COVID-19 Detection by Means of ECG, Voice, and X-ray Computerized Systems: A Review

Ribeiro, Pedro; Marques, João Alexandre Lobo; Rodrigues, Pedro Miguel

doi:10.3390/bioengineering10020198

Open AccessReview

COVID-19 Detection by Means of ECG, Voice, and X-ray Computerized Systems: A Review

by

Pedro Ribeiro

¹

,

João Alexandre Lobo Marques

²

and

Pedro Miguel Rodrigues

^1,*

¹

CBQF—Centro de Biotecnologia e Química Fina—Laboratório Associado, Escola Superior de Biotecnologia, Universidade Católica Portuguesa, Rua de Diogo Botelho 1327, 4169-005 Porto, Portugal

²

Laboratory of Applied Neurosciences, University of Saint Joseph, Macao SAR 999078, China

^*

Author to whom correspondence should be addressed.

Bioengineering 2023, 10(2), 198; https://doi.org/10.3390/bioengineering10020198

Submission received: 13 December 2022 / Revised: 31 January 2023 / Accepted: 1 February 2023 / Published: 3 February 2023

(This article belongs to the Special Issue Health and Public Health Applications for Decision Support Using Machine Learning)

Download

Browse Figures

Versions Notes

Abstract

Since the beginning of 2020, Coronavirus Disease 19 (COVID-19) has attracted the attention of the World Health Organization (WHO). This paper looks into the infection mechanism, patient symptoms, and laboratory diagnosis, followed by an extensive assessment of different technologies and computerized models (based on Electrocardiographic signals (ECG), Voice, and X-ray techniques) proposed as a diagnostic tool for the accurate detection of COVID-19. The found papers showed high accuracy rate results, ranging between 85.70% and 100%, and F1-Scores from 89.52% to 100%. With this state-of-the-art, we concluded that the models proposed for the detection of COVID-19 already have significant results, but the area still has room for improvement, given the vast symptomatology and the better comprehension of individuals’ evolution of the disease.

Keywords: COVID-19; artificial intelligence; signal processing; image processing; computerized diagnostic systems

Share and Cite

MDPI and ACS Style

Ribeiro, P.; Marques, J.A.L.; Rodrigues, P.M. COVID-19 Detection by Means of ECG, Voice, and X-ray Computerized Systems: A Review. Bioengineering 2023, 10, 198. https://doi.org/10.3390/bioengineering10020198

AMA Style

Ribeiro P, Marques JAL, Rodrigues PM. COVID-19 Detection by Means of ECG, Voice, and X-ray Computerized Systems: A Review. Bioengineering. 2023; 10(2):198. https://doi.org/10.3390/bioengineering10020198

Chicago/Turabian Style

Ribeiro, Pedro, João Alexandre Lobo Marques, and Pedro Miguel Rodrigues. 2023. "COVID-19 Detection by Means of ECG, Voice, and X-ray Computerized Systems: A Review" Bioengineering 10, no. 2: 198. https://doi.org/10.3390/bioengineering10020198

APA Style

Ribeiro, P., Marques, J. A. L., & Rodrigues, P. M. (2023). COVID-19 Detection by Means of ECG, Voice, and X-ray Computerized Systems: A Review. Bioengineering, 10(2), 198. https://doi.org/10.3390/bioengineering10020198

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Menu

COVID-19 Detection by Means of ECG, Voice, and X-ray Computerized Systems: A Review

Abstract

Share and Cite

Article Metrics

Article Access Statistics

Further Information

Guidelines

MDPI Initiatives

Follow MDPI