Characterizing Eye Gaze for Assistive Device Control

Larisa Y.C. Loke; Demiana R. Barsoum; Todd D. Murphey; Brenna D. Argall

doi:10.1109/ICORR58425.2023.10304812

Characterizing Eye Gaze for Assistive Device Control

Larisa Y.C. Loke, Demiana R. Barsoum, Todd D. Murphey, Brenna D. Argall

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Eye gaze tracking is increasingly popular due to improved technology and availability. However, in assistive device control, eye gaze tracking is often limited to discrete control inputs. In this paper, we present a method for collecting both reactionary and control eye gaze signals to build an individualized characterization for eye gaze interface use. Results from a study conducted with motor-impaired participants are presented, offering insights into maximizing the potential of eye gaze for assistive device control. These findings can inform the development of continuous control paradigms using eye gaze.

Original language	English (US)
Title of host publication	2023 International Conference on Rehabilitation Robotics, ICORR 2023
Publisher	IEEE Computer Society
ISBN (Electronic)	9798350342758
DOIs	https://doi.org/10.1109/ICORR58425.2023.10304812
State	Published - 2023
Event	2023 International Conference on Rehabilitation Robotics, ICORR 2023 - Singapore, Singapore Duration: Sep 24 2023 → Sep 28 2023

Publication series

Name	IEEE International Conference on Rehabilitation Robotics
ISSN (Print)	1945-7898
ISSN (Electronic)	1945-7901

Conference

Conference	2023 International Conference on Rehabilitation Robotics, ICORR 2023
Country/Territory	Singapore
City	Singapore
Period	9/24/23 → 9/28/23

Funding

*Funding for this work was provided by UL Research Institutes through the Center for Advancing Safety of Machine Intelligence. 1Northwestern University, Evanston, IL., USA 2Shirley Ryan AbilityLab, Chicago, IL., USA

ASJC Scopus subject areas

Control and Systems Engineering
Rehabilitation
Electrical and Electronic Engineering

Access to Document

10.1109/ICORR58425.2023.10304812

Cite this

@inproceedings{09bfd48e00114765bb8e555cb9b00f6b,

title = "Characterizing Eye Gaze for Assistive Device Control",

abstract = "Eye gaze tracking is increasingly popular due to improved technology and availability. However, in assistive device control, eye gaze tracking is often limited to discrete control inputs. In this paper, we present a method for collecting both reactionary and control eye gaze signals to build an individualized characterization for eye gaze interface use. Results from a study conducted with motor-impaired participants are presented, offering insights into maximizing the potential of eye gaze for assistive device control. These findings can inform the development of continuous control paradigms using eye gaze.",

author = "Loke, {Larisa Y.C.} and Barsoum, {Demiana R.} and Murphey, {Todd D.} and Argall, {Brenna D.}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 International Conference on Rehabilitation Robotics, ICORR 2023 ; Conference date: 24-09-2023 Through 28-09-2023",

year = "2023",

doi = "10.1109/ICORR58425.2023.10304812",

language = "English (US)",

series = "IEEE International Conference on Rehabilitation Robotics",

publisher = "IEEE Computer Society",

booktitle = "2023 International Conference on Rehabilitation Robotics, ICORR 2023",

address = "United States",

}

Loke, LYC, Barsoum, DR, Murphey, TD & Argall, BD 2023, Characterizing Eye Gaze for Assistive Device Control. in 2023 International Conference on Rehabilitation Robotics, ICORR 2023. IEEE International Conference on Rehabilitation Robotics, IEEE Computer Society, 2023 International Conference on Rehabilitation Robotics, ICORR 2023, Singapore, Singapore, 9/24/23. https://doi.org/10.1109/ICORR58425.2023.10304812

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T1 - Characterizing Eye Gaze for Assistive Device Control

AU - Loke, Larisa Y.C.

AU - Barsoum, Demiana R.

AU - Murphey, Todd D.

AU - Argall, Brenna D.

PY - 2023

Y1 - 2023

N2 - Eye gaze tracking is increasingly popular due to improved technology and availability. However, in assistive device control, eye gaze tracking is often limited to discrete control inputs. In this paper, we present a method for collecting both reactionary and control eye gaze signals to build an individualized characterization for eye gaze interface use. Results from a study conducted with motor-impaired participants are presented, offering insights into maximizing the potential of eye gaze for assistive device control. These findings can inform the development of continuous control paradigms using eye gaze.

AB - Eye gaze tracking is increasingly popular due to improved technology and availability. However, in assistive device control, eye gaze tracking is often limited to discrete control inputs. In this paper, we present a method for collecting both reactionary and control eye gaze signals to build an individualized characterization for eye gaze interface use. Results from a study conducted with motor-impaired participants are presented, offering insights into maximizing the potential of eye gaze for assistive device control. These findings can inform the development of continuous control paradigms using eye gaze.

UR - http://www.scopus.com/inward/record.url?scp=85176458634&partnerID=8YFLogxK

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U2 - 10.1109/ICORR58425.2023.10304812

DO - 10.1109/ICORR58425.2023.10304812

M3 - Conference contribution

C2 - 37941208

AN - SCOPUS:85176458634

T3 - IEEE International Conference on Rehabilitation Robotics

BT - 2023 International Conference on Rehabilitation Robotics, ICORR 2023

PB - IEEE Computer Society

T2 - 2023 International Conference on Rehabilitation Robotics, ICORR 2023

Y2 - 24 September 2023 through 28 September 2023

ER -

Characterizing Eye Gaze for Assistive Device Control

Abstract

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