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A Low-Complexity ECG Feature Extraction Algorithm for Mobile Healthcare Applications

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Abstract—Thispaperintroducesalow-complexityalgorithmfor the extraction of the fiducial points from the electrocardiogram (ECG). The application area we consider is that of remote cardiovascular monitoring, where continuous sensing and processingtakesplaceinlow-power,computationallyconstraineddevices, thusthepowerconsumptionandcomplexityoftheprocessingalgorithms should remain at a minimum level. Under this context, we choose to employ the discrete wavelet transform (DWT) with the Haar function being the mother wavelet, as our principal analysis method. From the modulus-maxima analysis on the DWT coefficients, an approximation of the ECG fiducial points is extracted. These initial findings are complimented with a refinement stage, based on the time-domain morphological properties of the ECG, which alleviates the decreased temporal resolution of the DWT. Theresultingalgorithmisahybridschemeoftime-andfrequencydomain signal processing. Feature extraction results from 27 ECG signals from QTDB were tested against manual annotations and usedtocompareourapproachagainstthestate-of-theartECGdelineators.Inaddition,450signalsfromthe15-leadPTBDBareused to evaluate the obtained performance against the CSE tolerance limits. Our findings indicate that all but one CSE limits are satisfied. This level of performance combined with a complexity analysis, where the upper bound of the proposed algorithm, in terms of arithmetic operations, is calculated as 2.423N + 214 additions and 1.093N + 12 multiplications for N ≤ 861 or 2.553N + 102 additions and 1.093N + 10 multiplications for N>861 (N beingthenumberofinputsamples),revealsthattheproposedmethod achieves an ideal tradeoff between computational complexity and performance, a key requirement in remote cardiovascular disease monitoring systems.

IndexTerms—Discretewavelettransform(DWT),electrocardiogram (ECG) feature extraction, low complexity algorithm, mobile healthcare.

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Informasi Detail

Judul Seri

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No. Panggil

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Penerbit

: ., 2013

Deskripsi Fisik

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, VOL. 17, NO. 2, MARCH 2013 p.459-469

Bahasa

English

ISBN/ISSN

2168-2194

Klasifikasi

NONE

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

KEDOKTERAN-ALAT DAN PERLENGKAPAN

Info Detail Spesifik

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Pernyataan Tanggungjawab

Evangelos B. Mazomenos ... [et al.]

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