Introducing EmotiBit, an open-source multi-modal sensor for measuring research-grade physiological signals

Sitting at the nexus of brain and behavior, peripheral physiological signals provide a powerful window toward understanding the body and mind. However, the currently available peripheral physiology sensing devices have a number of roadblocks for utilizing their data. Consumer-grade devices like the FitBit and Apple Watch are easy to wear on the wrist but provide very limited access to consumer-grade data derived by black-box signal processing algorithms, which can make it difficult to interpret the data in research contexts. On the other hand, research-grade devices (e.g. Empatica, Shimmer, BIOPAC) provide greater access to high-quality data but remain in closed ecosystems at high price points that are out of reach for many. To bridge these gaps in available biometrics solutions, our labs launched an open-source physiological sensing platform called EmotiBit (http://www.emotibit.com/). EmotiBit can wirelessly stream and locally record data from a multi-modal constellation of sensors, including electrodermal activity (EDA), multi-wavelength PPG, a medical-grade temperature sensor, 9-axis IMU, and a growing list of derivative metrics. The software is open-source, the data is 100% owned by the user, and the hardware design is compatible with the Adafruit Feather (Arduino) open-source ecosystem to easily sense physiological signals from nearly anywhere on the body.