PSG Kayıt Sinyalleri Kullanılarak Uyku Evrelerinin Sınıflandırılması

Yasin Koca,Hülya Vatansev,Seral Özşen,Gülay Tezel,Serkan Küçüktürk,Fatma Zehra Göğüş

doi:10.31590/ejosat.804709

Abstract

Automatic sleep staging is aimed within the scope of this paper. Sleep staging is a study by a sleep specialist. Since this process takes quite a long time and sleep is a method based on the knowledge and experience, it is inevitable for each person to show different results. For this, an automatic sleep staging method has been introduced. In the study, EEG (Electroencephalogram), EOG (Electrooculogram), EMG (Electromyogram) data recorded by PSG (Polysomnography) device for seven patients in Necmettin Erbakan University sleep laboratory were used. 81 different features were taken from the data in time and frequency environment. Also, PCA (Principal component analysis) and SFS (Sequential forward selection) feature selection methods were used. The classification success of the sleep phases in different machine learning methods was measured by using the received features. Linear D. (Linear Discriminant Analysis), Cubic SVM (Support vector machine), Weighted kNN (k nearest neighbor), Bagged Trees, ANN (Artificial neural network) were used as classifiers. System success was achieved with a 5 fold cross-validation method. Accuracy rates obtained were respectively 55.6%, 65.8%, 67%, 72.1%, and 69.1%.

Highlights

The process of sleep staging is carried out by an expert by examining the electroencephalogram (EEG), the electrooculogram (EOG), and electromyogram (EMG), electrocardiogram (EKG) tracings received from patients throughout the night (6-8 hours) and some other signals and by identifying stages of sleep in different parts of time called epoch (30-second parts)
If we look at the classification success of the 81 features in Table 5; we see the highest accuracy in the Bagged Trees algorithm
If we look at general Sensitivity, we see that the Bagged Trees algorithm gives the best sensitivity

Summary

Introduction

The process of sleep staging is carried out by an expert by examining the electroencephalogram (EEG), the electrooculogram (EOG), and electromyogram (EMG), electrocardiogram (EKG) tracings received from patients throughout the night (6-8 hours) and some other signals and by identifying stages of sleep in different parts of time called epoch (30-second parts). The process is executed by a sleep expert and takes quite a long time. Making these processes done automatically reduces processing load and provides convenience for sleep expert in the diagnosis process and shortens the diagnosis period. Elektroensefalogram (EEG), right and left eye Elektrookülogram (EOG) and the chin Elektromiyogram (EMG) signals are the most frequently used ones (Iber, Ancoli-Israel, Chesson & Quan, 2007). There are five sleep stages: Awake (W), Non-REM1, Non-REM2, Non-REM3 and REM (Iber, Ancoli-Israel, Chesson & Quan, 2007)

Methods

Results

Conclusion