| With the increasing of sudden cardiac death (SCD, also called sudden arrest), the developing of a reliable and portable electrocardiograph (ECG) monitor is imminent. There is no sign before it. According to statistics by AHA (American Heart Association), up to 30 percent of people died of a sudden death have no or never have heart disease. Almost all of them died outside of hospital. If the disease can be detected ahead and then treatment was carried out immediately, it can improve the opportunity of subsistence rate. Therefore, it is an important topic of forecasting a sudden death and life-threatening ventricular arrhythmia. Ventricular Fibrillation are malignant cardiac rhythm and easy to trigger the phenomenon of sudden cardiac death. The TWA test is non-invasive, and the more costly invasive electrophysiological study (EPS)—were compared for their ability to predict which patients were at highest risk for sudden cardiac death or a defibrillator shock. The detection of ventricular fibrillation (VF) and T-wave alternans (TWA) is the main content of this paper.For detecting VF, in this paper we proposed a new algorithm, which is based on support vector machine (SVM), Hurst index, and the time-delay algorithm [phase space reconstruction (PSR)]. The data sets were taken from the BIH-MIT database and the CU database. After data preprocessing, we obtained H and d values and then putted them into SVM, which was designed before and used for two classifications. Finally, the results putted out, VF and no VF classification could be realized. Besides the quality parameters Sensitivity and Specificity, we calculated the Positive Predictivity and Accuracy of the new algorithm. The result shows that the proposed algorithm has a high detection quality and outperforms all other investigated algorithms.T-wave alternans (TWA) is a variation in the amplitude or morphology of the T wave of the beat-to-beat ECG which provides a noninvasive and clinically useful marker for the risk of sudden cardiac death (SCD) caused by life threatening arrhythmias. Detection of beat-to-beat microvolt fluctuation of the T wave has been made possible with the use of advanced signal processing techniques and high-resolution electrodes to reduce ambient noise. Traditional spectral analysis of TWA needs precise positioning, in this paper, an algorithm based on the maximum of T waves is studied. Using the method can reduce sample rate, which means the amount of calculation can be reduced, and can solve the problem that the fixed T-wave sampling points can't change along with the change of heart rate. A time series of 128 amplitudes of corresponding points on the T wave are processed by fast Fourier transformation (FFT) to yield the spectral display with the various peaks. The result shows that the algorithm has a high detection quality and greatly reduces the amount of calculation.We devote our mind to developing an embedded portable electrocardiograph (ECG) monitor with wireless data communication; the easy-taking ECG monitoring system can detect the ventricular arrhythmia in time and give rise to an alarm at the same time. It possesses such traits as small volume, easy-taking, smart operations etc, and plays an important role in saving patients'life outside hospitals. In addition to high-quality algorithms, the choice of processors is also particularly important. ARM CortexTM-M3 processor mainly applied to embedded applications of high performance, extremely low cost requirements, such as: micro-controllers, automotive systems, large household appliances and network devices. The paper designs the key part of the hardware and the software of prototype in the core of the Cortex(tm)-M3 processor STM32F103. The hardware includes the collecting module and the data processing module (external storage and communication interface circuits). |
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