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

John C Ksander,Sarah M Kark,Christopher R Madan

doi:10.12688/f1000research.13849.1

John C Ksander, Sarah M Kark + Show 1 more

Open Access

https://doi.org/10.12688/f1000research.13849.1

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Abstract

Electrodermal activity (EDA) recordings are widely used in experimental psychology to measure skin conductance responses (SCRs) that reflect sympathetic nervous system arousal. However, irregular respiration patterns and deep breaths can cause EDA fluctuations that are difficult to distinguish from genuine arousal-related SCRs, presenting a methodological challenge that increases the likelihood of false positives in SCR analyses. Thus, it is crucial to identify respiration-related artifacts in EDA data. Here we developed a novel and freely distributed MATLAB toolbox, Breathe Easy EDA (BEEDA). BEEDA is a flexible toolbox that facilitates EDA visual inspection, allowing users to identify and eliminate respiration artifacts. BEEDA further includes functionality for EDA data analyses (measuring tonic and phasic EDA components) and reliability analyses for artifact identification. The toolbox is suitable for any experiment recording both EDA and respiration data, and flexibly adjusts to experiment-specific parameters (e.g., trial structure and analysis parameters).

Highlights

Electrodermal activity (EDA) methods evaluate fluctuations in skin electrical conductance caused by changes in sweat gland production
We have developed a novel MATLAB toolbox for efficiently eliminating EDA respiration artifacts and analyzing EDA data, which we freely distribute as Breathe Easy EDA or ‘BEEDA’
Have provided example analysis output using this dataset as Supplementary File 1. This output shows artifact information from data cleaning, along with the analyses described in the sections on EDA analysis functionality and statistics

Summary

Introduction

Electrodermal activity (EDA) methods evaluate fluctuations in skin electrical conductance caused by changes in sweat gland production. An easy-to-use and freely available software that expedites visual inspection of respiration data, and allows researchers to quantify their artifact-control procedures is not available. BEEDA’s streamlined artifact removal interface allows users to quickly identify and clean EDA data, expediting EDA analysis without compromising analysis integrity. BEEDA’s integrated EDA analysis functionality allows users to seamlessly analyze cleaned EDA data within the toolbox.

Results

Conclusion