Portable Multi-physiological Parameter Monitor Real-time Analysis And Software Design

With the continuous development of science and technology at home and abroad, socialmedical treatment had a huge promotion, and the mean life of people is increasing. People whoare enjoying their lives pay more and more attention at the same time to their health status. Themain focus of family medical treatment has changed from healing diseases to improving physicalquality, physiological parameters measurement tools such as thermometer, sphygmomanometerand blood glucose meter and so on, already have been widely used during people’s daily life.These years, the functions of medical monitor from simple diagnostic functions extend to themulti-functional aspects, and gradually extended to the family from the medical health caremarketplace. Nowadays, though multi-physiological parameters monitor is very powerful, it alsohas some shortcomings that keep it away from widely used, such as: professionalized, it must beoperated by professionals, and its information such as ECG can only be interpreted byprofessional doctor; bulky and expensive that normal family can’t afford. Therefore, develop amonitor that is convenient to operate, can be understood by person not having professionalknowledge, becomes the development trend.The thesis proposes a design of multi-physiological parameters monitor that can realizecollecting, analyzing, displaying in real-time. The function of physiological parametersacquisition is realized by OEM custom model with high-precision performance, upper computeris built by embedded hardware and Windows CE operating system. The monitor software mainlyachieves ECG automatic analysis. After received data, the ECG real-time analysis parts first dodata pre-processing, Median filter and smoothing filter are designed to restrain base line floatand AC interference. Based on the ē lead ECG wave features, differential gradient is chose torecognize QRS wave group position., then P wave and T wave are checked between every periodinterval. In order to improve accuracy of ECG automatic analysis, the software increased Offlinedata analysis algorithm that based on wavelet theory, in the algorithm multiresolution analysistheory and Singularity detection theory are used to recognize ECG wave. Firstly, Gauss waveletis used to do continuous wavelet transform (CWT) which will amplify the signal. Then, mallatalgorithm is used to break the signal down into different frequency bands, after filtering the reconstructed signal only has QRS spikes. When QRS wave groups are detected, CWT is usedagain between every interval to detect T waves and P waves, and finally we get the conclusion.