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Published on: April 26, 2024
Effective features extraction by analyzing heart sound for identifying cardiovascular diseases related to COVID-19: A
Zahra Sabouri1, Abbas Ghadimi2, Azadeh Kiani-Sarkaleh3
1Department of Electrical Engineering, College of Technical and Engineering, West Tehran Branch, Islamic Azad University, Tehran, Iran.
Insights
This study introduces an automatic, non-invasive method for diagnosing cardiovascular diseases exacerbated by COVID-19 using heart sound analysis. The proposed system achieves high accuracy, offering a practical tool for early detection during the pandemic.
Area of Science:
- Cardiology
- Medical Signal Processing
- Artificial Intelligence in Healthcare
Background:
- Cardiovascular diseases (CVDs) pose increased mortality risks when co-occurring with coronavirus infections, particularly during the COVID-19 pandemic.
- Early and accurate diagnosis of COVID-19-related cardiac complications is critical for patient outcomes.
- Current diagnostic methods may be invasive, costly, or time-consuming, necessitating alternative approaches.
Purpose of the Study:
- To develop an automatic, non-invasive, and inexpensive method for diagnosing cardiovascular diseases in the context of COVID-19.
- To leverage heart sound processing and feature extraction for improved diagnostic capabilities.
- To establish a generalizable and practical model for identifying cardiac conditions during the COVID-19 pandemic.
Main Methods:
- Extraction and selection of morphological and statistical features from heart sound signals across various frequencies.
- Application of diverse classifiers with different kernels for diagnostic analysis under balanced and unbalanced data conditions.
- Elimination of dependence on specific segmentation and filtering techniques to enhance generalizability.
Main Results:
- Achieved 93.15% accuracy and 93.72% F1-score using 60 effective features in balanced data conditions.
- Demonstrated the system's ability to achieve desired results on a generalized dataset using features extracted from the Azad dataset.
- Validated the effectiveness and generalizability of the proposed method for diagnosing cardiovascular diseases in COVID-19 patients.
Conclusions:
- The proposed heart sound processing approach provides an effective and generalizable method for diagnosing cardiovascular diseases in COVID-19 patients.
- The system offers a practical and rapid diagnostic tool, crucial for managing cardiac complications during the pandemic.
- This non-invasive technique holds significant potential for early detection and improved patient management in resource-limited settings.
Abstract:
Incidence and exacerbation of some of the cardiovascular diseases in the presence of the coronavirus will lead to an increase in the mortality rate among patients. Therefore, early diagnosis of such diseases is critical, especially during the COVID-19 pandemic (mild COVID-19 infection). Thus, for diagnosing the heart diseases related to the COVID-19, an automatic, non-invasive, and inexpensive method based on the heart sound processing approach is proposed. In the present study, a set of features related to the nature of heart signals is defined and extracted. The investigated features included morphological and statistical features in the heart sound frequencies. By extracting and selecting a set of effective features related to the mentioned diseases, and avoiding to use different segmentation and filtering techniques, dependence on a limited dataset and specific sampling procedures has been eliminated. Different classifiers with various kernels are applied for diagnosis in data unbalanced and balanced conditions. The results showed 93.15% accuracy and 93.72% F1-score using 60 effective features in data balanced conditions. The identification system using the extracted features from Azad dataset is able to achieve the desired results in a generalized dataset. In this way, in the shortest possible sampling time, the present system provided an effective and generalizable method and a practical model for diagnosing important cardiovascular diseases in the presence of coronavirus in the COVID-19 pandemic.
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