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Life Threatening Arrhythmias Classification using Nuclear Quadrupole Resonance Spectroscopy Signals

Journal: International Journal of Linguistics and Computational Applications (Vol.4, No. 1)

Publication Date:

Authors : ;

Page : 27-31

Keywords : Adaptive Wiener Filter; Wavelet Transform; Nuclear quadrupole resonance spectroscopy; Support vector machine;

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In this paper, Nuclear Quadrupole Resonance Spectroscopy signals of human recorded using called HTEC is analysed and compressed to classify Arrhythmias .The device is able to record medical quality which leads ECG signal from the patient's hearth by using dry electrodes and without any skin preparation or medical knowledge. Nuclear quadrupole resonance spectroscopy is a method of measuring the pattern activities of heart. Every portion of spectroscopy is very essential for the diagnosis of different cardiac problems. But the amplitude and duration of spectroscopy signal is usually corrupted by different noises. In this paper a broader study for denoising every types of noise involved with real spectroscopy signal and the type of adaptive filters are considered to reduce the spectroscopy signal Base Line Interference. Hence adaptive filters, now days, are used for artifact removal from spectroscopy signals and the adaptive filters update their coefficients according to the requirement. Spectroscopy is an essential clinical analytic apparatus for recognition of cardiovascular arrhythmias and also, RR interim data is processed to give dynamic elements. These two different types of features are concatenated and a support vector machine classifier is utilized for the classification of heartbeats into different classes. The procedure is independently applied to the data from two Spectroscopy leads and the two decisions are fused for the final classification decision.

Last modified: 2017-12-23 04:39:03