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Detection Of Heart Disease In ECG Signals Using Spectral Estimations

Norhashimah, Mohd Saad and Abdul Rahim, Abdullah (2006) Detection Of Heart Disease In ECG Signals Using Spectral Estimations. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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This research presents the use of signal processing techniques for the detection of heart blocks in electrocardiogram (ECG) signals. Spectral estimations such as periodogram power spectrum, Blackman-Tukey power spectrum and spectrogram time-frequency distribution technique are proposed to analyze ECG variations. Window functions are applied to the signals which are Boxcar, Hamming and Bartlett. Analysis results revealed that the periodogram power spectrum with Boxcar window can be used to differentiate between normal and heart block subjects, while the spectrogram time-frequency distribution is used to give better characterization of ECG parameters in terms of three- dimension (time, frequency and power intensity). The analysis can be used to construct ECG monitoring and classification system for heart blocks detection.

Item Type: Monograph (Project Report)
Uncontrolled Keywords: Biomedical engineering, Time-series analysis, Electrocardiography, Signal processing
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Library > Projek Jangka Panjang / Pendek > FKEKK
Depositing User: Siti Syahirah Ab Rahim
Date Deposited: 27 May 2014 02:30
Last Modified: 28 May 2015 04:25

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