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Automatic EEG spike detection provide valuable information for diagnosis of epilepsy. In the past 30 years, a number of algorithms were proposed. However, the basic idea of most algorithms is to identify spike activities. We have developed an algorithm based on identify non-spike activities for off-line analysis. In this paper, we improved the algorithm for online application using real-time template...
A multi-channel template extraction method is proposed for automatic EEG spike detection. The template is extracted automatically without any prior knowledge. The template extraction algorithm consists of three steps. Firstly, all possible spike events are detected. Secondly, the focus channels are identified for each event. Thirdly, the multi-channel template is extracted for each focus channel....
Most automatic spike detection systems in the scalp electroencephalogram (EEG) focused on the characteristics of “spike.” However, the characteristics of “false positives” (FPs) have not been fully studied. In this paper, we proposed a system that contains a series of algorithms to eliminate FPs and a template method to confirm spikes. The system used large area context available on 49 channels from...
Electrocardiogram (EKG) and Electroencephalogram (EEG) are widely used for kinds of disorders detection. In case of EKG, RR interval series is used for heart rate variability (HRV) analysis, which is a reliable reflection of status of autonomic nervous system. HRV is a function of both physical and mental activity. In order to analyze the influence of metal stress on HRV, EKG signals including information...
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