Analysis of Heart Rate Variability (HRV) Feature Robustness for Measuring Technostress

Research output: Chapter in Book/Report/Conference proceedingsChapterpeer-review

3 Citations (Scopus)

Abstract

Technostress has become an important topic in the scientific literature, particularly in Information Systems (IS) research. Heart rate variability (HRV) has been proposed as a measure of (techno)stress and is widely used in scientific investigations. The objective of the pilot study reported in this paper is to showcase how the preprocessing/cleaning of captured data can influence the results and their interpretation, when compared to self-report data. The evidence reported in this paper supports the notion that NeuroIS scholars have to deliberately make methodological decisions such as those related to preprocessing of physiological data. It is therefore crucial that methodological details are presented in NeuroIS papers in order to create a better understanding of the study results and their implications.

Original languageEnglish
Title of host publicationLecture Notes in Information Systems and Organisation
PublisherSpringer
Pages221-228
Number of pages8
DOIs
Publication statusPublished - 2019
EventNeuroIS Retreat 2018 - Vienna, Austria
Duration: 19 Jun 201821 Jun 2018
http://www.neurois.org

Publication series

NameLecture Notes in Information Systems and Organisation
Volume29
ISSN (Print)2195-4968
ISSN (Electronic)2195-4976

Conference

ConferenceNeuroIS Retreat 2018
CountryAustria
CityVienna
Period19.06.201821.06.2018
Internet address

Keywords

  • Data preprocessing
  • Heart rate variability (HRV)
  • NeuroIS research methodology
  • Signal feature
  • Stress
  • Technostress

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