Analysis of A-phase transitions during the cyclic alternating pattern under normal sleep

被引:23
作者
Oswaldo Mendez, Martin [1 ]
Chouvarda, Ioanna [2 ]
Alba, Alfonso [1 ]
Bianchi, Anna Maria [3 ]
Grassi, Andrea [4 ]
Arce-Santana, Edgar [1 ]
Milioli, Guilia [4 ]
Terzano, Mario Giovanni [4 ]
Parrino, Liborio [4 ]
机构
[1] Univ Autonoma San Luis Potosi, Fac Ciencias, Lateral Av Salvador Nava S-N, San Luis Potosi 78290, SLP, Mexico
[2] Aristotle Univ Thessaloniki, Lab Med Informat, GR-54006 Thessaloniki, Greece
[3] Politecn Milan, Dept Biomed Engn, I-20133 Milan, Italy
[4] Univ Parma, Dept Neurol, Sleep Disorders Ctr, I-43100 Parma, Italy
关键词
Sleep; CAP; Nonlinear analysis; Border identification; EEG; SLOW-WAVE SYNCHRONIZATION; AUTOMATIC METHOD; TIME-SERIES; CAP; FREQUENCY; AROUSALS; COMPLEXITY; SPINDLES;
D O I
10.1007/s11517-015-1349-9
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
An analysis of the EEG signal during the B-phase and A-phases transitions of the cyclic alternating pattern (CAP) during sleep is presented. CAP is a sleep phenomenon composed by consecutive sequences of A-phases (each A-phase could belong to a possible group A1, A2 or A3) observed during the non-REM sleep. Each A-phase is separated by a B-phase which has the basal frequency of the EEG during a specific sleep stage. The patterns formed by these sequences reflect the sleep instability and consequently help to understand the sleep process. Ten recordings from healthy good sleepers were included in this study. The current study investigates complexity, statistical and frequency signal properties of electroencephalography (EEG) recordings at the transitions: B-phase-A-phase. In addition, classification between the onset-offset of the A-phases and B-phase was carried out with a kNN classifier. The results showed that EEG signal presents significant differences (p < 0.05) between A-phases and B-phase for the standard deviation, energy, sample entropy, Tsallis entropy and frequency band indices. The A-phase onset showed values of energy three times higher than B-phase at all the sleep stages. The statistical analysis of variance shows that more than 80 % of the A-phase onset and offset is significantly different from the B-phase. The classification performance between onset or offset of A-phases and background showed classification values over 80 % for specificity and accuracy and 70 % for sensitivity. Only during the A3-phase, the classification was lower. The results suggest that neural assembles that generate the basal EEG oscillations during sleep present an over-imposed coordination for a few seconds due to the A-phases. The main characteristics for automatic separation between the onset-offset A-phase and the B-phase are the energy at the different frequency bands.
引用
收藏
页码:133 / 148
页数:16
相关论文
共 33 条
  • [1] Use of the fractal dimension for the analysis of electroencephalographic time series
    Accardo A.
    Affinito M.
    Carrozzi M.
    Bouquet F.
    [J]. Biological Cybernetics, 1997, 77 (5) : 339 - 350
  • [2] [Anonymous], 2007, AASM MANUAL SCORING
  • [3] A general automatic method for the analysis of NREM sleep microstructure
    Barcaro, U
    Bonanni, E
    Maestri, M
    Murri, L
    Parrino, L
    Terzano, MG
    [J]. SLEEP MEDICINE, 2004, 5 (06) : 567 - 576
  • [4] Assessment of the EEG complexity during activations from sleep
    Chouvarda, I.
    Rosso, V.
    Mendez, M. O.
    Bianchi, A. M.
    Parrino, L.
    Grassi, A.
    Terzano, M.
    Cerutti, S.
    [J]. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2011, 104 (03) : E16 - E28
  • [5] Quantitative analysis of sleep EEG microstructure in the time-frequency domain
    De Carli, F
    Nobili, L
    Beelke, M
    Watanabe, T
    Smerieri, A
    Parrino, L
    Terzano, MG
    Ferrillo, F
    [J]. BRAIN RESEARCH BULLETIN, 2004, 63 (05) : 399 - 405
  • [6] Dynamics of the EEG slow-wave synchronization during sleep
    Ferri, R
    Rundo, F
    Bruni, O
    Terzano, MG
    Stam, CJ
    [J]. CLINICAL NEUROPHYSIOLOGY, 2005, 116 (12) : 2783 - 2795
  • [7] All-night EEG power spectral analysis of the cyclic alternating pattern components in young adult subjects
    Ferri, R
    Bruni, O
    Miano, S
    Plazzi, G
    Terzano, MG
    [J]. CLINICAL NEUROPHYSIOLOGY, 2005, 116 (10) : 2429 - 2440
  • [8] Inter-rater reliability of sleep cyclic alternating pattern (CAP) scoring and validation of a new computer-assisted CAP scoring method
    Ferri, R
    Bruni, O
    Miano, S
    Smerieri, A
    Spruyt, K
    Terzano, MG
    [J]. CLINICAL NEUROPHYSIOLOGY, 2005, 116 (03) : 696 - 707
  • [9] Non-linear EEG measures during sleep: effects of the different sleep stages and cyclic alternating pattern
    Ferri, R
    Parrino, L
    Smerieri, A
    Terzano, MG
    Elia, M
    Musumeci, SA
    Pettinato, S
    Stam, CJ
    [J]. INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY, 2002, 43 (03) : 273 - 286
  • [10] The functional connectivity of different EEG bands moves towards small-world network organization during sleep
    Ferri, Raffaele
    Rundo, Francesco
    Bruni, Oliviero
    Terzano, Mario G.
    Stam, Cornelis J.
    [J]. CLINICAL NEUROPHYSIOLOGY, 2008, 119 (09) : 2026 - 2036