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

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

12 Citations (Scopus)


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
Number of pages8
Publication statusPublished - 2019
EventNeuroIS Retreat 2018 - Vienna, Austria
Duration: 19 Jun 201821 Jun 2018

Publication series

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


ConferenceNeuroIS Retreat 2018
Internet address


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


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