hosted by PhD Program in CS @ TU KL
"User´s ongoing physiological and mental state recognition using multimodal sensor approach"
The work is focused on the investigation and automatic recognition of the user´s cognitive state measuring its physiological markers. With the expanding number of low-cost and non-invasive physiological sensors, access to the physiological data is becoming easier, the amount of available data is increasing. Previous studies demonstrated, that the combination of this data with machine learning algorithms significantly enhances the development of automatic, user-independent models. However, the focus of these studies is heavily directed to the classification results of the built models, neglecting the meaningfulness of used physiological features and appropriateness of the used sensors. This procedure raises serious issues for the future reproducibility of reported results.
To overcome this gap, in my first field study I investigated phenomena of mind wandering using data from an electrodermal activity sensor and an eye-tracker. I did not only develop an ML model for mind wandering detection but also used behavioral data to increase the explanatory power of the developed model. The physiological markers were also extensively discussed.
|Time:||Monday, 22.02.2021, 15:45|