Iffat Ara

Pabna University of Science and Technology | PUST · Department of Information and Communication Engineering

Electrocardiography (ECG) is recording of heart electrical activity. For analyzing and diagnosis of heart diseases ECG is very important. In graphical ECG which used for clinical diagnosis all features are not visible. Different types of signal processing methods are present which can be used for extracting ECG signal features. Wavelet transforms i...

EMG is the recording of the electrical activity produced within the muscle fibers. Measurement of EMG signal is corrupted by additive noise whose signal-to-noise ratio (SNR) varies. Feature extraction is an important step for EMG classification. Time domain and frequency domain parameters were chosen as representative features for EMG signals. In t...

Electrical activity is essential for the cardiac cell to perform its function. Mathematical modeling of cardiac electrical activity is performed from the cell, tissue and organ levels through to the body surface level. The electrical activity of the cardiac as a whole is thus characterized by a complex multiscale structure. The most complete model...

ECG signal plays an important role in the primary diagnosis and analysis of heart diseases. When an Electrocardiogram is recorded many kinds of noise are recorded. The aim of this paper is to use discrete wavelet transform (DWT) for de- noising the ECG signal. Text formatted ECG signals of ten second duration are taken from the MIT-BIH arrhythmia d...

ECG signal plays an important role in the primary diagnosis and analysis of heart diseases. The feature of ECG signal with time-varying morphological characteristics needs to be extracted by signal processing method because there are not clearly visible in the graphical ECG signal. For analyzing this kind of signal wavelet transforms are a powerful...