ABSTRACT
The article adopts the BP neural network and probability neural network in classifying four arrhythmias (LBBB, RBBB, Paced Beat, Ventricular Escape Beat) and one normal beat, and their test results of the automatic classification and imitation study are 97.62% and 95.88%, showing an improved efficient classification.
Subject(s)
Arrhythmias, Cardiac , Classification , Electrocardiography , Classification , Methods , Neural Networks, ComputerABSTRACT
As basic electrophysiology signals of a human being, electroencephalogram (EEG) has been widely used in researches and clinics. The paper proposes a method for extracting rhythms of EEG, based on wavelet analysis. By using Daubechies mother wavelet, raw EEG is decomposed, and then we extract basic rhythms of EEG after interference is eliminated insome scales. This method not only eliminates interference well, but also extracts rhythms perfectly.
Subject(s)
Humans , Algorithms , Brain , Physiology , Electroencephalography , Methods , Periodicity , Signal Processing, Computer-Assisted , Wavelet AnalysisABSTRACT
In this paper, we discuss image fusion methods within the space domain, transform domain and intelligence domain, where the emphasis is given to the fusion method based on image segment, wavelet transform, its extension, and semantic predication. Finally, some remarks upon prospects of medical image fusion are presented.