摘 要：随着智能穿戴技术的快速发展，其在运动员训练监控中的应用逐渐成为体育科学领域的研究热点。本研究旨在探讨智能穿戴设备在运动员训练中的实际应用效果及其未来发展前景，通过系统性分析现有技术手段与训练数据的关系，提出了一种基于多源传感器融合的监测框架。研究采用实验与数据分析相结合的方法，选取了不同项目的专业运动员作为研究对象，利用心率、加速度、体温等多种生理参数进行实时采集与分析，评估其对运动表现及身体状态的影响。结果显示，智能穿戴设备能够显著提高训练数据的精确性和实时性，为教练员制定个性化训练计划提供了科学依据。此外，该技术还有效降低了运动损伤的风险，提升了运动员的恢复效率。本研究的创新点在于首次将深度学习算法引入数据处理环节，优化了复杂运动场景下的信号识别精度，并提出了适用于多种运动项目的通用模型。研究表明，智能穿戴设备不仅能够满足当前训练需求，还将在未来实现更深层次的运动生理机制探索，为竞技体育的发展提供重要技术支持。
关键词：智能穿戴设备；多源传感器融合；深度学习算法；运动表现监测；个性化训练计划
Application and Prospects of Smart Wearable Devices in Athlete Training Monitoring
英文人名
Directive teacher:×××
Abstract：With the rapid development of intelligent wearable technology, its application in athlete training monitoring has gradually become a research hotspot in the field of sports science. This study aims to explore the practical application effects of intelligent wearable devices in athlete training and their future development prospects. Through a systematic analysis of the relationship between existing technical means and training data, a monitoring fr amework based on multi-source sensor fusion is proposed. The study combines experimental methods with data analysis, selecting professional athletes from different disciplines as research subjects. By utilizing various physiological parameters such as heart rate, acceleration, and body temperature for real-time collection and analysis, the impact on athletic performance and physical condition is evaluated. The results indicate that intelligent wearable devices can significantly enhance the accuracy and real-time nature of training data, providing a scientific basis for coaches to develop personalized training plans. Additionally, this technology effectively reduces the risk of sports injuries and improves athletes' recovery efficiency. The innovation of this study lies in the first introduction of deep learning algorithms into the data processing phase, which optimizes signal recognition accuracy in complex sports scenarios and proposes a universal model applicable to multiple sports disciplines. The study demonstrates that intelligent wearable devices not only meet current training needs but will also facilitate deeper explorations of physiological mechanisms in the future, offering crucial technical support for the development of competitive sports.
Keywords: Smart Wearable Devices；Multi-Source Sensor Fusion；Deep Learning Algorithms；Movement Performance Monitoring；Personalized Training Plans
目 录
引言 1
一、智能穿戴设备的技术基础 1
(一)智能穿戴设备的定义与分类 1
(二)关键传感技术解析 2
(三)数据处理与算法支持 2
二、运动员训练监控的需求分析 3
(一)现代训练中的数据需求 3
(二)传统监控方式的局限性 4
(三)智能穿戴设备的适用场景 4
三、智能穿戴设备在训练监控中的应用实践 5
(一)生理参数监测的应用 5
(二)运动表现评估的功能实现 5
(三)伤病预防与康复的支持 6
四、智能穿戴设备的发展前景与挑战 6
(一)技术创新方向展望 7
(二)数据隐私与伦理问题 7
(三)商业化推广的可行性分析 8
结论 8
参考文献 10
致谢 10
