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Wearable bracelets with variable sampling frequency for measuring multiple physiological parameter of human

机译:具有可变采样频率的可穿戴手镯,用于测量人类多种生理参数

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摘要

With the acceleration of modernization and the marked improvement in the quality of life, more and more people pay attention to their own health. Sports health has become the first choice for most people because of its natural and healthy way. Therefore, devices with step counting functions such as smart bracelets and smart phones came into being. This paper proposes a design method for measuring the human body's multiple physiological parameters with multiple sampling frequencies. It collects three physiological parameters of blood oxygen saturation, exercise energy consumption and body temperature of a sports human body. At the same time, in order to improve the endurance of a healthy bracelet, a variable sampling frequency scheme is designed using the BP neural network algorithm, and all physical health information can be determined according to the heart rate frequency. STM32 combined with host computer is used to verify the design method. It can monitor real-time human physiological parameters and conduct a comprehensive assessment of human health recording changes in human health information. Through the system test and analysis of the experimental results, it is verified that the physiological data collected has higher accuracy based on improving the endurance.
机译:随着现代化的加速和生活质量的显着改善,越来越多的人关注自己的健康。由于其自然和健康的方式,体育健康已成为大多数人的首选。因此,具有阶跃计数功能的设备,例如智能手机和智能手机。本文提出了一种用多种采样频率测量人体多种生理参数的设计方法。它收集了血氧饱和度的三个生理参数,运动能量消耗和体育体的体温。同时,为了提高健康手镯的耐久性,使用BP神经网络算法设计可变采样频率方案,并且可以根据心率频率确定所有物理健康信息。 STM32与主机组合使用来验证设计方法。它可以监测实时人类生理参数,并对人类健康信息的综合评估进行全面评估人类健康信息的变化。通过对实验结果的系统测试和分析,验证收集的生理数据基于改善耐久性的准确性更高。

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