Translating Emotions to Annotations: A Participant's Perspective of Physiological Emotion Data Collection

Physiological signals hold immense potential for ubiquitous emotion monitoring, presenting numerous applications in emotion recognition. However, harnessing this potential is hindered by significant challenges, particularly in the collection of annotations that align with physiological changes since the process hinges heavily on human participants. In this work, we set out to study human participants' perspectives in the emotion data collection procedure. We conducted a lab-based emotion data collection study with 37 participants using 360 • virtual reality video stimulus followed by semi-structured interviews with the study participants. Our findings presented that intrinsic factors like participants' perception, experiment design nuances, and experiment setup suitability impact their emotional response and annotation within lab settings. Drawing from our findings and prior research, we propose recommendations for incorporating participants' context into annotations and emphasizing participant-centric experiment designs. Furthermore, we explore current emotion data collection practices followed by AI practitioners and offer insights for future contributions leveraging physiological emotion data.

CCS Concepts: • Human-centered computing → Empirical studies in HCI.