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Analyzing the impact of cognitive load in evaluating gaze-based typing

Analyzing the impact of cognitive load in evaluating gaze-based typing
Analyzing the impact of cognitive load in evaluating gaze-based typing
Gaze-based virtual keyboards provide an effective interface for text entry by eye movements. The efficiency and usability of these keyboards have traditionally been evaluated with conventional text entry performance measures such as words per minute, keystrokes per character, backspace usage, etc. However, in comparison to the traditional text entry approaches, gaze-based typing involves natural eye movements that are highly correlated with human brain cognition. Employing eye gaze as an input could lead to excessive mental demand, and in this work we argue the need to include cognitive load as an eye typing evaluation measure. We evaluate three variations of gaze-based virtual keyboards, which implement variable designs in terms of word suggestion positioning. The conventional text entry metrics indicate no significant difference in the performance of the different keyboard designs. However, STFT (Short-time Fourier Transform) based analysis of EEG signals indicate variances in the mental workload of participants while interacting with these designs. Moreover, the EEG analysis provides insights into the users cognition variation for different typing phases and intervals, which should be considered in order to improve eye typing usability.
Eye tracking, gaze, assistive technology
IEEE
Sengupta, Korok
72599c31-2af0-4bc4-961e-de785c13a69b
Sun, Jun
cbc6b83e-3571-4f6a-b77d-51a8a20ac839
Menges, Raphael
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Staab, Steffen
bf48d51b-bd11-4d58-8e1c-4e6e03b30c49
Kumar, Chandan
4b0e33e5-7a97-4c01-88b8-d1c4c588b60a
Sengupta, Korok
72599c31-2af0-4bc4-961e-de785c13a69b
Sun, Jun
cbc6b83e-3571-4f6a-b77d-51a8a20ac839
Menges, Raphael
0badd223-5f41-4770-b475-1fa96df2f669
Staab, Steffen
bf48d51b-bd11-4d58-8e1c-4e6e03b30c49
Kumar, Chandan
4b0e33e5-7a97-4c01-88b8-d1c4c588b60a

Sengupta, Korok, Sun, Jun, Menges, Raphael, Staab, Steffen and Kumar, Chandan (2017) Analyzing the impact of cognitive load in evaluating gaze-based typing. In IEEE International Symposium on Computer-based Medical Systems, Proceedings of. IEEE.. (doi:10.1109/CBMS.2017.134).

Record type: Conference or Workshop Item (Paper)

Abstract

Gaze-based virtual keyboards provide an effective interface for text entry by eye movements. The efficiency and usability of these keyboards have traditionally been evaluated with conventional text entry performance measures such as words per minute, keystrokes per character, backspace usage, etc. However, in comparison to the traditional text entry approaches, gaze-based typing involves natural eye movements that are highly correlated with human brain cognition. Employing eye gaze as an input could lead to excessive mental demand, and in this work we argue the need to include cognitive load as an eye typing evaluation measure. We evaluate three variations of gaze-based virtual keyboards, which implement variable designs in terms of word suggestion positioning. The conventional text entry metrics indicate no significant difference in the performance of the different keyboard designs. However, STFT (Short-time Fourier Transform) based analysis of EEG signals indicate variances in the mental workload of participants while interacting with these designs. Moreover, the EEG analysis provides insights into the users cognition variation for different typing phases and intervals, which should be considered in order to improve eye typing usability.

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IEEE-CBMS-2017 - Accepted Manuscript
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More information

Accepted/In Press date: 11 April 2017
e-pub ahead of print date: 13 November 2017
Additional Information: Doc is AM version.
Venue - Dates: IEEE International Symposium on Computer-based Medical Systems, , Thessaloniki, Greece, 2017-06-22 - 2017-06-24
Keywords: Eye tracking, gaze, assistive technology
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 410252
URI: http://eprints.soton.ac.uk/id/eprint/410252
PURE UUID: c3ff0c43-a81e-4eef-abd1-897b5f526843
ORCID for Steffen Staab: ORCID iD orcid.org/0000-0002-0780-4154

Catalogue record

Date deposited: 06 Jun 2017 04:03
Last modified: 16 Mar 2024 04:22

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Contributors

Author: Korok Sengupta
Author: Jun Sun
Author: Raphael Menges
Author: Steffen Staab ORCID iD
Author: Chandan Kumar

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