Physiological Signal Detection System Based On The Eyeglass Frame

Cardiovascular disease is the world’s leading cause of death, cardiovascular disease is a group of heart and vascular disease, once diagnosed, the cure rate is low, if early diagnosis and treatment, It will greatly enhance the success rate. Special emphasis has been given to the methods that allow the monitoring of the blood pressure and the arterial pulse waveform. Therefore, it is necessary to research and design a portable physiological signal monitoring equipment, long-term physiological signal detection, it can be found early symptoms of the disease, early intervention. This design of physiological signal detection system based on the principle of photoelectric plethysmography (PPG), the reflected light intensity signal through research and analysis results related physiological parameters to detect persons.In this paper, two aspects of the work completed:design a wearable, low-power multi-physiological signal detection system. Photoelectric sensors fixed on the front-end of eyeglass, to get a good pulse signal, without affecting the daily lives of those measurements. Integrated analog front end to convert the PPG signal to a digital signal. PPG signal and the acceleration signal is transmitted through Bluetooth low energy to the mobile client; on the phone side, the pulse signal is low-pass filtered and in turn to direct treatment, can effectively remove most of the noise, due to the different frequency bands of heart rate signals and respiration signals, low-pass filter can be used to extract the respiration signal from the PPG signal, VPD algorithm can effectively identify the real peak point, breathing rate and heart rate can be calculated by the spacing between adjacent peaks. Used acceleration signal as the reference signal for adaptive filtering algorithm, can effectively filter out the process of walking motion artifacts, improving the signal to noise ratio of the pulse signal.This paper consists of hardware circuit design and software design. Through the analysis of the PPG signal actually measured, effective algorithms was designed to process and analyze the PPG signal. The pulse parameters for improving the diagnostic accuracy by eight volunteers was found with high accuracy under static conditions for walking and physiological parameters measured, it can be effectively used for health monitoring...