Naslov
A Comparative Study of FFT, DCT and DWT for Efficient Arrhytmia Classification in RP-RF Framework

Autori
Marasović, Tea ; Papić, Vladan

Izvornik
International Journal of E-Health and Medical Communications (1947-315X) 9 (2018), 1; 35-49

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
compressive sensing ; DCT ; DWT ; ECG classification ; FFT ; MIT-BIH ; random forest ; random projection

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo

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