Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/8899
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Simjanoska, Monika | en_US |
dc.contributor.author | Koteska, Bojana | en_US |
dc.contributor.author | Madevska Bogdanova, Ana | en_US |
dc.contributor.author | Ackovska, Nevena | en_US |
dc.contributor.author | Trajkovikj, Vladimir | en_US |
dc.contributor.author | Kostoska, Magdalena | en_US |
dc.date.accessioned | 2020-09-05T15:02:37Z | - |
dc.date.available | 2020-09-05T15:02:37Z | - |
dc.date.issued | 2018-01-01 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12188/8899 | - |
dc.description.abstract | Low-cost biosensors combined with low-cost portable devices can be very useful in time critical situations of mass casualties, when fast triage procedure must be attained. A methodology that uses ECG to derive the vital parameters (heart rate and respiratory rate) needed for the triage procedure is presented and it is aimed to leverage affordable low-cost equipment that can be easily utilized by urgent medical units or even volunteers in events of considerable number of injured civilians. The methodology relies on selected well-known and published algorithms for heart rate and respiratory rate derivation from a given ECG signal. It consists of methods for R-wave detection, kurtosis computation, smoothing, and finding peaks. The proposed approach is shown to offer a good trade-off between the accurate measurement of the parameters and their fast derivation. It has been evaluated by using a publicly available database. Its robustness is measured in terms of accuracy estimation, showing a sensitivity of 0.87 for heart rate and 0.74 for respiratory rate, a sensitivity of 0.76 considering the triage process and an average-case execution time of 0.02 seconds, making it suitable for real-time applications. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Technology and health care : official journal of the European Society for Engineering and Medicine | en_US |
dc.title | Automated triage parameters estimation from ECG | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.3233/THC-171166 | - |
dc.identifier.volume | 26 | - |
dc.identifier.issue | 2 | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
Appears in Collections: | Faculty of Computer Science and Engineering: Journal Articles |
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