scholarly journals Erratum: Martín-Montero et al. Bispectral Analysis of Heart Rate Variability to Characterize and Help Diagnose Pediatric Sleep Apnea. Entropy 2021, 23, 1016

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1375
Author(s):  
Adrián Martín-Montero ◽  
Gonzalo C. Gutiérrez-Tobal ◽  
David Gozal ◽  
Verónica Barroso-García ◽  
Daniel Álvarez ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sleep Apnea ◽  
Bispectral Analysis ◽  
Pediatric Sleep

The author wishes to make the following correction to this paper [...]

scholarly journals Bispectral Analysis of Heart Rate Variability to Characterize and Help Diagnose Pediatric Sleep Apnea

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 1016
Author(s):  
Adrián Martín-Montero ◽  
Gonzalo C. Gutiérrez-Tobal ◽  
David Gozal ◽  
Verónica Barroso-García ◽  
Daniel Álvarez ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sleep Apnea ◽  
Characteristic Curve ◽  
Low Frequency ◽  
Bispectral Analysis ◽  
Obstructive Sleep ◽  
Specific Frequency ◽  
Similar Accuracy ◽  
Signal Characterization

Pediatric obstructive sleep apnea (OSA) is a breathing disorder that alters heart rate variability (HRV) dynamics during sleep. HRV in children is commonly assessed through conventional spectral analysis. However, bispectral analysis provides both linearity and stationarity information and has not been applied to the assessment of HRV in pediatric OSA. Here, this work aimed to assess HRV using bispectral analysis in children with OSA for signal characterization and diagnostic purposes in two large pediatric databases (0–13 years). The first database (training set) was composed of 981 overnight ECG recordings obtained during polysomnography. The second database (test set) was a subset of the Childhood Adenotonsillectomy Trial database (757 children). We characterized three bispectral regions based on the classic HRV frequency ranges (very low frequency: 0–0.04 Hz; low frequency: 0.04–0.15 Hz; and high frequency: 0.15–0.40 Hz), as well as three OSA-specific frequency ranges obtained in recent studies (BW1: 0.001–0.005 Hz; BW2: 0.028–0.074 Hz; BWRes: a subject-adaptive respiratory region). In each region, up to 14 bispectral features were computed. The fast correlation-based filter was applied to the features obtained from the classic and OSA-specific regions, showing complementary information regarding OSA alterations in HRV. This information was then used to train multi-layer perceptron (MLP) neural networks aimed at automatically detecting pediatric OSA using three clinically defined severity classifiers. Both classic and OSA-specific MLP models showed high and similar accuracy (Acc) and areas under the receiver operating characteristic curve (AUCs) for moderate (classic regions: Acc = 81.0%, AUC = 0.774; OSA-specific regions: Acc = 81.0%, AUC = 0.791) and severe (classic regions: Acc = 91.7%, AUC = 0.847; OSA-specific regions: Acc = 89.3%, AUC = 0.841) OSA levels. Thus, the current findings highlight the usefulness of bispectral analysis on HRV to characterize and diagnose pediatric OSA.

scholarly journals Symbolic dynamics marker of heart rate variability combined with clinical variables enhance obstructive sleep apnea screening

2014 ◽  
Vol 24 (2) ◽  
pp. 024404 ◽  
Author(s):  
A. G. Ravelo-García ◽  
P. Saavedra-Santana ◽  
G. Juliá-Serdá ◽  
J. L. Navarro-Mesa ◽  
J. Navarro-Esteva ◽  
...  
Keyword(s):  
Heart Rate ◽  
Obstructive Sleep Apnea ◽  
Heart Rate Variability ◽  
Sleep Apnea ◽  
Symbolic Dynamics ◽  
Clinical Variables ◽  
Obstructive Sleep

scholarly journals Augmented Very Low Frequency Component of Heart Rate Variability During Obstructive Sleep Apnea

SLEEP ◽  
1996 ◽  
Vol 19 (5) ◽  
pp. 370-377 ◽  
Author(s):  
Toshiaki Shiomi ◽  
Christian Guilleminault ◽  
Ryujiro Sasanabe ◽  
Izumi Hirota ◽  
Masato Maekawa ◽  
...  
Keyword(s):  
Heart Rate ◽  
Obstructive Sleep Apnea ◽  
Heart Rate Variability ◽  
Sleep Apnea ◽  
Low Frequency ◽  
Frequency Component ◽  
Very Low Frequency ◽  
Obstructive Sleep

Automatic detection and quantification of sleep apnea using heart rate variability

2010 ◽  
Vol 43 (6) ◽  
pp. 535-541 ◽  
Author(s):  
Saeed Babaeizadeh ◽  
David P. White ◽  
Stephen D. Pittman ◽  
Sophia H. Zhou
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sleep Apnea ◽  
Automatic Detection ◽  
Detection And Quantification

scholarly journals Sleep Apnea in Heart Failure Increases Heart Rate Variability and Sympathetic Dominance

SLEEP ◽  
2007 ◽  
Vol 30 (11) ◽  
pp. 1509-1514 ◽  
Author(s):  
Irene Szollosi ◽  
Henry Krum ◽  
David Kaye ◽  
Matthew T. Naughton
Keyword(s):  
Heart Failure ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Sleep Apnea
Sign in / Sign up

Export Citation Format

Share Document