The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Open source ECG analysis
Abstract
Each year companies and researchers expend significant resources developing basic beat detection and classification software. In an effort to reduce this duplication of effort we are developing and making available open source ECG analysis software. Our open source QRS detectors have sensitivities and positive predictivities that are close to 99.8% on the MIT/BIH and AHA arrhythmia databases. Our beat classifier has a sensitivity of 93.91% and a positive predictivity of 96.48% on the MIT/BIH arrhythmia database and a sensitivity of 93.2% and a positive predictivity of 97.83% on the AHA arrhythmia database. Since we have posted our source code, over 350 users have downloaded our ECG analysis software. Downloads have been nearly equally divided between students, researchers, and commercial developers.
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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
Cited by
Bota, P. J., Wang, C., Fred, A. L. N., & Placido Da Silva, H. (2019) · IEEE Access · doi:10.1109/access.2019.2944001 · Cited by 322
ECG signal analysis through hidden Markov models
Andreao, R. V., Dorizzi, B., & Boudy, J. (2006) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2006.877103 · Cited by 293
Sleep stage classification from heart-rate variability using long short-term memory neural networks
Radha, M., Fonseca, P., Moreau, A., Ross, M., Cerny, A., Anderer, P., Long, X., & Aarts, R. M. (2019) · Scientific Reports · doi:10.1038/s41598-019-49703-y · Cited by 186
Cao, R., Azimi, I., Sarhaddi, F., Niela-Vilen, H., Axelin, A., Liljeberg, P., & Rahmani, A. M. (2022) · Journal of Medical Internet Research · doi:10.2196/27487 · Cited by 159
Context-aware experience sampling reveals the scale of variation in affective experience
Hoemann, K., Khan, Z., Feldman, M. J., Nielson, C., Devlin, M., Dy, J., Barrett, L. F., Wormwood, J. B., & Quigley, K. S. (2020) · Scientific Reports · doi:10.1038/s41598-020-69180-y · Cited by 124
Metadata
- Authors
- Hamilton, P.
- Venue
- Computers in Cardiology
- Publisher
- IEEE
- Published
- 2003-08-27
- Pages
- 101-104
- ISSN
- 0276-6574 (ISSN-L)
- OpenAlex
- W2160439670
- Cited by
- 380
- References
- 1
- FWCI
- 5.95
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Hamilton, P. (2003). Open source ECG analysis. Computers in Cardiology. https://doi.org/10.1109/cic.2002.1166717
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
