A Comparative Study of FFT, DCT and DWT for Efficient Arrhytmia Classification in RP-RF Framework (CROSBI ID 244105)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Marasović, Tea ; Papić, Vladan
engleski
A Comparative Study of FFT, DCT and DWT for Efficient Arrhytmia Classification in RP-RF Framework
Computer-aided ECG classification is an important tool for timely diagnosis of abnormal heart conditions. This paper proposes a novel framework that combines the theory of compressive sensing with random forests to achieve reliable automatic cardiac arrhythmia detection. Furthermore, the paper evaluates the characterization power of FFT, DCT and DWT data transformations in order to extract significant features that will bring the additional boost to the classification performance. The experiments – carried out over MIT-BIH benchmark arrhythmia database, following the standards and recommended practices provided by AAMI – demonstrate that DWT based features exhibit better performances compared to other two feature extraction techniques for a relatively small number of random projected coefficients, i.e. after considerable (approx. 85%) dimensionality reduction of the input signal. The results are very promising, suggesting that the proposed model could be implemented for practical applications of real-time ECG monitoring, due to its low-complexity.
compressive sensing ; DCT ; DWT ; ECG classification ; FFT ; MIT-BIH ; random forest ; random projection
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Podaci o izdanju
9 (1)
2018.
35-49
objavljeno
1947-315X
1947-3168
10.4018/IJEHMC.2018010103