Literature DB >> 14723461

Respiration-related artifacts in EDA recordings: introducing a standardized method to overcome multiple interpretations.

Rainer Schneider1, Stefan Schmidt, Markus Binder, Florian Schäfer, Harald Walach.   

Abstract

When electrodermal activity (EDA) recordings are controlled for artifacts, i.e., electrodermal reactions [EDRs] elicited by breathing irregularities, several problems arise. For example, respiration is difficult to evaluate because there are no clear-cut criteria for its values, e.g., wave form, depth. Furthermore, respiration and EDA are rather complexly intertwined, and there is no established or standardized method for evaluation. Especially when subjects are not stimulated, i.e., when nonspecific EDRs are taken, EDR recordings elicited by irregular breathing may overestimate the subject's arousal and bias any given research question. Moreover, incidences of concurrent consecutive EDRs and changes in respiratory activity may encourage multicausal interpretation due to both signals' having a common central causation. To circumvent such problems, we developed a method which provides rule-based guidelines to identify potential artifacts. Two experiments (N = 14 and N = 12) were conducted to test the accuracy of the judgments of three independent raters. The reliability coefficients for the number of electrodermal reactions and the sum of their amplitudes yielded satisfactory coefficients of convergence for each individual experiment (.87 and .82 in Exp. 1 vs .94 and .95 in Exp. 2) as well as for the two experiments combined (.92 and .91).

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Year:  2003        PMID: 14723461     DOI: 10.2466/pr0.2003.93.3.907

Source DB:  PubMed          Journal:  Psychol Rep        ISSN: 0033-2941


  3 in total

1.  A cardiorespiratory classifier of voluntary and involuntary electrodermal activity.

Authors:  Stefanie Blain; Sarah D Power; Ervin Sejdic; Alex Mihailidis; Tom Chau
Journal:  Biomed Eng Online       Date:  2010-02-25       Impact factor: 2.819

2.  Inference of human affective states from psychophysiological measurements extracted under ecologically valid conditions.

Authors:  Alberto Betella; Riccardo Zucca; Ryszard Cetnarski; Alberto Greco; Antonio Lanatà; Daniele Mazzei; Alessandro Tognetti; Xerxes D Arsiwalla; Pedro Omedas; Danilo De Rossi; Paul F M J Verschure
Journal:  Front Neurosci       Date:  2014-09-24       Impact factor: 4.677

3.  Breathe Easy EDA: A MATLAB toolbox for psychophysiology data management, cleaning, and analysis.

Authors:  John C Ksander; Sarah M Kark; Christopher R Madan
Journal:  F1000Res       Date:  2018-02-22
  3 in total

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