Abstract :
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.
Keyword :
— Adaptive Wiener Filter, Wavelet Transform, Nuclear quadrupole resonance spectroscopy, Support vector machine