Combined analysis of Electroencephalography and eyetracking to create new windows into cognitive human-machine interaction

Wobrock D (2022)
Bielefeld: Universität Bielefeld.

Bielefelder E-Dissertation | Englisch
 
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Abstract / Bemerkung
Since their inception, machines, computers and robots have steadily grown in complexity to solve ever more complicated problems. For these systems of ever-growing complexity to be usable by the largest number of people, they need to be made affordant through tests evaluating system interactions. These tests have however shortcomings, leaving users sometimes lost and frustrated with these systems. In this work, we improve these interface evaluation test by relying on a Brain-Computer Interface combining Electroencephalography with Eyetracking. We use this bi-modal setup to provide complementary insights about a user’s perception which can be gathered from any interaction scenario. To achieve this, we have created a set of methods which allow our system to be applicable and informative in a variety of situations. For scenario transposability we developed the Fixation-based Component Synchronization method, allowing to reestablish synchronous recordings even when markers are lacking. Using both recording modalities and the Fixation-related Potentials observable thanks to them, we propose four different methods which provide insight into how user’s perceive the considered interaction. These four methods are the General Difficulty via Eyetracking (GDET) method, the Steady Peak Property Quantification (SPPQ) method, the Segment Frequency Bands Analysis (SFBA) method and the User-dependent Potential Variation (UdPV) method. These four methods provide respectively information about difficulties relating to the explored environment as a whole, specific elements in the environment, the task with which the environment is explored and specificities about the strategy with which the user explores the environment. We discuss and test the extent of all four of these methods in a series of three laboratory studies presenting artificial and natural interaction scenarios. The three scenarios presents different tasks and levels of difficulty allowing to establish the utility of these methods and verify their transposability between situations. All proposed methods are simple to implement and offer a new way to approach the analysis of interaction, both in a design environment and as a promising way to create adaptive interfaces.
Jahr
2022
Seite(n)
210
Page URI
https://pub.uni-bielefeld.de/record/2960703

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Wobrock D. Combined analysis of Electroencephalography and eyetracking to create new windows into cognitive human-machine interaction. Bielefeld: Universität Bielefeld; 2022.
Wobrock, D. (2022). Combined analysis of Electroencephalography and eyetracking to create new windows into cognitive human-machine interaction. Bielefeld: Universität Bielefeld. https://doi.org/10.4119/unibi/2960703
Wobrock, D. (2022). Combined analysis of Electroencephalography and eyetracking to create new windows into cognitive human-machine interaction. Bielefeld: Universität Bielefeld.
Wobrock, D., 2022. Combined analysis of Electroencephalography and eyetracking to create new windows into cognitive human-machine interaction, Bielefeld: Universität Bielefeld.
D. Wobrock, Combined analysis of Electroencephalography and eyetracking to create new windows into cognitive human-machine interaction, Bielefeld: Universität Bielefeld, 2022.
Wobrock, D.: Combined analysis of Electroencephalography and eyetracking to create new windows into cognitive human-machine interaction. Universität Bielefeld, Bielefeld (2022).
Wobrock, Dennis. Combined analysis of Electroencephalography and eyetracking to create new windows into cognitive human-machine interaction. Bielefeld: Universität Bielefeld, 2022.
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2022-01-24T08:38:26Z
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