Estimation of Sleep Stages by an Artificial Neural Network Employing EEG, EMG and EOG

被引:0
|
作者
M. Emin Tagluk
Necmettin Sezgin
Mehmet Akin
机构
[1] University of Inonu,Department of Electrical and Electronics Engineering
[2] University of Batman,Department of Electrical and Electronics Engineering
[3] University of Dicle,Department of Electrical and Electronics Engineering
来源
关键词
EEG; EMG; EOG; Sleep stages; ANN;
D O I
暂无
中图分类号
学科分类号
摘要
Analysis and classification of sleep stages is essential in sleep research. In this particular study, an alternative system which estimates sleep stages of human being through a multi-layer neural network (NN) that simultaneously employs EEG, EMG and EOG. The data were recorded through polisomnography device for 7 h for each subject. These collective variant data were first grouped by an expert physician and the software of polisomnography, and then used for training and testing the proposed Artificial Neural Network (ANN). A good scoring was attained through the trained ANN, so it may be put into use in clinics where lacks of specialist physicians.
引用
收藏
页码:717 / 725
页数:8
相关论文
共 50 条
  • [1] Estimation of Sleep Stages by an Artificial Neural Network Employing EEG, EMG and EOG
    Tagluk, M. Emin
    Sezgin, Necmettin
    Akin, Mehmet
    JOURNAL OF MEDICAL SYSTEMS, 2010, 34 (04) : 717 - 725
  • [2] Examining the Relevance with Sleep Stages of Time Domain Features of EEG, EOG, and Chin EMG signals
    Gunes, Salih
    Polat, Kemal
    Dursun, Mehmet
    Yosunkaya, Sebnem
    BIYOMUT: 2009 14TH NATIONAL BIOMEDICAL ENGINEERING MEETING, 2009, : 29 - +
  • [3] Comparison of EEG and EOG signals in classification of sleep stages
    Melek, Negin
    PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI, 2023, 29 (06): : 607 - 616
  • [4] Employing a Convolutional Neural Network to Classify Sleep Stages from EEG Signals Using Feature Reduction Techniques
    Mohammed, Maadh Rajaa
    Sagheer, Ali Makki
    ALGORITHMS, 2024, 17 (06)
  • [5] Automatic Processing of EEG-EOG-EMG Artifacts in Sleep Stage Classification
    Devuyst, S.
    Dutoit, T.
    Ravet, T.
    Stenuit, P.
    Kerkhofs, M.
    Stanus, E.
    13TH INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING, VOLS 1-3, 2009, 23 (1-3): : 146 - +
  • [6] ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM FOR AUTOMATIC SLEEP MULTISTAGE LEVEL SCORING EMPLOYING EEG, EOG, AND EMG EXTRACTED FEATURES
    Khasawneh, Natheer
    Jaradat, Mohammad Abdel Kareem
    Fraiwan, Luay
    Al-Fandi, Mohamed
    APPLIED ARTIFICIAL INTELLIGENCE, 2011, 25 (02) : 163 - 179
  • [7] Use of telemetric recording of EEG, EMG and EOG to assess sleep parameters in the common marmoset
    Melotto, S
    Poffe, A
    Gerrard, PA
    Reggiani, A
    Trist, D
    Ratti, E
    BRITISH JOURNAL OF PHARMACOLOGY, 1998, 125 : U35 - U35
  • [8] Removal of EOG and EMG artifacts from EEG using combination of functional link neural network and adaptive neural fuzzy inference system
    Hu, Jing
    Wang, Chun-sheng
    Wu, Min
    Du, Yu-xiao
    He, Yong
    She, Jinhua
    NEUROCOMPUTING, 2015, 151 : 278 - 287
  • [9] Multiscale neural dynamics in sleep transition volatility across age scales: a multimodal EEG-EMG-EOG analysis of temazepam effects
    Sirpal, Parikshat
    Sikora, William A.
    Refai, Hazem H.
    GEROSCIENCE, 2024, : 205 - 226
  • [10] Home monitoring of sleep with a temporary-tattoo EEG, EOG and EMG electrode array:a feasibility study
    Shustak, Shiran
    Inzelberg, Lilah
    Steinberg, Stanislav
    Rand, David
    Pur, Moshe David
    Hillel, Inbar
    Katzav, Shlomit
    Fahoum, Firas
    De Vos, Maarten
    Mirelman, Anat
    Hanein, Yael
    JOURNAL OF NEURAL ENGINEERING, 2019, 16 (02)