N. Uchaipichat

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We report an improved method for the estimation of shock outcome prediction based on novel wavelet transform-based time-frequency methods. Wavelet-based peak frequency, energy, mean frequency, spectral flatness and a new entropy measure were studied to predict shock outcome. Of these, the entropy measure provided optimal results with 60 +/- 6% specificity(More)
The aim of this study was to examine whether wavelet transform analysis of the electrocardiogram (ECG) can improve the prediction of the maintenance of sinus rhythm in patients with atrial fibrillation (AF) after external DC cardioversion. We examined a variety of wavelet transform-based statistical markers as potential candidates for the prediction of(More)
This paper reports our study in QRS complex detection. The short-time Fourier transform (STFT) was employed in ECG filtering stage. The narrow rectangular window was used to transform ECG signals into time-frequency domain. The temporal information at 45 Hz from spectrogram was analyzed for detecting QRS locations. The automated thresholding combined with(More)
Atrial fibrillation (AF) is the most common arrhythmia that causes stroke. The paroxysmal atrial fibrillation (PAF) is a type of AF that is self-terminated in less than 7 days and can recur later. This paper proposed new markers from electrocardiogram (ECG) for PAF prediction. The heart rate variability (HRV) obtained from ECG was use in this investigation.(More)
This paper reports our study in digital image geometrical distortion correction. The Artificial Neural Network (ANN) was employed to correct the distorted digital image which is simulated in computer. The ANN was trained to map the distorted points to the distortion-free points. As the results, our proposed technique can correct the detected distort-points(More)
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