IEEE J Biomed Health Inform - A low-complexity ECG feature extraction algorithm for mobile healthcare applications.

Tópicos

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Resumo

This paper introduces a low-complexity algorithm for 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 processing takes place in low-power, computationally constrained devices, thus the power consumption and complexity of the processing algorithms 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. The resulting algorithm is a hybrid scheme of time and frequency domain signal processing. Feature extraction results from 27 ECG signals from QTDB, were tested against manual annotations and used to compare our approach against the state-of-the art ECG delineators. In addition, 450 signals from the 15-lead PTBDB are used 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 being the number of input samples), reveals that the proposed method achieves an ideal trade-off between computational complexity and performance, a key requirement in remote CVD monitoring systems.

Resumo Limpo

paper introduc lowcomplex algorithm extract fiduci point electrocardiogram ecg applic area consid remot cardiovascular monitor continu sens process take place lowpow comput constrain devic thus power consumpt complex process algorithm remain minimum level context choos employ discret wavelet transform dwt haar function mother wavelet princip analysi method modulusmaxima analysi dwt coeffici approxim ecg fiduci point extract initi find compliment refin stage base timedomain morpholog properti ecg allevi decreas tempor resolut dwt result algorithm hybrid scheme time frequenc domain signal process featur extract result ecg signal qtdb test manual annot use compar approach stateofth art ecg delin addit signal lead ptbdb use evalu obtain perform cse toler limit find indic one cse limit satisfi level perform combin complex analysi upper bound propos algorithm term arithmet oper calcul n addit n multipl n n addit n multipl n n number input sampl reveal propos method achiev ideal tradeoff comput complex perform key requir remot cvd monitor system

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