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Automated ECG diagnosis (AED) & classification is essential to the timely diagnosis of potentially lethal heart conditions in clinical settings. In noisy environment, ECG feature extraction problem with considerable accuracy still remains open for research. Although, Wavelet Transform (WT) has been proved to be more prominent approach than other conventional detection algorithms, but much abstruse to implement in commercial medical software. To reduce this implementation complexity, in this work, a combination of DWT and FFT-IFFT pair is proposed with Adaptive thresholding technique. MATLAB…mehr

Produktbeschreibung
Automated ECG diagnosis (AED) & classification is essential to the timely diagnosis of potentially lethal heart conditions in clinical settings. In noisy environment, ECG feature extraction problem with considerable accuracy still remains open for research. Although, Wavelet Transform (WT) has been proved to be more prominent approach than other conventional detection algorithms, but much abstruse to implement in commercial medical software. To reduce this implementation complexity, in this work, a combination of DWT and FFT-IFFT pair is proposed with Adaptive thresholding technique. MATLAB analysis supports this preprocessing and automatic detection idea in terms of accuracy. A software implementation of this AED system is presented here in .net framework which can be interfaced with any commercial ECG machine only by changing some parameters.
Autorenporträt
Masudul Haider Imtiaz has received M.Sc'2009 and B.Sc. Hons'2008 from the Dept. of Applied Physics, Electronics & Communication Eng, University of Dhaka, Bangladesh. He is currently employed as a Lecturer in the Dept of ECE of the Institute of Science and Technology (IST), affiliated Inst. of National University, Bangladesh since September, 2012.