Automatic classification of regular and irregular capnogram segments using time- and frequency-domain features: a machine learning-based approach

• Main Authors: El-Badawy, I. M., Singh, O. P., Omar, Z.
• Format: Article
• Published: IOS Press BV 2021
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/94179/; http://www.dx.doi.org/10.3233/THC-202198
• Institution: Universiti Teknologi Malaysia

This paper presents a machine learning-based approach for the automatic classification of regular and irregular capnogram segments. METHODS: Herein, we proposed four time- and two frequency-domain features experimented with the support vector machine classifier through ten-fold cross-validation. MAT...