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ECG artefact detection algorithm: An algorithm to improve long-term ECG analysis

Title
ECG artefact detection algorithm: An algorithm to improve long-term ECG analysis
Type
Article in International Conference Proceedings Book
Year
2012
Authors
Bras, S
(Author)
Other
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Ferreira, N
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
Conference proceedings International
Pages: 329-333
International Conference on Bio-inspired Systems and Signal Processing, BIOSIGNALS 2012
Vilamoura, Algarve, 1 February 2012 through 4 February 2012
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Other information
Authenticus ID: P-008-471
Abstract (EN): Newly devices allow the analysis and collection of very long-term electrocardiogram (ECG). However, associated with this devices and long-term signal, are artefacts that conduce to misleading interpretations and diagnosis. So, new developments over automatic ECG classification are needed for a reliable interpretation. The feasibility of the cardiac systems is one of the main concerns, once they are currently used as diagnosis or help systems. In this project, an artefact detection algorithm is developed, dividing the time-series in intervals of signal and artefact. The algorithm is based on the assumption that, if the analysed frame is signal, there is not an abrupt alteration over consecutive short windows. So, the time-series is divided in consecutive nonoverlapped short windows. Over these windows, it is calculated the time-series standard deviation, the maximum and minimum slope. A threshold-based rule is applied, and the algorithm reveals that, in mean, it is verified a 99.29% of correctly classified signal and only 0.71% of signal erroneously classified. Over the results obtained, the algorithm seems to present good results, however it is needed its validation in a wider and representative sample with segments marked as artefact by multiple specialists.
Language: English
Type (Professor's evaluation): Scientific
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