Abstract
Now-a-days, there are numerous techniques and ICT tools for the detection of Covid-19. But, these techniques are working with the help; of culminated or peak of symptoms. However, there is a demanding need for the early detection of Covid with self-reported symptoms or even without any symptoms, which makes it easier for further diagnosis or treatment. This research paper proposes a novel approach for the early detection of Covid with the spectral analysis of Cough sound using discrete wavelet transform (DWT), followed by deep convolution neural network (DCNN) based classification. The proposed method with the cough spectral analysis and Deep Learning based algorithm returns the covid infection probability. The empirical results show that the proposed method of covid detection using cough spectral analysis using DWT and deep learning achieves better accuracy, while compared to the conventional methods.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wong, Z.S.Y., Zhou, J., Zhang, Q.: Artificial Intelligence for infectious disease big data analytics. Infect Dis Health. 24, 44–48 (2019). https://doi.org/10.1016/j.idh.2018.10.002
Harrus, I., Wyndham, J.: Artificial intelligence and COVID-19: applications and impact assessment. Technical report prepared by under the auspices of the AAAS Scientific Responsibility, Human Rights and Law Program, 2021 (2021)
Zhao, W., Jiang, W., Qiu, X.: Fine-tuning convolutional neural networks for COVID-19 detection from chest X-ray images. Diagnostics 11, 1887 (2021)
Ting, D.S.W., Lin, H., Ruamviboonsuk, P., Wong, T.Y., Sim, D.A.: Artificial intelligence, the internet of things, and virtual clinics: ophthalmology at the digital translation forefront. Lancet Digital Health 2(1), e8–e9 (2020)
Ting, D.S.W., Liu, Y., Burlina, P., Xu, X., Bressler, N.M., Wong, T.Y.: Al for medical imaging goes deep. Nat Med. 24, 539–540 (2018). https://doi.org/10.1038/s41591-018-0029-3
Khan, W.Z., Azam, F., Khan, M.K.: Deep Learning Based COVID-19 Detection: Challenges and Future Directions. TechRxiv. Preprint. https://doi.org/10.36227/techrxiv.14625885 (2021)
Samer Ellahham, S., Ellahham, N.: Use of artificial intelligence for improving patient flow and healthcare delivery. J. Comput. Sci. Syst. Biol. 12, 303 (2019)
Davenport, T., Kalakota, R.: The potential for artificial intelligence in healthcare. Future Healthc. J. 6(2), 94–98 (2019)
Rousan, L.A., Elobeid, E., Karrar, M., Khader, Y.: Chest X-ray findings and temporal lung changes in patients with covid-19 pneumonia. BMC Pulm. Med. 20(1), 1–9 (2020)
Cleverley, J., Piper, J., Jones, M.M.: The role of chest radiography in confirming covid-19 pneumonia. BMJ m2426 (2020)
Rahaman, M.M., Li, C., Yao, Y., Kulwa, F., Rahman, M.A., Wang, Q., et al.: Identification of COVID-19 samples from chest X-ray images using deep learning: a comparison of transfer learning approaches. J. Xray Sci. Technol. 28(5), 821–839 (2020)
Wang, L., Lin, Z.Q., Wong, A.: Covid-net: A tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images. Sci. Rep. 10(1), 1–12 (2020)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Mariappan, R. (2023). Early Detection of Covid Using Spectral Analysis of Cough and Deep Convolutional Neural Network. In: Molla, A.R., Sharma, G., Kumar, P., Rawat, S. (eds) Distributed Computing and Intelligent Technology. ICDCIT 2023. Lecture Notes in Computer Science, vol 13776. Springer, Cham. https://doi.org/10.1007/978-3-031-24848-1_14
Download citation
DOI: https://doi.org/10.1007/978-3-031-24848-1_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-24847-4
Online ISBN: 978-3-031-24848-1
eBook Packages: Computer ScienceComputer Science (R0)