Architecture design of the multi-functional wavelet-based ECG microprocessor for realtime detection of abnormal cardiac events.
EMBC(2012)
摘要
Most of the abnormal cardiac events such as myocardial ischemia, acute myocardial infarction (AMI) and fatal arrhythmia can be diagnosed through continuous electrocardiogram (ECG) analysis. According to recent clinical research, early detection and alarming of such cardiac events can reduce the time delay to the hospital, and the clinical outcomes of these individuals can be greatly improved. Therefore, it would be helpful if there is a long-term ECG monitoring system with the ability to identify abnormal cardiac events and provide realtime warning for the users. The combination of the wireless body area sensor network (BASN) and the on-sensor ECG processor is a possible solution for this application. In this paper, we aim to design and implement a digital signal processor that is suitable for continuous ECG monitoring and alarming based on the continuous wavelet transform (CWT) through the proposed architectures--using both programmable RISC processor and application specific integrated circuits (ASIC) for performance optimization. According to the implementation results, the power consumption of the proposed processor integrated with an ASIC for CWT computation is only 79.4 mW. Compared with the single-RISC processor, about 91.6% of the power reduction is achieved.
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关键词
optimisation,electrocardiography,time delay,medical disorders,medical signal detection,power consumption,microprocessor chips,on-sensor ecg processor,wavelet transforms,body area networks,patient monitoring,reduced instruction set computing,multifunctional wavelet-based ecg microprocessor,programmable risc processor,continuous wavelet transform,asic,medical signal processing,myocardial ischemia,wireless body area sensor network,long-term ecg monitoring system,continuous electrocardiogram analysis,fatal arrhythmia,body sensor networks,digital signal processing chips,delays,application specific integrated circuits,realtime abnormal cardiac event detection,power 79.4 muw,performance optimization,acute myocardial infarction,architecture design,power reduction,biomedical electronics,digital signal processor
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