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Today, many bio-signals such as Electroencephalography (EEG) are recorded in digital format. It is an emerging research area of analyzing these digital bio-signals to extract useful health information in biomedical engineering. In this paper, a bio-signal analyzing cloud computing architecture, called BACCA, is proposed. The system has been designed with the purpose of seamless integration into the...
Bio-signal analysis is one of the most important approaches to biomedical engineering. The health information such as ECG, PCG, EMG and EEG are often recorded in digital format to be analyzed. In this paper, a bio-signal analyzing Web service system using Support Vector Machines (SVM) classifier technique is proposed. The bio-signals are recorded in digital format as the input of the system. In addition,...
Sudden cardiac death (SCD) is one of continuing challenges to the modern clinician. It is responsible for an estimated 400,000 deaths per year in the United States and millions of deaths worldwide. This research developed a personal cardiac homecare system by sensing Lead-I ECG signals for detecting and predicting SCD events, which also builds in ECG identity verification. A MIT/BIH SCD Holter database...
Electrocardiogram (ECG) analysis is one of the most important approaches to cardiac arrhythmia detection. This paper proposed an ECG analysis approach with adaptive feature selection and support vector machines (SVMs). Many wavelet transform-based coefficients are used as candidates, but only a few coefficients are selected for classification problem of each class pair. In addition, the several variation...
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