Good morning to everyone. I'm Davide Bacchin, and I will present our work. Gaze-based metrics of cognitive load in a conjunctive visual memory task.
The objective of our paper is measuring cognitive load during this novel task the CVSTM, which exploits conjunctive feature to overload the visual short-term memory.
The literature represents many ways to measure cognitive workload.
Among them, objective measures based on psychophysiology offer reduced intrusiveness, real time assessment, and the analysis of interpersonal variability.
In our work the aim was to validate a new experimental paradigm called CVSTM, and its ability to induce different levels of cognitive low through the exploitation of indexes based on eye-tracking method, which provides reliable and easy to access data.
Among the possible indexes, we selected two novelty ones. LHIPA that is based on the Fourier transformation of the signals derived from pupil circulation, and microsaccade magnitude.
We believe that this task could better approximate usual tasks in human computer interaction studies requiring visual, short-term memory, such as interface evaluation. To compare the ability of CVSTM to evoke different levels of cognitive load, we compare it to the well known n-back task with n used to evoke different levels of cognitive load.
In the slide, the reader can visualize this procedure, and the stimuli provided. The 1-back task was considered the easy level, while the 2-back, the hard one.
In the CVSTM, the task required remembering the location and color of a series of squares, which were 4 in the easy condition, and 8 in the hard one. The participants has to indicate if the prompt presented the same 2 features of one of them.
The procedures is schematically shown on this slide.
Accuracy measures suggest that a multi-valent feature of the easy CVSTM task indicated as significantly harder than the monovalent nature of of the easy n-back, agreeing with subjective impressions derived from NASA TLX questionnaire of significantly increased difficulty of the former versus the latter.
This data shows that LHIPA discriminates between baseline and task condition, but not between difficulty levels.
Results show LHIPA indicating n-back as the harder task and the reverse for microsadde magnitude. One possible explanation is that LHIPA is more sensitive to tasks involving short-term memory, while microsaccades are more sensitive to a visual short-term memory.
It is possible to conclude that CVSTM can be a viable tool to evoke mental effort in scenarios approximating real world Human Computer Interaction in conjunction with the use of eye tracking methods.
Thank you for your attention.