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.

随着现代化进程的加快和生活质量的显着提高，越来越多的人开始关注自己的健康。运动健康以其自然而健康的方式已成为大多数人的首选。因此，出现了具有步数计数功能的设备，例如智能手环和智能电话。本文提出了一种以多种采样频率测量人体多种生理参数的设计方法。它收集运动人体的血氧饱和度，运动能量消耗和体温的三个生理参数。同时，为了提高健康手镯的耐力，使用BP神经网络算法设计了可变采样频率方案，并可以根据心律频率确定所有身体健康信息。STM32结合上位机用于验证设计方法。它可以监视人类的实时生理参数，并对人类健康进行全面评估，记录人类健康信息的变化。通过系统测试和实验结果分析，验证了所采集的生理数据在提高耐力的基础上具有更高的准确性。