A method for the automatic analysis of the sleep macrostructure in continuum

被引:27
|
作者
Alvarez-Estevez, Diego [1 ]
Fernandez-Pastoriza, Jose M. [1 ]
Hernandez-Pereira, Elena [1 ]
Moret-Bonillo, Vicente [1 ]
机构
[1] Univ A Coruna, Dept Comp Sci, Lab Res & Dev Artificial Intelligence LIDIA, La Coruna 15071, Spain
关键词
Sleep studies; Hypnogram; Fuzzy reasoning; CLASSIFICATION; INFANTS; SYSTEM; EEG; RECHTSCHAFFEN; RELIABILITY; STATES; DEPTH; KALES;
D O I
10.1016/j.eswa.2012.09.022
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Sleep staging is one of the most important tasks within the context of sleep studies. For more than 40 years the gold standard to the characterization of patient's sleep macrostructure has been based on set of rules proposed by Rechtschaffen and Kales and recently modified by the American Academy of Sleep Medicine. Nevertheless the resulting map of sleep, the so-called hypnogram, has several limitations such as its low temporal resolution and the unnatural characterization of sleep through the assignment of discrete sleep states. This study reports an automatic method for the characterization of the structure of the sleep. The main intention is to overcome limitations of epoch-based sleep staging by obtaining a more continuous evolution of the sleep of the patient. The method is based on the use of fuzzy inference in order to avoid binary decisions, provide soft transitions and enable concurrent characterization of the different states. It is proven, in addition, how the new proposed continuous representation can still be used to generate the classical epoch-based hypnogram. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1796 / 1803
页数:8
相关论文
共 50 条
  • [41] ANALYSIS OF CONTINUUM BY THE INTEGRATED FORCE METHOD
    PATNAIK, SN
    NAGARAJ, MS
    COMPUTERS & STRUCTURES, 1987, 26 (06) : 899 - 905
  • [42] Deep Learning Automatic Sleep Staging Method Based on Multidimensional Sleep Data
    Yang, Jian
    Meng, Yao
    Cheng, Qian
    Li, Huafei
    Cai, Wenpeng
    Wang, Tengjiao
    IEEE ACCESS, 2024, 12 : 168360 - 168369
  • [43] A rule-based automatic sleep staging method
    Liang, Sheng-Fu
    Kuo, Chin-En
    Hu, Yu-Han
    Cheng, Yu-Shian
    JOURNAL OF NEUROSCIENCE METHODS, 2012, 205 (01) : 169 - 176
  • [44] Ensemble SVM Method for Automatic Sleep Stage Classification
    Alickovic, Emina
    Subasi, Abdulhamit
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2018, 67 (06) : 1258 - 1265
  • [45] Fast Convolutional Method for Automatic Sleep Stage Classification
    Yulita, Intan Nurma
    Fanany, Mohamad Ivan
    Arymurthy, Aniati Murni
    HEALTHCARE INFORMATICS RESEARCH, 2018, 24 (03) : 170 - 178
  • [46] A rule-based automatic sleep staging method
    Liang, Sheng-Fu
    Kuo, Chih-En
    Hu, Yu-Han
    Cheng, Yu-Shian
    2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2011, : 6067 - 6070
  • [47] The Automatic Sleep Stage Diagnosis Method by using SOM
    Shimada, Takamasa
    Tamura, Kazuhiro
    Fukami, Tadanori
    Saito, Yoichi
    13TH INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING, VOLS 1-3, 2009, 23 (1-3): : 245 - +
  • [48] AUTOMATIC-ANALYSIS OF POLYGRAPHIC SLEEP RECORDS
    BARON, E
    GATH, I
    BENTAL, E
    PHYSICS IN MEDICINE AND BIOLOGY, 1980, 25 (05): : 999 - 999
  • [49] A System for Automatic Sleep Structure Recognition and Analysis
    Cao, Yuting
    Li, Baozhu
    Zhang, Yuan
    Kos, Anton
    ELEKTROTEHNISKI VESTNIK, 2023, 90 (03): : 99 - 104
  • [50] A System for Automatic Sleep Structure Recognition and Analysis
    Cao, Yuting
    Li, Baozhu
    Zhang, Yuan
    Kos, Anton
    Elektrotehniski Vestnik/Electrotechnical Review, 2023, 90 (03): : 99 - 104