Abstract
Sudden cardiac death (SCD) is one of the most prominent causes of death among patients with cardiac diseases. Since ventricular arrhythmia is the main cause of SCD and it can be predicted by T wave alternans (TWA), the detection of TWA in the body-surface electrocardiograph (ECG) plays an important role in the prevention of SCD. But due to the multi-source nature of TWA, the nonlinear propagation through thorax, and the effects of the strong noises, the information from different channels is uncertain and competitive with each other. As a result, the single-channel decision is one-sided while the multichannel decision is difficult to reach a consensus on. In this paper, a novel multichannel decision-level fusion method based on the Dezert-Smarandache Theory is proposed to address this issue. Due to the redistribution mechanism for highly competitive information, higher detection accuracy and robustness are achieved. It also shows promise to low-cost instruments and portable applications by reducing demands for the synchronous sampling. Experiments on the real records from the Physikalisch-Technische Bundesanstalt diagnostic ECG database indicate that the performance of the proposed method improves by 12%-20% compared with the one-dimensional decision method based on the periodic component analysis.
Highlights
Sudden cardiac death (SCD) is known for its suddenness and high mortality rate.[1,2] Some researches show that in developed countries, 1 out of 1000 subjects die every year due to SCD, which is almost 20% of all deaths.[3,4] According to the statistical results from the American Heart Association, the survival rate of the out-of-hospital cardiac arrests is only 5%.5 Unless cardiopulmonary resuscitation is performed within several minutes after the cardiac arrest, the chance of survival would be very slim.[6]
The cause of most SCDs is the ventricular arrhythmia, which can be predicted by T wave alternans (TWA) in the body-surface electrocardiogram (ECG).[7,8]
After the channel-by-channel characteristic parameter extraction, a decision-level fusion method derived from the proportional conflict redistribution rule no. 6 (PCR6) from the DSmT41 is performed to fuse this competitive information from different channels in a reasonable and comprehensive way
Summary
Sudden cardiac death (SCD) is known for its suddenness and high mortality rate.[1,2] Some researches show that in developed countries, 1 out of 1000 subjects die every year due to SCD, which is almost 20% of all deaths.[3,4] According to the statistical results from the American Heart Association, the survival rate of the out-of-hospital cardiac arrests is only 5%.5 Unless cardiopulmonary resuscitation is performed within several minutes after the cardiac arrest, the chance of survival would be very slim.[6]. In order to detect TWA as accurate as possible, instruments with custom-designed signal processing methods are needed. To reach a consensus on the final decision, most existing methods just get rid of partial information to reduce conflict. A multichannel hard-decision strategy called “OR” is to choose one channel, which is supposed to have a higher detection accuracy than others, to make the final decision. The information is fully used in the TWA estimation by linear transformation while the “OR” strategy is performed in the decision process. Considering the multi-dimensional nature of TWA, these methods based on the one-dimensional signal make the final decision with a relatively low information utilization rate. Due to the channel-by-channel design, it provides a possibility of extending the multichannel TWA detection to low-cost and portable applications
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