  Mindfulness and relaxation techniques for mental health are increasingly
being explored in the human-computer interaction community. Physiological
signals and their visualization have often been exploited together in a form of
biofeedback with other intervention methods. Here, we aim to contribute to the
body of existing work on biofeedback interfaces for mindfulness, with a
particular focus on incorporating artistic effects into physiological signal
visualization. With an implemented artistic biofeedback interface, we conduct a
pilot study where 10 participants attend stress-induction sessions followed by
two biofeedback mindfulness sessions: classic biofeedback and artistic
visualization. The result demonstrates that artistic visualization-driven
biofeedback significantly improves the effectiveness of biofeedback in helping
users feel relaxed in comparison with a classic graphical form of biofeedback.
Also, it shows that the artistic effect makes it easy to understand what
biofeedback represents. Future work includes exploring how advanced
physiological computing methods can improve its efficiency and performance.
