Abstract:In view of the high mortality rate of cardiovascular disease and the phenomenon of population aging, this article develops a wearable health monitoring system based on STM32 microcontroller and wavelet adaptive threshold filtering algorithm. The system can be divided into several parts, such as system microprocessor, digital system module, human-computer interaction module, signal acquisition module and wireless communication module, which are processed and analyzed for important physiological parameters such as human heart rate, blood oxygen, and body temperature, and then monitor the human body in real time. The system processor selects STM32F103C8T6 as the control chip, and the display module uses OLED. The physiological parameter acquisition system uses the MAX30102 sensor and the Pulse sense sensor to collect the heart rate of the human wrist and fingertips, respectively. After the physiological parameters are collected, the physiological characteristics of the human body are recorded by further A/D conversion, based on the proposed improved wavelet adaptive threshold filtering algorithm to reduce noise filtering. The collected data is then transmitted to the mobile phone through Bluetooth, and the ZigBee module is mainly to transmit the obtained data to the remote control terminal again, so that patients can get better medical monitoring remotely. The system is a combination of software and hardware. Finally, the error of the center rate (BPM) result is 2 BPM, and the error of the blood oxygen content monitoring result is within 2%.
