Ecg Signal Characteristic Parameter Detection Based On Embedded System Research

With economic development, improvement of living conditions and human lifestyle changes, cardiovascular disease not only has been the trend of high incidence, and has become "the first killer" that threat to human life and health. Its harm has no age, identity and geographical limit. According to statistics, there were about30%of the number of global deaths died of the disease, and there were about2.6million people died of the disease every year in our country. With the enhancement of people’s self-care awareness, its prevention and diagnosis that has become the main problem which is facing in present medical profession and has become the focus of attention.Electrocardiogram (ECG) is an important basis of the diagnosis of cardiovascular disease, has been widely used in clinical medicine. However, it is time-consuming and labor-consuming that the understanding and analysis of the clinical ECG rely mainly on labor for a long time. And expert analysts of ECG that Being Short. In order to change this situation, the domestic and foreign scholars have been committed to the research and development of automatic analysis system of ECGThe detection and analysis of the feature parameters of ECG signal that is the cornerstone of research and development of automatic analysis system of ECG. And the realization of analysis and diagnosis function of the automatic analysis system of ECG that based on the detection and analysis of the feature parameters of ECG signal. This paper study for the purpose of develops the portable electrocardiograph, and committed to studying the Detection and Analysis Algorithm which is used in detecting and analyzing the feature parameters of ECG signal. First, it detects QRS complex with regional extreme value detecting algorithm that Combined with corresponding relationship between the signal feature and the one or two scale wavelet coefficient of quadratic B-spline wavelet transform in previous studies; Secondly, it detects P wave, T wave and their starting points and end points with regional baseline algorithm based on the detection of QRS complex; At last, it uses a simple and effective way to achieve the recognition of the shape and amplitude of the ST segment which has a great significance in clinical medicine.The algorithm that had been programmed in the MATLAB experimental platform, had been verified with the standard ECG database of MIT-BIH and clinical ECG data, and had been transplanted into32bits high-speed ARM platform which had been embedded the real-time operating system of μC/OS-Ⅱ. Testing found that the system is completely meet the need of real-time and with high accuracy when analysis the ECG signal which does not contain the extremely complex and varied ECG signal.