Building trust and safety correlates for autonomous systems using physiological, behavioral, and subjective measures

Zakeri, Z ORCID: https://orcid.org/0000-0003-2588-8360, Khalid, A ORCID: https://orcid.org/0000-0001-5270-6599, Omurtag, A ORCID: https://orcid.org/0000-0002-3773-8506, Breedon, P ORCID: https://orcid.org/0000-0002-1006-0942 and Hilliard, G, 2022. Building trust and safety correlates for autonomous systems using physiological, behavioral, and subjective measures. In: Industrial cognitive ergonomics and engineering psychology: proceedings of the 13th AHFE International Conference on Industrial Cognitive Ergonomics and Engineering Psychology. AHFE International. ISBN 9781958651117

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Abstract

The use of collaborative robots (cobots) in the industrial setting has grown and continues to expand globally, especially in the context of the smart factory. Mistrust and stress results, as cobots don’t provide facial, auditory, and visual cues that workers normally use to predict behavior. For quantification of mental stress, physiological, behavioral and subjective measures are integrated, processed and analyzed in a smart factory lab setting. The impact on the human workers as mental stress and fatigue conditions are correlated with the task complexity, speed of work, length of collaborative task and cobot payload etc. Multimodal functional neuroimaging was used to record participants’ neural and cardiac activity, in addition to the standard subjective and behavioral measures as they collaborated with robots in multitasking contexts. Preliminary results show that task complexity is positively correlated with beta and gamma band power, left prefrontal cortex activation, and heart rate, while it is negatively correlated with alpha band power during task performance.

Item Type:	Chapter in book
Description:	Paper presented at 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022), New York, USA, 25-28 July 2022
Creators:	Zakeri, Z., Khalid, A., Omurtag, A., Breedon, P. and Hilliard, G.
Publisher:	AHFE International
Date:	28 July 2022
Volume:	35
ISBN:	9781958651117
Identifiers:	Number Type 10.54941/ahfe1001595 DOI 1578185 Other
Divisions:	Schools > School of Science and Technology
Record created by:	Laura Ward
Date Added:	03 Aug 2022 07:53
Last Modified:	03 Aug 2022 07:53
URI:	https://irep.ntu.ac.uk/id/eprint/46816

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