2017
DOI: 10.1007/s40846-017-0251-3
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Detrended Fluctuation Analysis of Oxyhemoglobin Saturation by Pulse Oximetry in Sleep Apnea Syndrome

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Cited by 3 publications
(10 citation statements)
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“…The DFA profile shows changes in the correlation properties for different ranges of scales, termed 'crossovers', which may be caused by different non-stationarities in the signal such as (Chen et al 2002): (i) segments removed from the signal; (ii) random spikes with variable amplitude; (iii) segments with different local behaviour. Segments of the SpO 2 signal associated with apnoeic events typically have different statistical properties, presenting fluctuations and spikes (Crespo et al 2017, Hua andYu 2017). Thus, these properties of the SpO 2 signal may be reflected in the DFA profile.…”
Section: Detrended Fluctuation Analysismentioning
confidence: 99%
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“…The DFA profile shows changes in the correlation properties for different ranges of scales, termed 'crossovers', which may be caused by different non-stationarities in the signal such as (Chen et al 2002): (i) segments removed from the signal; (ii) random spikes with variable amplitude; (iii) segments with different local behaviour. Segments of the SpO 2 signal associated with apnoeic events typically have different statistical properties, presenting fluctuations and spikes (Crespo et al 2017, Hua andYu 2017). Thus, these properties of the SpO 2 signal may be reflected in the DFA profile.…”
Section: Detrended Fluctuation Analysismentioning
confidence: 99%
“…A double logarithmic plot was used to analyse the evolution of the DFA plot along scales: log (F(k)) versus log (k) (Penzel et al 2003, Dehkordi et al 2016, Hua and Yu 2017. Figure 1 shows the averaged DFA plot for the four SAHS severity groups (AHI < 1 e h −1 , 1 ⩽ AHI < 5 e h −1 , 5 ⩽ AHI < 10 e h −1 , and AHI ⩾ 10 e h −1 ) in the training set.…”
Section: Detrended Fluctuation Analysismentioning
confidence: 99%
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