3DA: Assessing 3D-Printed Electrodes for Measuring Electrodermal Activity
Martin Schmitz, Dominik Schön, Henning Klagemann, Thomas Kosch
CHI 2024: The ACM CHI Conference on Human Factors in Computing Systems
Session: Late-Breaking Work: Hardware, Fabrication, and New Devices
Electrodermal activity (EDA) reflects changes in skin conductance, which are closely tied to human psychophysiological states. For example, EDA sensors can assess stress, cognitive workload, arousal, or other measures tied to the sympathetic nervous system for interactive human-centered applications. Yet, current limitations involve the complex attachment and proper skin contact with EDA sensors. This paper explores the concept of 3D printing electrodes for EDA measurements, integrating sensors into arbitrary 3D-printed objects, alleviating the need for complex assembly and attachment. We examine the adaptation of conventional EDA circuits for 3D-printed electrodes, assessing different electrode shapes and their impact on the sensing accuracy. A user study (N=6) revealed that 3D-printed electrodes can measure EDA with similar accuracy, suggesting larger contact areas for improved precision. We derive design implications to facilitate the integration of EDA sensors into 3D-printed devices to foster diverse integration into everyday objects for prototyping physiological interfaces.
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Pre-recorded video presentations for Late-Breaking Works at CHI 2024
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