A Review on ECG Signal Processing and HRV Analysis
A large section of world's population suffers from heart diseases because of different causes. The cardiac diseases may be found suddenly due to the conduction system failure of the heart leading to heart failure or they may be due to long term abnormalities found because of malfunctioning of the different parts of the heart. Though tremendous efforts have been put in finding the causes of heart diseases and treating the cardiac diseases with most sophisticated instrumentation, the post monitoring of the cardiac diseases is one of the important issue today. This requires the thorough knowledge of ECG and associated non invasive cardiac signals such as heart rate variability (HRV), blood pressure (BP) and their pre and post processing along with the knowledge of symptoms of the heart diseases. The review here provides the different pre and post processing techniques applied in ECG and HRV signal processing and analysis techniques applied for identification of cardiac diseases. The review emphasizes power spectral analysis after time-frequency decomposition of the non-invasive analysing signals. The spectral analysis carried out subsequently helps in selecting more number of statistical features which can quantify the subtle details revealing physiological conditions. Further using higher order spectra with spectral representations of higher order statistics also known as poly-spectra, it is possible to study the nonlinear behaviour of cardiac signals. Application of higher order spectra (HOS) has been the recent development for non-Gaussian, non-stationary behaviour of HRV.
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Document Type: Review Article
Publication date: June 1, 2013
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- Journal of Medical Imaging and Health Informatics (JMIHI) is a medium to disseminate novel experimental and theoretical research results in the field of biomedicine, biology, clinical, rehabilitation engineering, medical image processing, bio-computing, D2H2, and other health related areas.
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