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.