Good afternoon
I am Tanya Bafna
Welcome to the presentation of my paper
titled 'Cognitive Load during Eye-typing'
submitted to ETRA 2020.
My co-authors from the paper are
John Paulin Hansen and Per Bækgaard from Technical University of Denmark.
I would like to start with defining a multidimensional construct familiar to some of us – cognitive load.
It is defined as the load on the cognitive system when performing a mentally demanding task.
It can also affect task performance.
It can be measured using various physiological signals, including phasic changes in pupil size.
Cognitive load measurement finds use in real-life applications,
in detection of the load experienced by surgeons during microsurgeries
which require a lot of training and precision by the surgeon,
or the load experienced during a complex activity such as driving,
which includes being attentive to multiple visual sources and reacting to them,
in addition to audio disturbances such as conversation with the passengers or radio.
These examples are also indicative of situations where the users' hands are pre-occupied
and physiological signals, such as pupil size, are the most effective method for continuous cognitive load measurement.
In this paper, we have applied techniques of cognitive load measurement using eye-tracking
in a similar field of hands-free application related to accessibility.
People with motor disabilities can lose control of their voluntary muscles, including arms and vocal chords.
The most common method of communication for them is with an eye-tracker,
where they use eyes to fixate on the keys of an on-screen keyboard for a short time.
The fixated keys are detected and used to select letters and form words and sentences in a task of eye-typing.
The research goal of the paper was to explore the usability of the existing eye-metrics for cognitive load detection
during an interactive eye-tracking task of eye-typing via an experiment with able-bodied individuals.
Cognitive load was induced in the experiment by designing a task of sentence memorization with two difficulty levels – easy and difficult.
Examples of each difficulty level are provided in the table.
The trial was divided into the following sections – reading and memorizing the sentence,
and thereafter eye-typing the sentence.
At the end of the trial, the participants were asked to rate the cognitive load experienced during eye-typing --
which provided data on the subjective score of cognitive load.
The keyboard that you see was used as an on-screen keyboard on a monitor, and a Tobii Eye-tracker 4C was mounted on the monitor to record the eye data.
The participants performed 2 sessions in a day, with one session being easy, and the other difficult.
Each participant performed the experiment on 4 different days.
The order of the easy and difficult sessions was balanced within the participant.
18 able-bodied university students participated in the experiment,
out of which 9 identified themselves as males, and 9 identified as females.
The average age of the participants was 25.5 years.
I will present the results in the following 3 sections:
the subjective score on cognitive load, pupil size and performance on the task of eye-typing.
First, starting with the subjective scores..
In response to the question ‘how hard did you have to work to accomplish your level of performance, on a scale of 1 to 7?’,
the participants gave an average score of 2.9 to the task of eye-typing easy sentences,
and an average score of 4.7 to the task of eye-typing difficult sentences.
To observe the physiological signals of pupil size changes,
absolute and relative pupil sizes were averaged for 300 milliseconds, at different phases of the trial:
(1) during the baseline, which was before starting the trial, (2) when starting to read and memorize, (3) towards the end of reading and memorizing the sentence,
(4) when starting to write and finally (5) when ending writing the sentence.
The absolute pupil size increased from the baseline, reaching a maximum when finishing reading and memorizing the sentence,
indicating that the sentence was in memory at this point of time.
Thereafter, the pupils constricted, when the participants finished writing the sentence.
This pupil constriction at the end of the trial has also been noted in literature, as an indication of relief of memory load.
When observing the relative pupil size
and if the pupils reacted differently during easy and difficult trials, we found that the difference was not significant.
Finally, we recorded the task performance, indicated by typing performance, to find out if these data might also be used to measure the cognitive load.
Typing speed, or the words typed per minute was higher for easy sessions, than difficult by 1.1 words per minute.
The uncorrected error rate, or the errors that the participants did NOT correct during typing, were higher by 20% for the difficult sessions compared to the easy sessions.
As observed in the results, the subjective scores and phasic pupil size indicate that
memorization of sentences and eye-typing can be used for cognitive load measurement.
The task difficulty was also observed in the task performance.
This experiment was performed with able-bodied university students.
It will need to be replicated with people with motor disability, who actually use eye-typing in their daily lives.
Further applications of cognitive load measurement could be --
to design on-screen keyboards that will generate lower cognitive load during eye-typing.
This has been tested by Sengupta et al., but they used EEG signals to measure the cognitive load.
Another application could be to design navigation interfaces for virtual and augmented reality.
Thank you for listening to my talk.
I look forward to your questions.
In case I am not able to answer any questions today, feel free to write to me.