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利用基于 IoMT 的智能手套进行连续生命体征监测,以保障运动员健康和优化训练方案。

Utilizing IoMT-Based Smart Gloves for Continuous Vital Sign Monitoring to Safeguard Athlete Health and Optimize Training Protocols.

机构信息

Information Systems Engineering, Kocaeli University, Umuttepe Campus, 41001 Kocaeli, Turkey.

Biomedical Engineering, Kocaeli University, Umuttepe Campus, 41001 Kocaeli, Turkey.

出版信息

Sensors (Basel). 2024 Oct 10;24(20):6500. doi: 10.3390/s24206500.

Abstract

This paper presents the development of a vital sign monitoring system designed specifically for professional athletes, with a focus on runners. The system aims to enhance athletic performance and mitigate health risks associated with intense training regimens. It comprises a wearable glove that monitors key physiological parameters such as heart rate, blood oxygen saturation (SpO2), body temperature, and gyroscope data used to calculate linear speed, among other relevant metrics. Additionally, environmental variables, including ambient temperature, are tracked. To ensure accuracy, the system incorporates an onboard filtering algorithm to minimize false positives, allowing for timely intervention during instances of physiological abnormalities. The study demonstrates the system's potential to optimize performance and protect athlete well-being by facilitating real-time adjustments to training intensity and duration. The experimental results show that the system adheres to the classical "220-age" formula for calculating maximum heart rate, responds promptly to predefined thresholds, and outperforms a moving average filter in noise reduction, with the Gaussian filter delivering superior performance.

摘要

本文提出了一种专门为专业运动员(尤其是跑步运动员)设计的生命体征监测系统的开发。该系统旨在提高运动员的表现,并降低与高强度训练方案相关的健康风险。它由一个可穿戴手套组成,可监测关键生理参数,如心率、血氧饱和度(SpO2)、体温和陀螺仪数据,用于计算线性速度等其他相关指标。此外,还跟踪环境变量,包括环境温度。为了确保准确性,该系统采用了板载滤波算法来最小化误报,以便在出现生理异常时及时进行干预。该研究表明,该系统通过实时调整训练强度和持续时间,具有优化性能和保护运动员健康的潜力。实验结果表明,该系统符合经典的“220-年龄”公式来计算最大心率,对预定义阈值做出快速响应,在降噪方面优于移动平均滤波器,而高斯滤波器则具有更好的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e45f/11511544/8d95400af16f/sensors-24-06500-g001.jpg

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