human factors engineers

Abstract: Transcutaneous Electrical Stimulation (TES) for stress modulation has largely focused on vagus nerve stimulation at the neck, yet two questions remain underexplored: how users experience electrotactile sensations at this sensitive site, and whether electrotactile feedback itself can function as a haptic stress intervention. To investigate this gap, we applied an 8-node TES array to two body sites during a cognitively demanding 2-back task: the neck, a site used in prior vagal TES research for its anatomical proximity to the cervical vagus nerve, and the arm, the most common haptic wearable site, which primarily provides cutaneous electrotactile sensation without vagal access. In a usability study, both sites were rated as comparably comfortable without disrupting task performance, though the same stimulation was interpreted differently across sites. A second study assessing the physiological effects of active versus inactive stimulation under identical electrode attachment revealed that only neck TES produced cortical and autonomic changes consistent with stress modulation, while arm TES did not differ from inactive conditions. These findings suggest that neck TES can be acceptable despite the site's sensitivity, and that both the physiological effects and the sensory experience of TES depend on placement.

Abstract: Much of what we know about human perception and cognition comes from austere experimental settings: static stimuli presented to sedentary observers on flat monitors, complex responses reduced to simple button presses, and brain activity recorded from immobilized heads using EEG or fMRI. These highly controlled paradigms have provided remarkable insights, but capture a small and often unusual slice of behavior, raising questions about how well the findings generalize to the real world. Extended reality (XR), spanning both immersive virtual reality (VR) and augmented reality (AR) that overlays digital content on the real world, offers a way beyond these constraints, supporting controlled, reproducible experiments in which participants actively engage with three-dimensional tasks. Drawing on a growing body of VR and AR studies of attention, memory, and language -- our own and others', some involving EEG -- we outline what XR makes newly possible for cognitive neuroscience and reflect on the practical and conceptual obstacles that remain. The opportunities are substantial, but realizing them requires solving practical problems of hardware, timing, and measurement, and being realistic about what a virtual or augmented world can and cannot stand in for.

Abstract: False-positive computer-aided detection (CADe) prompts may divert endoscopists' attention during colonoscopy, yet the attentional impact of individual prompts remains unclear. We used event-locked eye tracking to quantify gaze attraction and attention occupation in complementary retrospective and prospective studies. In a retrospective paired-video experiment, 3 senior and 2 novice endoscopists viewed 60 colonoscopy videos with and without CADe. The prospective study recorded gaze during 42 real-time CADe-assisted colonoscopies performed by 9 senior endoscopists. Screened CADe prompts outside expert-annotated lesion windows were classified as false-positive artifact events. False-positive prompts attracted gaze in 48.6% (68/140) of retrospective observations and 65.2% (533/817) of prospective events. Among attraction events with complete recovery, median attention occupation lasted 1000 ms in the retrospective study and 1100 ms in the prospective study. Corresponding median prompt durations were 33 ms and 267 ms, with median time amplifications of 17.55-fold and 5.15-fold, respectively. In paired retrospective comparisons, visible artifact prompts drew gaze closer to the prompted region than did the same-coordinate unassisted reference. Secondary retrospective analyses showed high lesion gaze recognition without and with CADe (98.0% versus 99.0%). First gaze entry into lesion regions occurred 147.8 ms earlier with CADe. Across controlled and real-time clinical settings, false-positive CADe prompts frequently captured gaze, with attention persisting beyond prompt visibility. These findings support considering prompt-related attentional burden in CADe evaluation and design.

Abstract: In this article, we present TeamCAMS (Cabin Air Management System), a collaborative work environment for simulating human-AI (artificial intelligence) interaction for scientific research. The article outlines how several psychological theories guided the development of this multiple-task simulation. Modelling a process control environment, previous versions of TeamCAMS have already been used in empirical studies to address a wide range of research questions (e.g., comparing different forms of automation, evaluating impact of automation reliability, effects of stress on multiple-task performance). Outlining the technical possibilities offered by TeamCAMS, the article points out how its latest version offers researchers the possibility of addressing a set of new research questions including problems associated with teamwork (e.g., within-team conflict, distributed teamwork) and human-AI interaction. Finally, we will outline how this simulation environment can be enhanced further still to address research questions in new fields (e.g., automation of leadership). To promote transparency, reproducibility, and further development, TeamCAMS is made available to the research community under an open-source license.

Abstract: Physical teleoperation integrates human cognitive flexibility with robotic precision, yet demanding manipulation tasks frequently induce severe cognitive workload, acute frustration, and execution breakdown. Conventional shared autonomy paradigms rely primarily on task-based rules, such as spatial error boundaries, which disregard the operator's transient affective state and risk misaligned control interventions. To address this limitation, we propose an affect-aware shared autonomy teleoperation framework that dynamically modulates robotic assistance based on real-time operator state estimation. The system estimates operator affective states from synchronized facial video, cardiac signals, and bilateral arm kinematics, outputting a seven-state affective distribution and a three-category operational abstraction (neutral, productive, adverse). Affect-aware assistance is selectively triggered when the user is detected in a continuous adverse state, preserving task-positive engagement without unnecessary disruption. The empirical user study ($N = 30$) confirms that the proposed affective assistance increases the productive states by up to 39.7% without compromising user agency. The collected dataset represents the first multimodal dataset that provides continuous visual, physiological, and operator's bilateral motion tracking of temporal affective state shifts during bimanual teleoperation. Our multimodal fusion model outperforms zero-shot baselines (Qwen, MiniCPM-V) in tracking temporal state dynamics. This real-world deployment offers a new human-centric framework that integrates visual, physiological, and motion tracking for physical human-robot interaction.

Abstract: Prototyping and evaluating human-robot teaming (HRT) scenarios in the real-world is costly. Virtual simulation of HRT scenarios has been adopted as an alternative to conducting user studies in the real-world to investigate user perceptions, behaviors, and performance during human-robot interactions. The consistency of human behavior between the real and virtual-worlds is integral to the validity of utilizing such virtual experimentation. This paper presents a user study examining the difference in human behavior between an HRT scenario conducted in a virtual vs real environment. We employed mixed-methods to examine team performance and human factors during the HRT. Our quantitative results showed a significant difference in workload between the two modalities. Our qualitative analysis expanded on the quantitative results and found differences in participants' strategy, their mental model of robots, and the type of trust they had for robots between modalities.

Abstract: Maritime Autonomous Surface Ships (MASS) and AI- supported decision assistants are expected to transform maritime operations, but their safe integration depends on how maritime professionals perceive and trust such systems. This paper presents a survey study on maritime stakeholders' attitudes toward an AI-supported assistant in collision-avoidance scenarios. Participants evaluated technology anxiety, trust in automation, and explanation quality using established and adapted questionnaires, complemented by sentiment and thematic analysis of open-ended responses Results indicate a generally positive disposition toward maritime technology, no clear age-related differences in openness, stable trust across scenarios, and more scenario-sensitive, multidimensional explanation ratings. Open responses showed that participants valued support for decision-making, situation awareness, and confidence-building, while raising concerns about AI reliability, over- reliance and loss of expertise. The findings suggest that maritime AI systems should not focus solely on increasing automation or trust, but on supporting calibrated reliance through transparent, reliable, and operationally meaningful design with domain experts in the loop.