Calm beats cute: designing aesthetic-functional congruence in human-robot interaction for breathing companion robots

Which robot would you trust to guide you through a breathing exercise, a cute cartoon-like humanoid, a soft animal companion, a clinical mechanical device, or a serene meditative figure? This study examines how four design aesthetics affect social evaluation and technology acceptance of Neffy, a social breathing-companion robot that supports stress relief and wellbeing by guiding exercises through visual, audio, and haptic cues synchronized with upper-body movement.

In an online study, 126 participants viewed a video of a person interacting with Neffy during a guided breathing exercise. Four design styles were tested: cartoonish humanoid, meditative humanoid, animal-like (zoomorphic), and machine-like (mechanomorphic). Participants rated each style on warmth, competence, perceived enjoyment, and intention to use, and made pairwise comparisons of human-likeness, social presence, trustworthiness, breathing companion preference, and overall liking.

The zoomorphic design received the highest warmth ratings, the mechanomorphic design scored lowest across all measures. Perceived human-likeness positively predicted both warmth and competence, confirming its role in social evaluation. However, human-likeness alone did not determine preference: despite comparable perceived human-likeness between the two humanoid designs, the meditative humanoid achieved the highest scores for competence, trustworthiness, and breathing companion preference, outperforming the cartoon-like humanoid.

These results suggest that "calm" aesthetics are preferred over "cute" aesthetics for wellbeing robots, challenging the assumption that human-likeness alone drives design success. Instead, aesthetic-functional congruence-alignment between a robot's visual design and its functional purpose, appears to be a critical, under-explored factor in social robot design for wellbeing. Since this study assessed general evaluations, future work should test whether these preferences hold across application domains (e.g. clinical, workplace, educational, domestic) and cross-cultural contexts.