A Self‐powered Tennis Training System Based on Micro‐Nano Structured Sensing Yarn Arrays

IF 18.5 1区 材料科学 Q1 CHEMISTRY, MULTIDISCIPLINARY Advanced Functional Materials Pub Date : 2024-11-09 DOI:10.1002/adfm.202414395
Qian Chen, Duo Xu, Yan Yan, Zhan Qu, Haoyue Zhao, Xinyu Li, Yuying Cao, Chenhong Lang, Wasim Akram, Zhe Sun, Li Niu, Jian Fang
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Abstract

Wearable sensing devices can reliably track players' mobility, revolutionizing sports training. However, current sensing electronics face challenges due to their complex structures, battery dependence, and unreliable sensing signals. Here, a tennis training system is demonstrated using machine learning based on elastic self‐powered sensing yarns. By employing a simple and effective strategy, piezoelectric nanofibers and triboelectric materials are integrated into a single yarn, enabling the simultaneous translation of both triboelectric and piezoelectric signals. Additionally, these yarns exhibit outstanding processability, allowing them to be machine‐knitted into self‐powered sensing fabrics. Due to their great sensitivity, these sensing yarns and fabrics may detect human movement with great precision. Machine learning algorithms can classify and interpret these signals to recognize various human motions. The developed tennis training system aims to maximize its benefits and provide comprehensive training for both players and coaches. This work enhances the applicability of self‐powered sensing systems in smart sports monitoring and training, advancing the field of intelligent sports training.

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基于微纳结构传感纱线阵列的自供电网球训练系统
可穿戴传感设备能够可靠地跟踪运动员的移动情况,为体育训练带来了革命性的变化。然而,目前的传感电子设备因结构复杂、依赖电池和传感信号不可靠而面临挑战。在此,我们展示了一种基于弹性自供电传感纱线的机器学习网球训练系统。通过采用简单有效的策略,压电纳米纤维和三电材料被集成到一根纱线中,从而实现了三电信号和压电信号的同步转换。此外,这些纱线还具有出色的可加工性,可以用机器编织成自供电传感织物。由于具有极高的灵敏度,这些传感纱线和织物可以非常精确地探测到人体运动。机器学习算法可以对这些信号进行分类和解释,从而识别各种人体运动。所开发的网球训练系统旨在最大限度地发挥其优势,为运动员和教练员提供全面的训练。这项工作提高了自供电传感系统在智能运动监测和训练中的适用性,推动了智能运动训练领域的发展。
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来源期刊
Advanced Functional Materials
Advanced Functional Materials 工程技术-材料科学:综合
CiteScore
29.50
自引率
4.20%
发文量
2086
审稿时长
2.1 months
期刊介绍: Firmly established as a top-tier materials science journal, Advanced Functional Materials reports breakthrough research in all aspects of materials science, including nanotechnology, chemistry, physics, and biology every week. Advanced Functional Materials is known for its rapid and fair peer review, quality content, and high impact, making it the first choice of the international materials science community.
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