Tachycardias Classification via the Generalized Mean Frequency and Generalized Frequency Variance of Electrocardiograms-Reference-Cited by-同舟云学术

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Tachycardias Classification via the Generalized Mean Frequency and Generalized Frequency Variance of Electrocardiograms

Published:2021-08-26 Issue:2 Volume:41 Page:1207-1222
ISSN:0278-081X
Container-title:Circuits, Systems, and Signal Processing
language:en
Short-container-title:Circuits Syst Signal Process

Author:

Ho Charlotte Yuk-Fan,Ling Bingo Wing-Kuen^ORCID,Deng Danny Xinghua,Liu Yuwei

Funder

National Nature Science Foundation of China

Team Project of the Education Ministry of the Guangdong Province

Guangdong Higher Education Engineering Technology Research Center for Big Data on Manufacturing Knowledge Patent

Hong Kong Innovation and Technology Commission, Enterprise Support Scheme

Shenzhen Science and Technology International Cooperation Research Project

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Signal Processing

Link

https://link.springer.com/content/pdf/10.1007/s00034-021-01819-1.pdf

Reference22 articles.

1. Y. Alwan, Z. Cvetković, M.J. Curtis, Methods for improved discrimination between ventricular fibrillation and tachycardia. IEEE Trans. Biomed. Eng. 65(10), 2143–2151 (2018)

2. J. Antoni, J. Schoukens, A comprehensive study of the bias and variance of frequency-response-function measurements: optimal window selection and overlapping strategies. Automatica 43(10), 1723–1736 (2007)

3. Database for performing the tachycardias classification. http://ecg.mit.edu

4. N. Glazkova, T. Podladchikova, R. Gerzer, D. Stepanova, Non-invasive wearable ECG-patch system for astronauts and patients on earth. Acta Astronaut. 166, 613–618 (2020)

5. C.Y.F. Ho, B.W.K. Ling, Y.Q. Liu, P.K.S. Tam, K.L. Teo, Efficient algorithm for solving semi-infinite programming problems and their applications to nonuniform filter bank designs. IEEE Trans. Signal Process. 54(11), 4223–4232 (2006)

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