A dynamic Fourier series for the compression of ECG using FFT and adaptive coefficient estimation.
In this article, a new ECG data compression technique is proposed. The method relies on modelling quasi-periodic ECG signals as a dynamic Fourier series. Fourier coefficients are continuously estimated using either an FFT algorithm or the adaptive least mean square algorithm. Results from simulated normal and pathological ECGs are presented and discussed. The merits of each of the above two methods are also illustrated. Furthermore, a comparison with other compression techniques is also discussed.
al-Nashash
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Electronic Engineering Department, Hijjawi Faculty for Applied Engineering, Yarmouk University, Irbid, Jordan.
D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000175:diagnosis / Q000503:physiopathology; D001698:Biomedical Engineering; D004562:Electrocardiography / Q000379:methods* / Q000706:statistics & numerical data; D015716:Electrocardiography, Ambulatory / Q000379:methods / Q000706:statistics & numerical data; D005583:Fourier Analysis; D006801:Humans; D008955:Models, Cardiovascular; D015233:Models, Statistical; D012815:Signal Processing, Computer-Assisted