Single-channel EEG processing for sleep apnea detection and differentiation

• Autorzy: Prucnal Monika A. , Polak Adam G.

Identyfikatory

DOI

10.24425/mms.2023.144866

• Języki publikacji: EN

Abstrakty

EN

Sleep apnea syndrome is a common sleep disorder. Detection of apnea and differentiation of its type: obstructive (OSA), central (CSA) or mixed is important in the context of treatment methods, however, it typically requires a great deal of technical and human resources. The aim of this research was to propose a quasi-optimal procedure for processing single-channel electroencephalograms (EEG) from overnight recordings, maximizing the accuracy of automatic apnea or hypopnea detection, as well as distinguishing between the OSA and CSA types. The proposed methodology consisted in processing the EEG signals divided into epochs, with the selection of the best methods at the stages of preprocessing, extraction and selection of features, and classification. Normal breathing was unmistakably distinguished from apnea by the k-nearest neighbors (kNN) and an artificial neural network (ANN), and with 99.98% accuracy by the support vector machine (SVM). The average accuracy of multinomial classification was: 82.29%, 83.26%, and 82.25% for the kNN, SVM and ANN, respectively. The sensitivity and precision of OSA and CSA detection ranged from 55 to 66%, and the misclassification cases concerned only the apnea type.

Słowa kluczowe

EN

single-channel EEG; sleep apnea detection; optimization of signal processing; medical decision support

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2023
• Tom: Vol. 30, nr 2
• Strony: 323--336
• Opis fizyczny: Bibliogr. 44 poz., tab.

Twórcy

autor

Prucnal Monika A.

• Department of Electronic and Photonic Metrology, Faculty of Electronics, Photonics and Microsystems, Wroclaw University of Science and Technology, Wroclaw, Poland

autor

Polak Adam G.

• Department of Electronic and Photonic Metrology, Faculty of Electronics, Photonics and Microsystems, Wroclaw University of Science and Technology, Wroclaw, Poland

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Uwagi

1. Research supported by the Grant no. 0402/0148/18 from the Ministry of Science and Higher Education, Poland.

2. Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).