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

7 Pages Posted: 13 Feb 2024

See all articles by Sean Montgomery

Sean Montgomery

University of Nevada, Reno - Department of Psychology

Nitin Nair

Connected Future Labs

Phoebe

affiliation not provided to SSRN

Suzanne Dikker

New York University

Date Written: October 5, 2022

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.

Keywords: Affective computing, Biometrics, Physiological signals, Multi-modal sensing, PPG, Heart rate, Electrodermal activity, EDA, GSR, Galvanic skin response, Temperature, Motion, IMU, accelerometer, gyroscope, magnetometer, emotions, health, wellness, peripheral nervous system, PNS

Suggested Citation

Montgomery, Sean and Nair, Nitin and Chen, Hanzhi and Dikker, Suzanne, Validating EmotiBit, an open-source multi-modal sensor for capturing research-grade physiological signals from anywhere on the body (October 5, 2022). Available at SSRN: https://ssrn.com/abstract=4700861 or http://dx.doi.org/10.2139/ssrn.4700861

Sean Montgomery (Contact Author)

University of Nevada, Reno - Department of Psychology ( email )

United States

Nitin Nair

Connected Future Labs ( email )

Reno, NV
United States

Hanzhi Chen

affiliation not provided to SSRN

Suzanne Dikker

New York University ( email )

New York
United States

HOME PAGE: http://www.suzannedikker.net

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