Prakash Mishra

This paper introduces BB-STT, a deep learning framework that classifies smartphone interaction behaviors using multimodal physiological signals, achieving high accuracy in distinguishing between different activities.

The paper presents a multimodal dataset of EEG, eye-tracking, and physiological signals during smartphone interactions and relaxation, enabling analysis of neural and autonomic responses.

This study examines how personalized smartphone notifications affect neural responses across processing stages, finding that they engage robust early salience detection while habitual use affects later attentional and evaluative processing.