Gut-brain computer interfacing (GBCI) : wearable electrogastrography for emotion regulation

Abstract

Sound decision making relies on emotional markers created in the body when deliberating action; according to the Somatic Marker hypothesis, this process is compromised under strong and incongruous emotional states. At the same time, "gut feelings" are rooted in neuroanatomical evidence of gut-brain crosstalk. I hypothesize we could measure "gut" biosignals to help individuals regulate emotions and enhance decision-making. However, this work has not been explored in human-computer interaction (HCI). In this thesis I motivate, define and design gut-brain computer interfacing (GBCI). I define GBCIs to be interfaces that measure gut-brain activity and establish communication between the gut-brain and an external device. This thesis investigates GBCI as a closed-loop biofeedback interface for enhancing higher order cognitive functions. In specific, a GBCI for emotion regulation.

I've chosen to define and investigate GBCIs based on the Somatic Marker Hypothesis, neuroanatomical links between the enteric nervous system (ENS) and emotional processing regions of the brain, and the lack of research in gut-brain physiological computing. I designed and implemented Serosa, a non-invasive wearable interface that records gastric slow waves through electrogastrography (EGG) and provides haptic, visual or auditory biofeedback. Through three versions of Serosa, I investigated the core components of a GBCI: signal acquisition, signal processing, and feedback and output. My studies with Serosa demonstrate how EGG correlates with emotional stimuli and the usability of an EGG-based GBCI in a real-time physiological regulation intervention. Based on these results, I provide guidelines for how to implement an EGG-based GBCI. I also describe potential applications and future directions to expand upon the work. The gut-brain is not well studied compared to the brain.

In addition to creating a new area for HCI, we may also contribute new data and understandings of the relationship between higher order cognitive functions and the ENS. Ultimately, I envision GBCI showing how we can enhance cognition starting within the body versus starting within the brain.