Key result
Frequency-plane analysis of ECG signals using Discrete Fourier transform demonstrated significantly different amplitude and phase properties between normal and diseased subjects.
Frequency-plane analysis of digitized ECG signals reveals significant differences in amplitude and phase properties between normal and diseased subjects, potentially aiding in automated disease identification.
In this paper a frequency plane analysis of both normal and diseased ECG signals is performed specifically for disease identification. Image processing techniques are used to develop an automated data acquisition package of 12 lead ECG signals from paper records. A regeneration domain is also developed to check the captured pattern with the original wave shape. A QRS complex detector with an accuracy level approximately 98.4% in up to 30% signal to noise level is developed. Discrete Fourier transform (DFT) is performed to obtain the frequency spectrum of every ECG signal. Some interesting amplitude and phase response properties of chest lead V2, V3, V4, V6 and limb lead I, II, III, AVL, AVF are seen. Both amplitude and phase properties are different for normal and diseased subjects and can serve an important role in disease identification. A statistical analysis of amplitude property is carried out to show that this property is significantly different for normal and diseased subjects.
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Mitra et al. (2005) studied Normal and pathological ECG signals. Frequency-plane analysis vs. Normal ECG signals was evaluated on Amplitude and phase response properties. Frequency-plane analysis of ECG signals using Discrete Fourier transform demonstrated significantly different amplitude and phase properties between normal and diseased subjects.
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