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Neural-network-based adaptive matched filtering for QRS detection
Abstract
We have developed an adaptive matched filtering algorithm based upon an artificial neural network (ANN) for QRS detection. We use an ANN adaptive whitening filter to model the lower frequencies of the ECG which are inherently nonlinear and nonstationary. The residual signal which contains mostly higher frequency QRS complex energy is then passed through a linear matched filter to detect the location of the QRS complex. We developed an algorithm to adaptively update the matched filter template from the detected QRS complex in the ECG signal itself so that the template can be customized to an individual subject. This ANN whitening filter is very effective at removing the time-varying, nonlinear noise characteristic of ECG signals. Using this novel approach, the detection rate for a very noisy patient record in the MIT/BIH arrhythmia database is 99.5%, which compares favorably to the 97.5% obtained using a linear adaptive whitening filter and the 96.5% achieved with a bandpass filtering method.
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Citations
Cites
A Real-Time QRS Detection Algorithm
Pan, J., & Tompkins, W. J. (1985) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.1985.325532 · Cited by 7,855
Self-citation
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The principles of software QRS detection
Kohler, B.-U., Hennig, C., & Orglmeister, R. (2002) · IEEE Engineering in Medicine and Biology Magazine · doi:10.1109/51.993193 · Cited by 1,242
The use of the Hilbert transform in ECG signal analysis
Benitez, D., Gaydecki, P. A., Zaidi, A., & Fitzpatrick, A. P. (2001) · Computers in Biology and Medicine · doi:10.1016/s0010-4825(01)00009-9 · Cited by 489
Current methods in electrocardiogram characterization
Martis, R. J., Acharya, U. R., & Adeli, H. (2014) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2014.02.012 · Cited by 278
A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising
Chen, S.-W., Chen, H.-C., & Chan, H.-L. (2006) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2005.11.012 · Cited by 264
Qiu, S., Feng, J., Xu, R., Xu, J., Wang, K., He, F., Qi, H., Zhao, X., Zhou, P., Zhang, L., et al. (2015) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2015.2407834 · Cited by 39
Metadata
- Authors
- Xue, Q., Hu, Y. H., & Tompkins, W. J.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 1992-04
- Volume
- 39
- Issue
- 4
- Pages
- 317-329
- ISSN
- 0018-9294 (ISSN-L)
- OpenAlex
- W2117911070
- Cited by
- 423
- References
- 1
- FWCI
- 3.73
- Type
- journal article
- Language
- en
- Open access
- closed
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- Xue, Q., Hu, Y. H., & Tompkins, W. J. (1992). Neural-network-based adaptive matched filtering for QRS detection. IEEE Transactions on Biomedical Engineering. https://doi.org/10.1109/10.126604
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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