ArticleSleep2014
Envelope analysis of the airflow signal to improve polysomnographic assessment of sleep disordered breathing.
Article in Sleep, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 25 citations in OpenAlex.
- Noncontact identification of sleep-disturbed breathing from smartphone-recorded sounds validated by polysomnography.Sleep & breathing = Schlaf & Atmung · 2019Trial
- An Innovative EEG-Based Pain Identification and Quantification: A Pilot Study.Sensors (Basel, Switzerland) · 2024Article
- Utilizing Envelope Analysis of a Nasal Pressure Signal for Sleep Apnea Severity Estimation.Diagnostics (Basel, Switzerland) · 2023Article
- Towards the Objective Identification of the Presence of Pain Based on Electroencephalography Signals' Analysis: A Proof-of-Concept.Sensors (Basel, Switzerland) · 2022Article
- Airflow Analysis in the Context of Sleep Apnea.Advances in experimental medicine and biology · 2022Review
- Instability of non-REM sleep in older women evaluated by sleep-stage transition and envelope analyses.Frontiers in aging neuroscience · 2022Article
- A Review of Methods for Sleep Arousal Detection Using Polysomnographic Signals.Brain sciences · 2021Review
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
STUDY
objectivesGiven the detailed respiratory waveform signal provided by the nasal cannula in polysomnographic (PSG) studies, to quantify sleep breathing disturbances by extracting a continuous variable based on the coefficient of variation of the envelope of that signal.
designApplication of an algorithm for envelope analysis to standard nasal cannula signal from actual polysomnographic studies.
settingPSG recordings from a sleep disorders center were analyzed by an algorithm developed on the Igor scientific data analysis software. PATIENTS OR
participantsRecordings representative of different degrees of sleep disordered breathing (SDB) severity or illustrative of the covariation between breathing and particularly relevant factors and variables.
interventionsThe method calculated the coefficient of variation of the envelope for each 30-second epoch. The normalized version of that coefficient was defined as the respiratory disturbance variable (RDV). The method outcome was the all-night set of RDV values represented as a time series. MEASUREMENTS AND
resultsRDV quantitatively reflected departure from normal sinusoidal breathing at each epoch, providing an intensity scale for disordered breathing. RDV dynamics configured itself in recognizable patterns for the airflow limitation (e.g., in UARS) and the apnea/hypopnea regimes. RDV reliably highlighted clinically meaningful associations with staging, body position, oximetry, or CPAP titration.
conclusionsRespiratory disturbance variable can assess sleep breathing disturbances as a gradual phenomenon while providing a comprehensible and detailed representation of its dynamics. It may thus improve clinical diagnosis and provide a revealing descriptive tool for mechanistic sleep disordered breathing modeling. Respiratory disturbance variable may contribute to attaining simplified screening methodologies, novel diagnostic criteria, and insightful research tools.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.