Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Measuring Mental Workload With Low-Cost and Wearable Sensors: Insights Into the Accuracy, Obtrusiveness, and Research Usability of Three Instruments
KTH, School of Technology and Health (STH), Health Systems Engineering.ORCID iD: 0000-0003-1126-3781
2017 (English)In: Journal of Cognitive Engineering and Decision Making, ISSN 1555-3434, E-ISSN 2169-5032, Vol. 11, no 4, 323-336 p.Article in journal (Refereed) Published
Abstract [en]

The affordability of wearable psychophysiological sensors has led to opportunities to measure the mental workload of operators in complex sociotechnical systems in ways that are more objective and less obtrusive. This study primarily focuses on the sensors themselves by investigating low-cost and wearable sensors in terms of their accuracy, obtrusiveness, and usability for research purposes. Two sensors were assessed on their accuracy as tools to measure mental workload through heart rate variability (HRV): the E3 from Empatica and the emWave Pro from HeartMath. The BioPatch from Zephyr Technology, which is an U.S. Food and Drug Administration-approved device, was used as a gold standard to compare the data obtained from the other 2 devices regarding their accuracy on HRV. Linear dependencies for 6 of 10 HRV parameters were found between the emWave and BioPatch data and for 1 of 10 for the E3 sensor. In terms of research usability, both the E3 and the BioPatch had difficulty acquiring either sufficiently high data recording confidence values or normal distributions. However, the BioPatch output files do not require postprocessing, which reduces costs and effort in the analysis stage. None of the sensors was perceived as obtrusive by the participants.

Place, publisher, year, edition, pages
SAGE PUBLICATIONS INC , 2017. Vol. 11, no 4, 323-336 p.
Keyword [en]
cognitive processes, topics, command and control, domains, ground transportation, workload, analysis methods
National Category
Medical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-217931DOI: 10.1177/1555343417716040ISI: 000414407500002Scopus ID: 2-s2.0-85032956243OAI: oai:DiVA.org:kth-217931DiVA: diva2:1158862
Note

QC 20171121

Available from: 2017-11-21 Created: 2017-11-21 Last updated: 2017-11-21Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Authority records BETA

Meijer, Sebastiaan

Search in DiVA

By author/editor
Meijer, Sebastiaan
By organisation
Health Systems Engineering
In the same journal
Journal of Cognitive Engineering and Decision Making
Medical Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 23 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf