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Cooperative classification of clean and deformed capnogram segments using a voting approach: a trade-off between specificity and sensitivity

Automatic discrimination of clean and deformed segments of capnogram signals is an essential requisite in capnogram-based respiratory assessment. However, improving the performance of this classification task remains challenging, particularly in terms of specificity and sensitivity. The goal of this...

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Main Authors: El-Badawy, Ismail M., Omar, Zaid, Singh, Om Prakash
Format: Conference or Workshop Item
Published: 2022
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/98873/
http://dx.doi.org/10.1109/EMBC48229.2022.9871051
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spelling my.utm.988732023-02-02T10:00:52Z http://eprints.utm.my/id/eprint/98873/ Cooperative classification of clean and deformed capnogram segments using a voting approach: a trade-off between specificity and sensitivity El-Badawy, Ismail M. Omar, Zaid Singh, Om Prakash TK Electrical engineering. Electronics Nuclear engineering Automatic discrimination of clean and deformed segments of capnogram signals is an essential requisite in capnogram-based respiratory assessment. However, improving the performance of this classification task remains challenging, particularly in terms of specificity and sensitivity. The goal of this paper is to address this issue by proposing a cooperative classification approach rather than relying solely on a single classifier. The presented method's main advantage is the vote participation of four distinct classifiers that affects the reliability of the final classification decision. MATLAB simulation was run on a dataset consisting of 200 15-seconds capnogram segments, 100 of which are clean and 100 are deformed. The results revealed a trade-off between the achieved specificity and sensitivity by adjusting the strictness of voting. Being highly strict in the sense of classifying a capnogram segment as clean if and only if all voting classifiers agreed on deciding so, provided specificity and sensitivity of 94% and 81%, respectively. On the contrary, lowering the strictness of voting by considering only one positive vote is sufficient to eventually classify the query capnogram segment as non-deformed gave specificity and sensitivity of 74% and 94%, respectively. 2022 Conference or Workshop Item PeerReviewed El-Badawy, Ismail M. and Omar, Zaid and Singh, Om Prakash (2022) Cooperative classification of clean and deformed capnogram segments using a voting approach: a trade-off between specificity and sensitivity. In: 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022, 11 July 2022 - 15 July 2022, Glasgow, Scotland. http://dx.doi.org/10.1109/EMBC48229.2022.9871051
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
El-Badawy, Ismail M.
Omar, Zaid
Singh, Om Prakash
Cooperative classification of clean and deformed capnogram segments using a voting approach: a trade-off between specificity and sensitivity
description Automatic discrimination of clean and deformed segments of capnogram signals is an essential requisite in capnogram-based respiratory assessment. However, improving the performance of this classification task remains challenging, particularly in terms of specificity and sensitivity. The goal of this paper is to address this issue by proposing a cooperative classification approach rather than relying solely on a single classifier. The presented method's main advantage is the vote participation of four distinct classifiers that affects the reliability of the final classification decision. MATLAB simulation was run on a dataset consisting of 200 15-seconds capnogram segments, 100 of which are clean and 100 are deformed. The results revealed a trade-off between the achieved specificity and sensitivity by adjusting the strictness of voting. Being highly strict in the sense of classifying a capnogram segment as clean if and only if all voting classifiers agreed on deciding so, provided specificity and sensitivity of 94% and 81%, respectively. On the contrary, lowering the strictness of voting by considering only one positive vote is sufficient to eventually classify the query capnogram segment as non-deformed gave specificity and sensitivity of 74% and 94%, respectively.
format Conference or Workshop Item
author El-Badawy, Ismail M.
Omar, Zaid
Singh, Om Prakash
author_facet El-Badawy, Ismail M.
Omar, Zaid
Singh, Om Prakash
author_sort El-Badawy, Ismail M.
title Cooperative classification of clean and deformed capnogram segments using a voting approach: a trade-off between specificity and sensitivity
title_short Cooperative classification of clean and deformed capnogram segments using a voting approach: a trade-off between specificity and sensitivity
title_full Cooperative classification of clean and deformed capnogram segments using a voting approach: a trade-off between specificity and sensitivity
title_fullStr Cooperative classification of clean and deformed capnogram segments using a voting approach: a trade-off between specificity and sensitivity
title_full_unstemmed Cooperative classification of clean and deformed capnogram segments using a voting approach: a trade-off between specificity and sensitivity
title_sort cooperative classification of clean and deformed capnogram segments using a voting approach: a trade-off between specificity and sensitivity
publishDate 2022
url http://eprints.utm.my/id/eprint/98873/
http://dx.doi.org/10.1109/EMBC48229.2022.9871051
_version_ 1758578031314599936
score 13.244413

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