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ECG beat detection using filter banks.

V X Afonso·W J Tompkins·T Q Nguyen·S Luo
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Abstract

We have designed a multirate digital signal processing algorithm to detect heart beats in the electrocardiogram (ECG). The algorithm incorporates a filter bank (FB) which decomposes the ECG into subbands with uniform frequency bandwidths. The FB-based algorithm enables independent time and frequency analysis to be performed on a signal. Features computed from a set of the subbands and a heuristic detection strategy are used to fuse decisions from multiple one-channel beat detection algorithms. The overall beat detection algorithm has a sensitivity of 99.59% and a positive predictivity of 99.56% against the MIT/BIH database. Furthermore this is a real-time algorithm since its beat detection latency is minimal. The FB-based beat detection algorithm also inherently lends itself to a computationally efficient structure since the detection logic operates at the subband rate. The FB-based structure is potentially useful for performing multiple ECG processing tasks using one set of preprocessing filters.

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AlgorithmsDatabases, FactualElectrocardiographyEquipment DesignHeart RateHumansSensitivity and SpecificitySignal Processing, Computer-AssistedTime FactorsJournal ArticleResearch Support, Non-U.S. Gov't

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BibTeXRIS

V X Afonso, W J Tompkins, T Q Nguyen, S Luo. 1999. ECG beat detection using filter banks.. https://doi.org/10.1109/10.740882

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