The DOI matches its Crossref record.
A Digital Filter for the QRS Complex Detection
Abstract
The five step digital filter has been developed which removes components other than those of QRS complex from the recorded electrocardiogram (ECG). The final step of the filter produces a square wave whose on-intervals correspond to the segments with QRS complexes in the original wave.
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Citations
Cited by
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
A comparison of the noise sensitivity of nine QRS detection algorithms
Friesen, G. M., Jannett, T. C., Jadallah, M. A., Yates, S. L., Quint, S. R., & Nagle, H. T. (1990) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.43620 · Cited by 1,043
Wavelet transform-based QRS complex detector
Kadambe, S., Murray, R., & Boudreaux-Bartels, G. F. (1999) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.771194 · Cited by 441
Respiratory sinus arrhythmia in new‐born infants.
Hathorn, M. K. (1987) · The Journal of Physiology · doi:10.1113/jphysiol.1987.sp016480 · Cited by 47
Metadata
- Authors
- Okada, M.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 1979-12
- Volume
- BME-26
- Issue
- 12
- Pages
- 700-703
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W2006467905
- Cited by
- 218
- References
- 0
- FWCI
- 0.35
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A Digital Filter for the QRS Complex Detection. https://app.cochat.ai/papers/10.1109/tbme.1979.326461
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- Okada, M. (1979). A Digital Filter for the QRS Complex Detection. IEEE Transactions on Biomedical Engineering. https://doi.org/10.1109/tbme.1979.326461
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
