The SIESTA project polygraphic and clinical database

Klosh, G.; Kemp, B.; Penzel, Thomas; Schlögl, Alois; Rappelsberger, Peter; Trenker, E.; Gruber, Georg; Zeithofer, J.; Saletu, B.; Herrmann, W. M.; Himanen, Sari-Leena; Kunz, Dieter; Barbanoj, M.J.; Röschke, Joachim; Värri, Alpo; Dorffner, Georg

doi:10.1109/51.932725

Cited by 162 publications

(110 citation statements)

References 14 publications

Supporting

Mentioning

108

Contrasting

Order By: Relevance

“…We analyzed heartbeat and respiratory data of 189 healthy subjects (90 male and 99 female, ages ranging from 20 to 95 y) recorded at eight sleep laboratories within the European Union project SIESTA (34). The study was approved by the local institutional human subjects review boards of the sleep laboratories involved; all subjects provided written informed consent.…”

Section: Methodsmentioning

confidence: 99%

“…Additional exclusion criteria in ref. 34 for healthy subjects comprised (i) significant medical disorders, (ii) a Mini Mental State Examination score <25, (iii) a Pittsburgh Sleep Quality Index global score >5, (iv) a usual bedtime before 10 PM or after 12 AM, (v) a SelfRating Anxiety Scale raw score ≥33, and (vi) a Self-Rating Depression Scale raw score ≥35.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Phase transitions in physiologic coupling

Bartsch

Schumann

Kantelhardt

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

212

208

View full text Add to dashboard Cite

Integrated physiological systems, such as the cardiac and the respiratory system, exhibit complex dynamics that are further influenced by intrinsic feedback mechanisms controlling their interaction. To probe how the cardiac and the respiratory system adjust their rhythms, despite continuous fluctuations in their dynamics, we study the phase synchronization of heartbeat intervals and respiratory cycles. The nature of this interaction, its physiological and clinical relevance, and its relation to mechanisms of neural control is not well understood. We investigate whether and how cardiorespiratory phase synchronization (CRPS) responds to changes in physiological states and conditions. We find that the degree of CRPS in healthy subjects dramatically changes with sleep-stage transitions and exhibits a pronounced stratification pattern with a 400% increase from rapid eye movement sleep and wake, to light and deep sleep, indicating that sympatho-vagal balance strongly influences CRPS. For elderly subjects, we find that the overall degree of CRPS is reduced by approximately 40%, which has important clinical implications. However, the sleep-stage stratification pattern we uncover in CRPS does not break down with advanced age, and surprisingly, remains stable across subjects. Our results show that the difference in CRPS between sleep stages exceeds the difference between young and elderly, suggesting that sleep regulation has a significantly stronger effect on cardiorespiratory coupling than healthy aging. We demonstrate that CRPS and the traditionally studied respiratory sinus arrhythmia represent different aspects of the cardiorespiratory interaction, and that key physiologic variables, related to regulatory mechanisms of the cardiac and respiratory systems, which influence respiratory sinus arrhythmia, do not affect CRPS.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Phase transitions in physiologic coupling

Bartsch

Schumann

Kantelhardt

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

212

208

View full text Add to dashboard Cite

show abstract

“…29,30 When scored using AASM sleep scoring rules, they found statistically different (but clinically insignificant) increases in mean Wake after Sleep Onset (WASO, +4 min), NREM 1 (+11 min, +3% TST) and NREM 3 (+9 min, +2% TST) and decreased NREM 2 sleep (-21 min, -5% TST).…”

Section: Differences In Sleep Architecture When Scoring Sleep In Adulmentioning

confidence: 99%

The AASM Scoring Manual Four Years Later

Grigg-Damberger

2012

Journal of Clinical Sleep Medicine

124

View full text Add to dashboard Cite

lent and incident blood pressure; 6,7 (2) lower neurocognitive test scores; 8 and (3) automobile crashes due to sleepiness. 9 The respiratory review paper also provided suffi cient evidence for scoring hypopneas which caused as little as ≥ 20% to 30% fall in airfl ow and/or ≥ 2% or ≥ 3% desaturations. [10][11][12] However, the AASM wanted rules for scoring hypopneas which had substantial or excellent interscorer reliability. Interrater reliability (IRR) as it relates to scoring sleep in a PSG measures how closely individuals score the same sleep study. IRR when scoring a PSG depends upon the: (1) skill, experience, and training of scorer; (2) technical quality of study; (3) clarity and simplicity of scoring rules; (4) diligence with which scoring rules are applied; and (5) degree of physiological ambiguity of the sleep/wake patterns. 13 When two or more individuals score a stage of sleep or an event in a PSG differently, it can introduce enough variability to lead to a false positive or false negative for a particular diagnosis.The IRR for scoring respiratory events in a PSG is particularly affected by the: (1) duration of the event; (2) degree of reduction in the amplitude of the measured signal(s); (3) level of the oxyhemoglobin desaturation associated with it; and (4) presence and duration of arousal which accompanies it. Ayappa et al. found the percent scoring agreement for scoring apneas using a nasal pressure sensor was excellent (0.91) but only moderate for hypopneas (0.69) or fl ow limitation events (0.64).14 The more subtle the reduction in airfl ow, the more diffi cult to achieve good interscorer agreement: one scorer identifi ed 35% more fl ow limitation events than the other. Whitney et al. found a hypopnea associated with 2% to 5% desaturations could be scored with IRR of 0.90, but scoring agreement inPurpose of Review: Review published studies and critiques which evaluate the impact and effects of the American Academy of Sleep Medicine (AASM) Sleep Scoring Manual in the four years since its publication. Findings: Using the AASM Manual rules to score sleep and events in a polysomnogram (PSG) results in: (1) very large differences in apnea-hypopnea indexes (AHI) when using the recommended and alternative rule for scoring hypopneas in adults; (2) increases in NREM 1 and sleep stage shifts with compensatory decreases in NREM 2 in children and adults when following rule 5.C.b. for ending NREM 2 sleep; (3) increases in NREM 3 in adults scoring slow wave activity in the frontal EEG derivations; (4) improved interscorer reliability; and (5) successfully identifi ed fragmented sleep in children with obstructive sleep apnea (OSA) from primary snorers or normal controls because they had more NREM 1 and stage shifts using rule 5.C.b. Criticism of the Manual most often cited: (1) two rules for scoring hypopneas; (2) alternative EEG montage cancellation effects; (3) scoring stages 3 and 4 as NREM 3; and (4) too few rules for scoring arousals and REM sleep without atonia. Summary: Four years have passed since the...

show abstract

“…Every node performs a weighted sum of all the rule strengths entering to it and the result is modified by a sigmoid function. The output at the th node is (4) where and are the slope and the center (or bias) of the output sigmoid of class at layer 3, and is the weight associated to rule strength in node . The slope was determined empirically and considered a fixed parameter in all output nodes.…”

Section: B Neuro-fuzzy Classifier (Nfc)mentioning

confidence: 99%