Madina Hamiane and May Hashim Ali
WaveletBased ECG Signal Analysis and Classification
895 - 909
2017
11
7
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/10008031
https://publications.waset.org/vol/127
World Academy of Science, Engineering and Technology
This paper presents the processing and analysis of ECG signals. The study is based on wavelet transform and uses exclusively the MATLAB environment. This study includes removing Baseline wander and further denoising through wavelet transform and metrics such as signalto noise ratio (SNR), Peak signaltonoise ratio (PSNR) and the mean squared error (MSE) are used to assess the efficiency of the denoising techniques. Feature extraction is subsequently performed whereby signal features such as heart rate, rise and fall levels are extracted and the QRS complex was detected which helped in classifying the ECG signal. The classification is the last step in the analysis of the ECG signals and it is shown that these are successfully classified as Normal rhythm or Abnormal rhythm. The final result proved the adequacy of using wavelet transform for the analysis of ECG signals.
Open Science Index 127, 2017