Emotional states influence a wide range of cognitive processes, such as attention, memory, and decision-making, and play an increasingly recognized role in human-computer interaction (HCI). Although most prior research has focused on high-level effects of emotion, the impact of incidental emotional states on fine-grained motor behaviors such as pointing and selection remains understudied. Addressing this gap, the present study examines how affective priming with validated emotional stimuli modulates user performance in a Fitts’ Law-based pointing paradigm. By systematically varying task difficulty, we quantitatively assess the effects of emotion on core performance measures: movement time, reaction time, error rate, and throughput. Our findings demonstrate that emotion can modulate low-level motor interactions in digital environments, with important implications for the design of adaptive, emotion-aware interfaces. These results advance the theoretical understanding of the interplay between emotion, cognition, and motor control and offer actionable insights to develop more robust and personalized interactive systems.
ACM CHI Conference on Human Factors in Computing Systems