Automatic Lock of Cursor Movement

Implications for an Efficient Eye-Gaze Input Method for Drag and Menu Selection

Atsuo Murata, Waldemar Karwowski

Research output: Contribution to journalArticle

Abstract

This study proposed a method—automatic lock of cursor movement (ALCM)—that locks a cursor at the center of a target at the instant the cursor enters the target. The method is intended to suppress irritating subtle cursor movements that occur when an eye-gaze input system transforms involuntary eye movement (e.g., drift) into cursor coordinates. The effectiveness of the proposed ALCM was verified using pointing performance (speed and accuracy) in two types of HCI tasks. In a drag task, we compared mouse input versus eye-gaze input with use of a backspace (BS) key or voice input. The key or voice facilitates target selection once the eye gaze was aligned with a target. In a menu selection task, we also compared mouse input with eye-gaze and the use of two voice input conditions. This task required gaze alignment with a menu and menu item by use of voice input for selection. Whether the ALCM function was added to the eye-gaze input system or not was a within-subject factor. The input method and target sizes were within-subject factors. The study concluded that the ALCM improved pointing accuracy for all eye-gaze input methods and all two tasks.

Original languageEnglish
JournalIEEE Transactions on Human-Machine Systems
DOIs
Publication statusAccepted/In press - Jan 1 2018

Fingerprint

Speech recognition
Drag
Eye movements
Human computer interaction

Keywords

  • Atmospheric measurements
  • Automotive lock of cursor movement (ALCM)
  • click
  • drag
  • HCI
  • Human computer interaction
  • involuntary eye movement
  • menu selection
  • Mice
  • pointing time
  • prediction accuracy
  • Presses
  • Pressing
  • Task analysis
  • Visualization

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Control and Systems Engineering
  • Signal Processing
  • Human-Computer Interaction
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

@article{c41b128742b049878516af2cc660b43b,
title = "Automatic Lock of Cursor Movement: Implications for an Efficient Eye-Gaze Input Method for Drag and Menu Selection",
abstract = "This study proposed a method—automatic lock of cursor movement (ALCM)—that locks a cursor at the center of a target at the instant the cursor enters the target. The method is intended to suppress irritating subtle cursor movements that occur when an eye-gaze input system transforms involuntary eye movement (e.g., drift) into cursor coordinates. The effectiveness of the proposed ALCM was verified using pointing performance (speed and accuracy) in two types of HCI tasks. In a drag task, we compared mouse input versus eye-gaze input with use of a backspace (BS) key or voice input. The key or voice facilitates target selection once the eye gaze was aligned with a target. In a menu selection task, we also compared mouse input with eye-gaze and the use of two voice input conditions. This task required gaze alignment with a menu and menu item by use of voice input for selection. Whether the ALCM function was added to the eye-gaze input system or not was a within-subject factor. The input method and target sizes were within-subject factors. The study concluded that the ALCM improved pointing accuracy for all eye-gaze input methods and all two tasks.",
keywords = "Atmospheric measurements, Automotive lock of cursor movement (ALCM), click, drag, HCI, Human computer interaction, involuntary eye movement, menu selection, Mice, pointing time, prediction accuracy, Presses, Pressing, Task analysis, Visualization",
author = "Atsuo Murata and Waldemar Karwowski",
year = "2018",
month = "1",
day = "1",
doi = "10.1109/THMS.2018.2884737",
language = "English",
journal = "IEEE Transactions on Human-Machine Systems",
issn = "2168-2291",
publisher = "IEEE Systems, Man, and Cybernetics Society",

}

TY - JOUR

T1 - Automatic Lock of Cursor Movement

T2 - Implications for an Efficient Eye-Gaze Input Method for Drag and Menu Selection

AU - Murata, Atsuo

AU - Karwowski, Waldemar

PY - 2018/1/1

Y1 - 2018/1/1

N2 - This study proposed a method—automatic lock of cursor movement (ALCM)—that locks a cursor at the center of a target at the instant the cursor enters the target. The method is intended to suppress irritating subtle cursor movements that occur when an eye-gaze input system transforms involuntary eye movement (e.g., drift) into cursor coordinates. The effectiveness of the proposed ALCM was verified using pointing performance (speed and accuracy) in two types of HCI tasks. In a drag task, we compared mouse input versus eye-gaze input with use of a backspace (BS) key or voice input. The key or voice facilitates target selection once the eye gaze was aligned with a target. In a menu selection task, we also compared mouse input with eye-gaze and the use of two voice input conditions. This task required gaze alignment with a menu and menu item by use of voice input for selection. Whether the ALCM function was added to the eye-gaze input system or not was a within-subject factor. The input method and target sizes were within-subject factors. The study concluded that the ALCM improved pointing accuracy for all eye-gaze input methods and all two tasks.

AB - This study proposed a method—automatic lock of cursor movement (ALCM)—that locks a cursor at the center of a target at the instant the cursor enters the target. The method is intended to suppress irritating subtle cursor movements that occur when an eye-gaze input system transforms involuntary eye movement (e.g., drift) into cursor coordinates. The effectiveness of the proposed ALCM was verified using pointing performance (speed and accuracy) in two types of HCI tasks. In a drag task, we compared mouse input versus eye-gaze input with use of a backspace (BS) key or voice input. The key or voice facilitates target selection once the eye gaze was aligned with a target. In a menu selection task, we also compared mouse input with eye-gaze and the use of two voice input conditions. This task required gaze alignment with a menu and menu item by use of voice input for selection. Whether the ALCM function was added to the eye-gaze input system or not was a within-subject factor. The input method and target sizes were within-subject factors. The study concluded that the ALCM improved pointing accuracy for all eye-gaze input methods and all two tasks.

KW - Atmospheric measurements

KW - Automotive lock of cursor movement (ALCM)

KW - click

KW - drag

KW - HCI

KW - Human computer interaction

KW - involuntary eye movement

KW - menu selection

KW - Mice

KW - pointing time

KW - prediction accuracy

KW - Presses

KW - Pressing

KW - Task analysis

KW - Visualization

UR - http://www.scopus.com/inward/record.url?scp=85058870919&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85058870919&partnerID=8YFLogxK

U2 - 10.1109/THMS.2018.2884737

DO - 10.1109/THMS.2018.2884737

M3 - Article

JO - IEEE Transactions on Human-Machine Systems

JF - IEEE Transactions on Human-Machine Systems

SN - 2168-2291

ER -