Measuring Mental Workload With Low-Cost and Wearable Sensors: Insights Into the Accuracy, Obtrusiveness, and Research Usability of Three Instruments. (December 2017)

• Record Type: Journal Article
• Authors: Lo, Julia C.; Sehic, Emdzad; Meijer, Sebastiaan A.
• Is Part Of: Journal of cognitive engineering and decision making. Volume 11:Number 4(2017:Dec.)
• Page Start: 323
• Page End: 336
• Publication Date: 2017-12
• Subjects: cognitive processes -- topics -- command and control -- domains -- ground transportation -- domains -- workload -- topics -- analysis methods -- topics; Human-computer interaction -- Periodicals; User-centered system design -- Periodicals; 004.019
• DOI: 10.1177/1555343417716040
• Languages: English
• ISSNs: 1555-3434

Abstract

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.