To prevent undesirable effects of attention grabbing at times when a user is occupied with a difficult task, ubiquitous computing devices should be aware of the user’s cognitive load.
To advance the field of cognitive load inference in ubiquitous computing, we organize a public machine learning challenge in which competitors have to infer cognitive load from sensor data. The goal of this machine learning challenge is to recognize 2 levels of cognitive load from the sensor data of a wearable wrist-band (Microsoft Band 2). The participants will have to develop a machine-learning pipeline that will process the sensor data, create models and output the recognized cognitive load.
The best three teams will also receive prizes!
Results will be presented at UbiTtention 2020, a workshop to be held in conjunction with UbiComp 2020 Cancún, México in September 12-13. (Note: of course, conference organizers are aware of the ongoing developments with COVID-19 and will announce any necessary changes on the respective websites!)
We would be happy if you would participate!