Self-Interfaces: Utilizing Real-Time Biofeedback in the Wild to Elicit Subconscious Behavior Change

Nava Haghighi, Arvind Satyanarayan

A variety of design iterations were explored to identify the most desirable design language ranging from more device-like designs to more biologically-inspired typologies. Actuators were linearly arranged to accommodate variation in the sequence of the beats.

Abstract

Self-Interfaces are interfaces that intuitively communicate relevant subconscious physiological signals through biofeedback to give the user insight into their behavior and assist them in creating behavior change. The human heartbeat is a good example of an intuitive and relevant haptic biofeedback; does not distract and is only felt when the heart beats fast. In this work, we discuss the design and development of a wearable haptic Self-Interface for Electrodermal Activity (EDA). EDA is a covert physiological signal correlated with high and low arousal affective states. We will evaluate the effectiveness of the EDA Self-Interface based on its intuitiveness, its ability to generate useful insight, whether this insight leads to behavior change, and whether the user can develop an intuitive awareness of their EDA over time when the device is removed. We hope the findings from this study will help us establish a series of guidelines for development of other Self-Interfaces in the future.

Citation

Self-Interfaces: Utilizing Real-Time Biofeedback in the Wild to Elicit Subconscious Behavior Change

Nava Haghighi, Arvind Satyanarayan

Work-in-Progress of ACM Tangible, Embedded, and Embodied Interaction (TEI), 2020.

Bibtex

@inproceedings{2020-self-interfaces,
 title = {{Self-Interfaces: Utilizing Real-Time Biofeedback in the Wild to Elicit Subconscious Behavior Change}},
 author = {Nava Haghighi AND Arvind Satyanarayan},
 booktitle = {Work-in-Progress of ACM Tangible, Embedded, and Embodied Interaction (TEI)},
 year = {2020},
 url = {http://vis.csail.mit.edu/pubs/self-interfaces}
}

Materials