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António Tavares, José Luís Silva & Rodrigo Ventura (2023). Physiologically Attentive User Interface for Improved Robot Teleoperation. ACM IUI'23.

A. Tavares et al.,  "Physiologically Attentive User Interface for Improved Robot Teleoperation", in ACM IUI'23, 2023

@misc{tavares2023_1728131061833,
	author = "António Tavares and José Luís Silva and Rodrigo Ventura",
	title = "Physiologically Attentive User Interface for Improved Robot Teleoperation",
	year = "2023",
	url = "https://iui.acm.org/2023/index.html"
}

TY  - CPAPER
TI  - Physiologically Attentive User Interface for Improved Robot Teleoperation
T2  - ACM IUI'23
AU  - António Tavares
AU  - José Luís Silva
AU  - Rodrigo Ventura
PY  - 2023
UR  - https://iui.acm.org/2023/index.html
AB  - User interfaces (UI) are shifting from being attention-hungry to
being attentive to users’ needs upon interaction. Interfaces developed
for robot teleoperation can be particularly complex, often
displaying large amounts of information, which can increase the
cognitive overload that prejudices the performance of the operator.
This paper presents the development of a Physiologically Attentive
User Interface (PAUI) prototype preliminary evaluated with
six participants. A case study on Urban Search and Rescue (USAR)
operations that teleoperate a robot was used although the proposed
approach aims to be generic. The robot considered provides an
overly complex Graphical User Interface (GUI) which does not
allow access to its source code. This represents a recurring and
challenging scenario when robots are still in use, but technical
updates are no longer offered that usually mean their abandon. A
major contribution of the approach is the possibility of recycling
old systems while improving the UI made available to end users
and considering as input their physiological data. The proposed
PAUI analyses physiological data, facial expressions, and eye movements
to classify three mental states (rest, workload, and stress).
An Attentive User Interface (AUI) is then assembled by recycling a
pre-existing GUI, which is dynamically modified according to the
predicted mental state to improve the user’s focus during mentally
demanding situations. In addition to the novelty of the proposed
PAUIs that take advantage of pre-existing GUIs, this work also contributes
with the design of a user experiment comprising mental
state induction tasks that successfully trigger high and low cognitive
overload states. Results from the preliminary user evaluation
revealed a tendency for improvement in the usefulness and ease of
usage of the PAUI, although without statistical significance, due to
the reduced number of subjects.
ER  -