Validating EmotiBit, an open-source multi-modal sensor for capturing research-grade physiological signals from anywhere on the body

Abstract

Peripheral physiological signals provide a powerful window into understanding the body and mind. Peripheral physiology devices that are currently available on the market, however, face a number of challenges. Consumer-grade devices (e.g. FitBit, Apple Watch) are easy to wear, but provide limited access to unprocessed data. Combined with black-box signal processing algorithms, this makes it difficult to interpret the data for scientific research purposes. Research-grade devices (e.g. Empatica, Shimmer, BIOPAC) provide greater access to high-quality data but remain in closed ecosystems and at price points that are out of reach for many. To bridge the gaps in available biometric solutions, our labs have created an open-source physiological sensing platform called EmotiBit (http://www.emotibit.com/), measuring EDA, multi-wavelength PPG, temperature, and 9-axis IMU. This study compares EmotiBit biometric signals to gold-standard devices by Brain Products and finds that the physiological signals exhibit a high degree of similarity, validating their use in research.