Comput Methods Programs Biomed - An R-peak detection method that uses an SVD filter and a search back system.

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Resumo

In this paper, we present a method for detecting the R-peak of an ECG signal by using an singular value decomposition (SVD) filter and a search back system. The ECG signal was detected in two phases: the pre-processing phase and the decision phase. The pre-processing phase consisted of the stages for the SVD filter, Butterworth High Pass Filter (HPF), moving average (MA), and squaring, whereas the decision phase consisted of a single stage that detected the R-peak. In the pre-processing phase, the SVD filter removed noise while the Butterworth HPF eliminated baseline wander. The MA removed the remaining noise of the signal that had gone through the SVD filter to make the signal smooth, and squaring played a role in strengthening the signal. In the decision phase, the threshold was used to set the interval before detecting the R-peak. When the latest R-R interval (RRI), suggested by Hamilton et al., was greater than 150% of the previous RRI, the method of detecting the R-peak in such an interval was modified to be 150% or greater than the smallest interval of the two most latest RRIs. When the modified search back system was used, the error rate of the peak detection decreased to 0.29%, compared to 1.34% when the modified search back system was not used. Consequently, the sensitivity was 99.47%, the positive predictivity was 99.47%, and the detection error was 1.05%. Furthermore, the quality of the signal in data with a substantial amount of noise was improved, and thus, the R-peak was detected effectively.

Resumo Limpo

paper present method detect rpeak ecg signal use singular valu decomposit svd filter search back system ecg signal detect two phase preprocess phase decis phase preprocess phase consist stage svd filter butterworth high pass filter hpf move averag ma squar wherea decis phase consist singl stage detect rpeak preprocess phase svd filter remov nois butterworth hpf elimin baselin wander ma remov remain nois signal gone svd filter make signal smooth squar play role strengthen signal decis phase threshold use set interv detect rpeak latest rr interv rri suggest hamilton et al greater previous rri method detect rpeak interv modifi greater smallest interv two latest rris modifi search back system use error rate peak detect decreas compar modifi search back system use consequ sensit posit predict detect error furthermor qualiti signal data substanti amount nois improv thus rpeak detect effect

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