Respiratory activity classification based on ballistocardiogram analysis [r-libre/2850]

Ben Nasr, Mohamed Chiheb; Ben Jebara, Sofia; Otis, Samuel; Abdulrazak, Bessam, & Mezghani, Neila (2020). Respiratory activity classification based on ballistocardiogram analysis. In The Impact of Digital Technologies on Public Health in Developed and Developing Countries, vol. 12157 (p. 79-88). Springer. ISBN 978-3-030-51517-1 https://doi.org/10.1007/978-3-030-51517-1_7

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Item Type:	Papers in Conference Proceedings
Refereed:	Yes
Status:	Published
Abstract:	Ballistocardiogram signals describe the mechanical activity of the heart. It can be measured by an intelligent mattress in a totally unobtrusive way during periods of rest in bed or sitting on a chair. The BCG signals are highly vulnerable to artefacts such as noise and movement making useful information like respiratory activities difficult to extract. The purpose of this study is to investigate a classification method to distinguish between seven types of respiratory activities such as normal breathing, cough and hold breath. We propose a feature selection method based on a spectral analysis namely spectral flatness measure (SFM) and spectral centroid (SC). The classification is carried out using the nearest neighbor classifier. The proposed method is able to discriminate between the seven classes with the accuracy of 94% which shows its usefulness in context of Telemedicine.
Official URL:	https://link.springer.com/chapter/10.1007/978-3-03...
Depositor:	Ayena, Johannes
Owner / Manager:	Johannes Ayena
Deposited:	12 Jan 2023 21:24
Last Modified:	12 Jan 2023 21:24

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