Measuring archetypal experiences with physiological sensors

Research in human computer interaction (HCI) has made remarkable progress, moving from simple pointing or touchbased interfaces to more advanced interaction paradigms powered by physiological computing, in which physiological data serves as input to the computer system.1 Computing interfaces take measurements—such as heart rate and skin conductance—which can be analyzed to measure cognitive2 and affective3 aspects of user activities. Research in psychology4, 5 and neuroscience6 has provided evidence that people are not aware of their own cognitive processes, and are not able to report accurately on them.7 Thus, developing computer systems that can report on cognitive processes is of interest. A considerable part of human experience is tied to the unconscious. The unconscious experience can be indirectly assessed by methods developed in psychophysiology,8 which are similar to measurements employed in physiological computing. Carl Jung described the content of the unconscious as ‘archetypes’ or ‘pre-existent forms.’ Archetypes are close analogies to instincts, which are impersonal, inherited traits that shape and motivate human behavior without consciousness. Computer recognition of archetypal experiences remains a largely unexplored area of HCI. 9, 10 Having a model of unconscious behaviors would enable novel interactions, and it would allow a HCI system to respond to changes in the unconscious levels of human experience. We examined the possibility of sensing and distinguishing between various archetypal experiences based on the analysis of physiological signals. First, we used film clips to elicit eight archetypal experiences (anima, animus, hero-departure, hero-initiation, hero-return, mentor, mother, and shadow) in our test subjects. Film clips are effective in capturing the attention Figure 1. The dynamic patterns of heart rate responses (mean values and 95% confidence intervals) of participants during various archetypal experiences, as elicited through film clips.