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

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.