Literature DB >> 28791596

Automated respiratory sinus arrhythmia measurement: Demonstration using executive function assessment.

Meghan Hegarty-Craver1, Kristin H Gilchrist2, Cathi B Propper3, Gregory F Lewis3, Samuel J DeFilipp1, Jennifer L Coffman3, Michael T Willoughby1.   

Abstract

Respiratory sinus arrhythmia (RSA) is a quantitative metric that reflects autonomic nervous system regulation and provides a physiological marker of attentional engagement that supports cognitive and affective regulatory processes. RSA can be added to executive function (EF) assessments with minimal participant burden because of the commercial availability of lightweight, wearable electrocardiogram (ECG) sensors. However, the inclusion of RSA data in large data collection efforts has been hindered by the time-intensive processing of RSA. In this study we evaluated the performance of an automated RSA-scoring method in the context of an EF study in preschool-aged children. The absolute differences in RSA across both scoring methods were small (mean RSA differences = -0.02-0.10), with little to no evidence of bias for the automated relative to the hand-scoring approach. Moreover, the relative rank-ordering of RSA across both scoring methods was strong (rs = .96-.99). Reliable changes in RSA from baseline to the EF task were highly similar across both scoring methods (96%-100% absolute agreement; Kappa = .83-1.0). On the basis of these findings, the automated RSA algorithm appears to be a suitable substitute for hand-scoring in the context of EF assessment.

Entities:  

Keywords:  Automated processing; Error correction; Executive functions; Heart rate; Respiratory sinus arrhythmia

Mesh:

Year:  2018        PMID: 28791596      PMCID: PMC5803481          DOI: 10.3758/s13428-017-0950-2

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  11 in total

1.  The two errors of using the within-subject standard deviation (WSD) as the standard error of a reliable change index.

Authors:  Gerard H Maassen
Journal:  Arch Clin Neuropsychol       Date:  2010-05-27       Impact factor: 2.813

Review 2.  The polyvagal perspective.

Authors:  Stephen W Porges
Journal:  Biol Psychol       Date:  2006-10-16       Impact factor: 3.251

3.  The relationships among heart rate variability, executive functions, and clinical variables in patients with panic disorder.

Authors:  Anders Hovland; Ståle Pallesen; Åsa Hammar; Anita Lill Hansen; Julian F Thayer; Mika P Tarvainen; Inger Hilde Nordhus
Journal:  Int J Psychophysiol       Date:  2012-10-13       Impact factor: 2.997

4.  Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database.

Authors:  P S Hamilton; W J Tompkins
Journal:  IEEE Trans Biomed Eng       Date:  1986-12       Impact factor: 4.538

5.  A real-time QRS detection algorithm.

Authors:  J Pan; W J Tompkins
Journal:  IEEE Trans Biomed Eng       Date:  1985-03       Impact factor: 4.538

6.  Moderate vagal withdrawal in 3.5-year-old children is associated with optimal performance on executive function tasks.

Authors:  Stuart Marcovitch; Janet Leigh; Susan D Calkins; Esther M Leerks; Marion O'Brien; A Nayena Blankson
Journal:  Dev Psychobiol       Date:  2010-09       Impact factor: 3.038

7.  Marital conflict, allostatic load, and the development of children's fluid cognitive performance.

Authors:  J Benjamin Hinnant; Mona El-Sheikh; Margaret Keiley; Joseph A Buckhalt
Journal:  Child Dev       Date:  2013-03-27

8.  Is executive function intact after pediatric intracranial hemorrhage? A sample of Mexican children with hemophilia.

Authors:  Guadalupe Morales; Esmeralda Matute; Joan Murray; David J Hardy; Erin T O'Callaghan; Alberto Tlacuilo-Parra
Journal:  Clin Pediatr (Phila)       Date:  2013-07-19       Impact factor: 1.168

9.  The role of planning skills in the income-achievement gap.

Authors:  Stephen R Crook; Gary W Evans
Journal:  Child Dev       Date:  2013-07-01

10.  Real-time correction of heart interbeat intervals.

Authors:  Jeromie Rand; Adam Hoover; Stephanie Fishel; Jason Moss; Jennifer Pappas; Eric Muth
Journal:  IEEE Trans Biomed Eng       Date:  2007-05       Impact factor: 4.538

View more
  1 in total

1.  Cardiac-based detection of seizures in children with epilepsy.

Authors:  Meghan Hegarty-Craver; Barbara L Kroner; Adrian Bumbut; Samuel J DeFilipp; William D Gaillard; Kristin H Gilchrist
Journal:  Epilepsy Behav       Date:  2021-06-17       Impact factor: 3.337

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.