EFFECTIVE USE OF PHYSIOLOGICAL METRICS TO ASSESS USER EMOTION AND BEHAVIOR INTENTION BASED ON AN EYE TRACKER AND NEUROPHYSIOLOGICAL APPROACH

Abstract

Products are successfully designed only when they are in accord with the users’ emotional needs. A systematic research approach is aimed to propose that physiological metrics can be effectively used to assess user emotion and behavior intention based on an eye tracker and neurophysiological approach. Forty participants (20 males and 20 females, mean age=35.6, SD=6.38, range 21-48 years), were recruited from college campuses and communities to conduct an eye tracker and electroencephalography (EEG) experiment with the presented stimuli (images of SUVs). The study uses partial least squares structural equation modeling (PLS-SEM) to test the model hypotheses. The results show a strong and significant relationship between eye tracker metrics, neurophysiological metrics, user affective responses, and behavior intention. These findings could enable industrial counselors, professional product designers, and academics to categorize users’ emotional needs that can be subsequently incorporated into final product design.