Annotating Affect in the Field: A Case Study on the Usability of a Minimalist Smartwatch User Interface for Affect Annotation

Abstract

Successful empathetic interaction requires an accurate understanding of the interaction partner’s affect dynamics. Self-reported annotations provide a way to better understand affect and empathy in real-life; however, the necessary user interactions for collecting such data must be designed to be as unobtrusive as possible. To address this challenge, we explore the potential of a smartwatch annotation application for affect that aims to minimize user interaction effort while maximizing usability. In a field study conducted as part of a student career fair (N=9), we evaluated the feasibility and usability of our app. Participants reported high usability scores and our data collection successfully captured self-reported affect labels at a high temporal resolution. Our work contributes to the challenge of providing minimal obtrusive applications for the collection of self-reported labels of affective states.