovative technology toward intelligent sports[J]. Adv Mater, 2021, 33(17):2004178. 本文引用 [1]

[44]	GENG F, HUO X. A self powered sport sensor based on triboelectric nanogenerator for fosbury flop training[J]. Journal of Sensors, 2022(1):3130928. 本文引用 [1]

[45]	陈莉, 张艳琳, 刘皓, 等. 智能可穿戴产品用柔性传感器研究进展[J]. 针织工业, 2021(11):81-85. 本文引用 [1]

[46]

宿荣芳, 文心仪, 王俊, 等. 智能可穿戴柔性压力传感器的研究进展[J]. 材料工程, 2024, 52(8):98-108.

https://doi.org/10.11868/j.issn.1001-4381.2023.000861

本文引用 [1] 摘要

柔性压力传感器可以附着在人体皮肤感知外界压力信号，且具有传感范围广、响应时间短、灵敏度和耐久性高等特点，因此被广泛应用于电子皮肤和人机交互等领域。柔性压力传感器通常由柔性基底、活性材料、导电电极组成。其中，一种或多种活性材料通过与柔性基底复合形成传感材料，其受外界刺激产生的变形会引起阻值等变化，进而实现传感功能。此外，通过引入微结构可增加传感材料的可压缩性以及对微小压力的敏感度，提升传感性能。本文围绕薄膜和织物两类基底，综述了在其中掺杂碳基、金属基与黑磷基等活性材料的柔性压力传感器的研究，重点论述了不同传感器的制备方法、机电性能与应用场景，总结了各类传感器的优缺点。在此基础上，对未来智能可穿戴柔性压力传感器如何实现宽范围压力检测、商业化以及制作流程无毒化与长时期生物相容性实验等方面的研究做出了展望。

[47]	DOVGAN N. The pivotal role of technology in enhancing athletic performance: insights and future directions[J]. SSRN Electronic Journal, 2023:4602857. 本文引用 [2]

[48]

王玲, 战鹏弘, 刘文勇. 互联网时代的弄潮儿——可穿戴医疗设备[J]. 科技导报, 2017, 35(2):12-18.

https://doi.org/10.3981/j.issn.1000-7857.2017.02.001

本文引用 [1] 摘要

随着移动医疗的强势兴起、智能传感等新技术的发展以及个性化健康观念的普及，智能可穿戴设备近年来发展迅速，其中与健康医疗相关的可穿戴设备已成为最有前景的领域之一。本文从可穿戴医疗设备涉及的新型材料技术、智能传感技术、无线数据传输技术、低功耗电路设计技术、能源采集与存储技术和大数据分析技术等方面，综述了可穿戴医疗设备关键技术的最新进展，并分析了该领域未来的趋势和面临的挑战。

[49]	YANG M, YE Z, REN Y, et al. Recent advances in nanomaterials used for wearable electronics[J]. Micromachines, 2023, 14(3):603. 本文引用 [1]

[50]	ZHANG S, LIU C, SUN X, et al. Current development of materials science and engineering towards epidermal sensors[J]. Prog Mater Sci, 2022, 128:100962. 本文引用 [1]

[51]	LU Z, JIA C, YANG X, et al. A flexible TENG based on micro-structure film for speed skating techniques monitoring and biomechanical energy harvesting[J]. Nanomaterials, 2022, 12(9):1576. 本文引用 [1]

[52]	WANG J, LI L, LIU H, et al. Graphene/carbon nanotube conductive ink-based biomimetic structure for self-powered flexible medical monitoring devices[J]. ACS Applied Nano Materials, 2024, 7(2):1863-1875. 本文引用 [1]

[53]

GAUTHIER

, ROUDJANE

, FRASIE

, et al. Multimodal electrophysiological signal measurement using a new flexible and conductive polymer fiber-electrode[C]// 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). New York: IEEE, 2020: 4373-4376.

本文引用 [1]

[54]	CHIU C, HUANG C, LI J, et al. Flexible hybrid electronics nanofiber electrodes with excellent stretchability and highly stable electrical conductivity for smart clothing[J]. ACS Applied Materials & Interfaces, 2022, 14(37):42441-42453. 本文引用 [1]

[55]	QIU J, YU T, ZHANG W, et al. A bioinspired, durable, and nondisposable transparent graphene skin electrode for electrophysiological signal detection[J]. ACS Materials Letters, 2020, 2(8):999-1007. 本文引用 [1]

[56]	林卓藩, 郑浩宇, 马志伟. 基于人体姿态的可穿戴智能设备[J]. 科技传播, 2020, 12(1):97-98. 本文引用 [1]

[57]	LYMBERIS A. Intelligent wearable systems achievements, challenges and perspectives[J]. Advances in Science and Technology, 2009, 57:88-93. 本文引用 [1]

[58]	彭仲康, 崔兴然, 张政波, 等. 可穿戴设备:评估与监测人体生理状态的展望[J]. 生物医学工程学杂志, 2023, 40(6):1045-1052. 本文引用 [2]

[59]	NGUYEN L N N, RODRÍGUEZ M D, CATALÀ A, et al. Basketball activity recognition using wearable inertial measurement units[C]// Proceedings of the XVI International Conference on Human Computer Interaction. New York: Association for Computing Machinery, 2015: 1-6. 本文引用 [2]

[60]	MAJEED M G, SABAH H A, DAWOOD M N, et al. Athlete’s performance analysis based on improved machine learning approach on wearable devices[J]. Full Length Article, 2023, 8(1):75-91. 本文引用 [1]

[61]	徐艺文, 王梓, 李甜. 人工智能技术在运动表现优化中的应用与挑战[C]// 四川省体育科学学会,四川省学生体育艺术协会. 2024第二届四川省体育科学大会论文报告会论文集(2). 北京: 中央民族大学体育学院,2024:2. 本文引用 [1]

[62]	BHATIA M. Intelligent system of game-theory-based decision making in smart sports industry[J]. ACM Transactions on Intelligent Systems and Technology (TIST), 2021, 12(3):1-23. 本文引用 [1]

[63]	陈丁丁, 田浩, 王登, 等. 可穿戴设备在健康管理预防系统构建中的应用与创新发展[C]// 中国体育科学学会体质与健康分会. 2024年全国运动增强体质与健康学术会议论文摘要集. 南京: 南京体育学院,2024:3. 本文引用 [1]

[64]	HUIFENG W, KADRY S N, RAJ E D. Continuous health monitoring of sportsperson using IoT devices based wearable technology[J]. Computer Communications, 2020, 160:588-595. 本文引用 [1]

[65]	LI Z, LI A, CHEN T, et al. Research on health management and risk warning based on sensor data[J]. Procedia Computer Science, 2022, 214:329-336. 本文引用 [1]

[66]	WEI S, WU Z. The application of wearable sensors and machine learning algorithms in rehabilitation training: A systematic review[J]. Sensors, 2023, 23(18):7667. 本文引用 [1]

[67]	ALEXANDRE R, POSTOLACHE O, GIRÃO P S. Physical rehabilitation based on smart wearable and virtual reality serious game[C]// 2019 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). New York: IEEE, 2019: 1-6. 本文引用 [1]

[68]	GOLBERG E, PINKOSKI A, BEAUPRE L, et al. Monitoring external workload with wearable technology after anterior cruciate ligament reconstruction: A scoping review[J]. Orthopaedic Journal of Sports Medicine, 2023, 11(8):1-10. 本文引用 [1]

[69]	HILTY D M, ARMSTRONG C M, EDWARDS S A, et al. Sensor, wearable, and remote patient monitoring competencies for clinical care and training: scoping review[J]. Journal of Technology in Behavioral Science, 2021, 6(2):252-277. 本文引用 [1]

[70]	MEKRUKSAVANICH S, JANTAWONG P, JITPATTANAKUL A. Recognizing and under standing sport activities based on wearable sensor signals using deep residual networ[C]//2023 Research, Invention, and Innovation Congress:Innovative Electricals and Electronics (RI2C). New York: IEEE, 2023: 166-169. 本文引用 [1]

[71]	LU Z, XIE Z, ZHU Y, et al. A stable and durable triboelectric nanogenerator for speed skating land training monitoring[J]. Electronics, 2022, 11(22):3717. 本文引用 [1]

[72]	MADDIRALA G, SEARLE T, WANG X, et al. Multifunctional skin-compliant wearable sensors for monitoring human condition applications[J]. Applied Materials Today, 2022, 26:101361. 本文引用 [1]

[73]	COSOLI G, SPINSANTE S, SCALISE L. Wrist-worn and chest-strap wearable devices: Systematic review on accuracy and metrological characteristics[J]. Measurement, 2020, 159:107789. 本文引用 [1]

[74]	XU Y. Research on academic early warning and assistance under artificial intelligence vision: current situation, trend and application[C]// 2022 3rd International Conference on Education, Knowledge and Information Management (ICEKIM). New York: IEEE, 2022: 268-273. 本文引用 [1]

[75]	杨进, 王卿璞, 胡慧宁, 等. 可穿戴设备续航能力研究的新进展[J]. 微纳电子技术, 2016, 53(7):425-430,448. 本文引用 [1]

[76]	MITAL G. 可穿戴设备:如何延长电池续航时间[J]. 电子产品世界, 2015, 22(9):15-16,26. 本文引用 [1]

[77]	SONG Y, MIN J, YU Y, et al. Wireless battery-free wearable sweat sensor powered by human motion[J]. Science Advances, 2020, 6(40):eaay9842. 本文引用 [1]

[78]	张茜, 钟嘉馨. 基于交互理念的体育用品智能可穿戴技术及其应用研究[J]. 艺术百家, 2022, 38(3):156-163. 本文引用 [1]

[79]	徐子盛. 插层型驻极体换能器的模型构建和压电特性研究[D]. 武汉: 华中科技大学,2022:1-2. 本文引用 [1]

[80]	SHI X, HUANG Z. Wearable device monitoring exercise energy consumption based on Internet of things[J]. Complexity, 2021(1):8836723. 本文引用 [1]

[81]	冯登国, 张敏, 李昊. 大数据安全与隐私保护[J]. 计算机学报, 2014, 37(1):246-258. 本文引用 [1]

[82]	王乐, 杨哲荣, 刘容京, 等. 基于属性加密算法的可穿戴设备系统隐私保护方法研究[J]. 信息网络安全, 2018(6):77-84. 本文引用 [1]

[83]

马方方, 刘树波, 熊星星, 等. 可穿戴设备数值型敏感数据本地差分隐私保护[J]. 计算机应用, 2019, 39(7):1985-1990.

https://doi.org/10.11772/j.issn.1001-9081.2018122466

本文引用 [1] 摘要

针对数据服务器不可信时，直接收集可穿戴设备多维数值型敏感数据有可能存在泄露用户隐私信息的问题，通过引入本地差分隐私模型，提出了一种可穿戴设备数值型敏感数据的个性化隐私保护方案。首先，通过设置隐私预算的阈值区间，用户在区间内设置满足个人隐私需求的隐私预算，同时也满足了个性化本地差分隐私；其次，利用属性安全域将敏感数据进行归一化；最后，利用伯努利分布分组扰动多维数值型敏感数据，并利用属性安全域对扰动结果进行归一化还原。理论分析证明了该算法满足个性化本地差分隐私。实验结果表明该算法的最大相对误差（MRE）明显低于Harmony算法，在保护用户隐私的基础上有效地提高了不可信数据服务器从可穿戴设备收集数据的可用性。

[84]	王俊. 面向健康服务的可穿戴设备安全认证与隐私数据发布[D]. 武汉: 武汉大学, 2018. 本文引用 [1]

[85]	HAN J, LI Q, XU Y, et al. Design of a trusted content authorization security framework for social media[J]. Applied Sciences, 2024, 14(4):1643. 本文引用 [1]

[86]	CHOWDHURY M J M, KAYES A, WATTERS P, et al. Patient controlled, privacy preserving iot healthcare data sharing framework[C]// 53rd Annual Hawaii International Conference on System Scicences. Hawaii: IEEE, 2020:3700-3710. 本文引用 [1]

[87]	代青松. 科技赋能体育:可穿戴设备在运动训练中的应用与发展[C]// 中国体育科学学会运动训练学分会.2022年全国运动训练学术研讨会摘要集(一). 开封: 河南大学体育学院,2022:1. 本文引用 [2]