Trends and Opportunities for Open-Source Biometric Sensing Applications in Human Factors & Related Fields

Abstract

Biometric signals are poised to enhance the research landscape of Human Factors (HF) and related fields. However, many existing research-grade biometric devices run on expensive, proprietary systems, while consumer-grade devices are closed source, offering limited or no access to the data. To address this gap we developed EmotiBit, a scientifically-validated, wearable, open-source, biometric sensor module capable of collecting a range of emotional, physiological, and movement data. Affordable, open-source, non-invasive hardware can lower the barrier to entry for academic labs and industry practitioners to integrate research-grade physiological sensing into their Research & Development (R&D) workflows. After 5 years on the market, we have begun to see trends in the way that EmotiBit is being utilized in both research and industry settings. In this paper, we survey the landscape of scientific applications using EmotiBit and report on the impact of open-source biometric sensing on HF and related fields.