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|Title:||Embedded real-time feature extraction for electrode inversion detection in telemedicine electrocardiograms.|
|Authors:||Torres, Vitor Angelo Maria Ferreira|
Silva, D. A.C.
Torres, Luiz Carlos Bambirra
Braga, Mateus T.
Cardoso, M. B. R.
Lino, Vinicius Terra
Torres, Frank Sill
Braga, Antônio de Pádua
|Citation:||TORRES, V. A. M. F. et al. Embedded real-time feature extraction for electrode inversion detection in telemedicine electrocardiograms. Biomedical Signal Processing and Control, v. 60, 2020. Disponível em: <https://www.sciencedirect.com/science/article/pii/S1746809420301026>. Acesso em: 29 abr. 2022.|
|Abstract:||Early detection of technical errors in medical examinations, especially in remote locations, is of utmost importance in order to avoid invalid measurements that would require costly and time consuming repeti- tions. This paper proposes a highly efficient method for the identification of an erroneous inversion of the measuring electrodes during a multichannel electrocardiogram. Therefore, a widely applied approach for heart beat detection is modified and approximated feature extraction techniques are employed. In con- trast to existing works, the improved heart beat identification requires no removal of baseline wandering and no amplitude related thresholds. Furthermore, a piecewise linear approximation of the baseline and basic calculations are sufficient for extracting the cardiac axis, which allows the construction of a clas- sifier capable of quickly detecting electrode reversals. Our implementation indicates that the proposed method has minimal hardware costs and is able to operate in real-time on a simple micro-controller.|
|Appears in Collections:||DECSI - Artigos publicados em periódicos|
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