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. 2021 Jul 15:9:102327-102344.
doi: 10.1109/ACCESS.2021.3097559. eCollection 2021.

Cough Sound Detection and Diagnosis Using Artificial Intelligence Techniques: Challenges and Opportunities

Kawther S Alqudaihi  1 , Nida Aslam  1 , Irfan Ullah Khan  1 , Abdullah M Almuhaideb  2 , Shikah J Alsunaidi  1 , Nehad M Abdel Rahman Ibrahim  1 , Fahd A Alhaidari  2 , Fatema S Shaikh  3 , Yasmine M Alsenbel  1 , Dima M Alalharith  1 , Hajar M Alharthi  1 , Wejdan M Alghamdi  1 , Mohammed S Alshahrani  4
Affiliations

Cough Sound Detection and Diagnosis Using Artificial Intelligence Techniques: Challenges and Opportunities

Kawther S Alqudaihi et al. IEEE Access. .

Abstract

Coughing is a common symptom of several respiratory diseases. The sound and type of cough are useful features to consider when diagnosing a disease. Respiratory infections pose a significant risk to human lives worldwide as well as a significant economic downturn, particularly in countries with limited therapeutic resources. In this study we reviewed the latest proposed technologies that were used to control the impact of respiratory diseases. Artificial Intelligence (AI) is a promising technology that aids in data analysis and prediction of results, thereby ensuring people's well-being. We conveyed that the cough symptom can be reliably used by AI algorithms to detect and diagnose different types of known diseases including pneumonia, pulmonary edema, asthma, tuberculosis (TB), COVID19, pertussis, and other respiratory diseases. We also identified different techniques that produced the best results for diagnosing respiratory disease using cough samples. This study presents the most recent challenges, solutions, and opportunities in respiratory disease detection and diagnosis, allowing practitioners and researchers to develop better techniques.

Keywords: 2019 novel coronavirus disease (Covid-19); Artificial intelligence (AI); cough detection; cough-based diagnosis; respiratory illness diagnosis.

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Figures

FIGURE 1.
FIGURE 1.
Methodology of the proposed study.
FIGURE 2.
FIGURE 2.
Classification of current cough-based detection and diagnostic methods.
FIGURE 3.
FIGURE 3.
Number of cough detection and diagnosis studies.
FIGURE 4.
FIGURE 4.
Popular AI/ML techniques used in the current cough-based detection and diagnosis approaches.
FIGURE 5.
FIGURE 5.
Taxonomy of the state of art dataset size.
See this image and copyright information in PMC

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