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This paper highlights a new method for ECG segmentation based on the combination of two mathematical techniques namely the wavelet transform (WT) and hidden Markov models (HMM). In this method, we first localize edges in the ECG by wavelet coefficients, then, features extracted from the edges serve as input for the HMM. This new approach was tested and(More)
The method described in this paper deals with the problems of T-wave detection in an ECG. Determining the position of a T-wave is complicated due to the low amplitude, the ambiguous and changing form of the complex. A wavelet transform approach handles these complications therefore a method based on this concept was developed. In this way we developed a(More)
In this paper, we present a new design of a psychoacoustic model following the example model used in audio standard MPEG-1 layer 3 with the gammachirp wavelet packet decomposition. The essential characteristic of this model is that it proposes an analysis by wavelet packet transformation on the frequency bands that come closer the critical bands of the ear(More)
In this paper we develop a new approach to ECG analysis, combining Pitch Synchronous Wavelet Transform (PSWT) and Hidden Semi-Markov Model (HSMM) for tracking the typical ECG cycle. The combination of these two techniques was examined in a way that the PSWT of an ECG signal was an input for the HSMM. This approach was tested and evaluated on the manually(More)
This paper describes a recognition system based on diverse features combination for the automatic heartbeat recognition purpose. The method consists of three stages: at the first stage, we extract a set of features including the morphological ones, high order statistics and pitch synchronous decomposition from ECG data using QT database; at the second(More)
This paper describes a new design of a psychoacoustic model for audio coding following the model used in the standard MPEG-1 audio layer 3 using an appropriate wavelet packet decomposition of the speech/audio signal. The design of a psychoacoustic model is achieved by wavelet packet decomposition whose connections are selected in such a way that sub bands(More)
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