Study On Wearable Ambulatory Electrocardiogram Monitoring Systam And Electrocardiosignal Processing Method

In recent years, with the transformation of medical pattern from passive treatment to active prevention and monitoring, wearable computing technology-based healthcare monitoring is becoming a more effective model in the health of the elderly assisted areas. Wearable health monitoring fused electronic components, micro-electromechanical systems, electronic and advanced fabric technologies to assist patients achieve real-time monitoring and personalized health management. It will become one of the main research directions of modern medicine in the future.For ECG detection in wearable health monitoring, textile electrode based on different woven technologies has received wide research. However, because the textile electrodes may not always be close to skin in long-term monitoring situation and have the characteristics of low impedance, it is vulnerable for noise especially motion artifact noise in the case of human motion. Because motion artifact has a dynamic range of frequencies, large amplitude and damage or submerge biological signal easily, it is difficult to extract the characteristics of used signal. So how to design effective filtering algorithm to suppress the motion artifacts becomes a concerned problem for researchers.In view of the above analysis, this paper proposes a wearable healthcare system based on textile electrode allowing monitoring of ECG and demonstrated the motion artifact suppression method for arrhymia detection using the system. Wearable long-term ECG monitoring system is designed under human body movement and ECG motion artifact filtering algorithm is studied. Finally filtered ECG features are extracted and the heart rate variability is analyzed. The main contents are as follows:(1) Introducing the basic knowledge and detection principle of ECG analysis in wearable monitoring and diagnoses systems. Stating the ECG、typical ECG wave、ECG characteristics of each band and the implications for rehabilitation clinic. Analysis of the characteristics and detection methods of ECG, and several major noise signals in ECG acquisition process.(2) Designing wearable ECG monitoring system based on STM32 microprocessor. The system include textile ECG electrodes and basic modules to ensure the system works well, such as a signal conditioning module with high common mode rejection ratio and high input impedance for dynamic amplifying and filtering the signal to meet the voltage requirement of A/D conversion, data acquisition module, power module, data storage module, data transmission and data interface module. Signals are transmitted to the mobile devices(mobile phones, tablet computers, etc.) and PC for real-time displaying and analysis respectively. Finally, a PCB board with small size, strong reliability is designed.(3) Using adaptive filter to suppress the motion artifacts and the three-axis acceleration signal act as a reference signal to adaptive filter. Analyzing the structure of adaptive filter, the principle of NLMS adaptive filter algorithm and finally the ECG motion artifacts are suppressed by this method. After filtering the ECG signal adaptive threshold algorithm is used for R-wave detection to reduce the probability of false negative and false positive.