Article, 2024

Saccade response testing during teleoperations with a head-mounted display

Cognition Technology and Work, ISSN 1435-5558, Volume 26, 1, Pages 127-138, 10.1007/s10111-023-00750-6

Contributors

Zhang G. 0000-0003-0794-3338 (Corresponding author) Hansen S.H. [1] Behrens O.R. [1] Hansen J.P. 0000-0001-5594-3645 [1]

Affiliations

  1. [1] Technical University of Denmark
  2. [NORA names: DTU Technical University of Denmark; University; Denmark; Europe, EU; Nordic; OECD]

Abstract

Head-mounted displays (HMD) are increasingly used for teleoperating robots that stream video to the operator in real time. Eye-tracking sensors that can record saccadic eye movements non-intrusively are becoming a standard feature in HMDs. Saccade tests have been widely used in human factors research and can indicate operators’ mental task resources. However, previous work has not yet explored saccade tests in robot teleoperation using an HMD. We implemented a saccade response test (SRT) and the Situation Present Assessment Method (SPAM) and conducted an experiment with 32 operators navigating a telerobot via an HMD. The SRT was significantly correlated with the SPAM metrics (response time to the prompt test and correctness of answers to SPAM queries), the performance metrics (the number of collisions, and the task completion time), and the NASA Task Load Index ratings (Physical Demand). SRT was found to be more than 10 times faster than the SPAM prompt response test as an indicator of mental workload, that is, 291 ms vs. 3125 ms. SRT was highly correlated with the SPAM prompt test (r = 0.73) and moderately correlated with task completion time and the number of collisions. SRT was able to distinguish the eight best robot operators from the eight weakest performers. Our results suggest SRT be considered part of the assessments of mental task resources, for instance, when selecting operators for industrial teleoperations with HMDs.

Keywords

Eye-tracking, Head-mounted display, Saccade, Teleoperation, Workload

Funders

  • Bevica Fonden
  • Horizon 2020-EU
  • China Scholarship Council

Data Provider: Elsevier