Conference Paper/Proceeding/Abstract 521 views 205 downloads
Crucial Clues: Investigating Psychophysiological Behaviors for Measuring Trust in Human-Robot Interaction
,
Abdullah Alzahrani
ICMI '23: Proceedings of the 25th International Conference on Multimodal Interaction, Pages: 135 - 143
Swansea University Authors:
Muneeb Ahmad , Abdullah Alzahrani
-
PDF | Accepted Manuscript
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. © 2023 Copyright held by the owner/author(s).
Download (3.14MB)
DOI (Published version): 10.1145/3577190.3614148
Abstract
Existing work on the measurements of trust during Human-Robot Interaction (HRI) indicates that psychophysiological behaviours (PBs) have the potential to measure trust. However, we see limited work on the use of multiple PBs in combination to calibrate human's trust in robots in real-time durin...
| Published in: | ICMI '23: Proceedings of the 25th International Conference on Multimodal Interaction |
|---|---|
| ISBN: | 979-8-4007-0055-2 |
| Published: |
New York, NY, USA
ACM
2023
|
| URI: | https://cronfa.swan.ac.uk/Record/cronfa64073 |
| Abstract: |
Existing work on the measurements of trust during Human-Robot Interaction (HRI) indicates that psychophysiological behaviours (PBs) have the potential to measure trust. However, we see limited work on the use of multiple PBs in combination to calibrate human's trust in robots in real-time during HRI. Therefore, this study aims to estimate human trust in robots by examining the differences in PBs between trust and distrust states. It further investigates the changes in PBs across repeated HRI and also explores the potential of machine learning classifiers in predicting trust levels during HRI. We collected participants' electrodermal activity (EDA), blood volume pulse (BVP), heart rate (HR), skin temperature (SKT), blinking rate (BR), and blinking duration (BD) during repeated HRI. The results showed significant differences in HR and SKT between trust and distrust groups and no significant interaction effect of session and decision for all PBs. Random Forest classifier achieved the best accuracy of 68.6% to classify trust, while SKT, HR, BR, and BD were the important features. These findings highlight the value of PBs in measuring trust in real-time during HRI and encourage further investigation of trust measures with PBs in various HRI settings. |
|---|---|
| Keywords: |
Trust, Measurement, Psychophysiological behaviours, Human-Robot Interaction, Real-time |
| College: |
Faculty of Science and Engineering |
| Start Page: |
135 |
| End Page: |
143 |