ECG compression: evaluation of FFT, DCT, and WT performance.
This work investigates a set of ECG data compression schemes to compare their performances in compressing and preparing ECG signals for automatic cardiac arrhythmia classification. These schemes are based on transform methods such as fast Fourier transform (FFT), discrete cosine transform (DCT), wavelet transform (WT), and their combinations. Each specific transform is applied to a pre-selected data segment from the MIT-BIH database and then compression is performed in the new domain. These transformation methods are known as an important class of ECG compression techniques. The WT has been shown as the most efficient method for further improvement. A compression ratio of 7.98 to 1 has been achieved with a percent of root mean square difference (PRD) of 0.25%, indicating that the wavelet compression technique offers the best performance over the other evaluated methods.
School of Engineering, Flinders University of South Australia, Bedford Park, SA.
H
H
GholamHosseini
H
H
Nazeran
B
B
Moran
D000465:Algorithms; D001699:Biometry; D003627:Data Interpretation, Statistical; D004562:Electrocardiography / Q000706:statistics & numerical data*; D005069:Evaluation Studies as Topic; D005583:Fourier Analysis; D006801:Humans