Mohit Agarwal
Georgia Institute of Technology, Atlanta, GA, USA
Commercially available EEG-based Brain-Computer Interface (BCI) wearable headsets are always-on and are thus power hungry, requiring users to charge the headsets multiple times a day. In this paper, we tackle the problem of wake-up command design and detection for BCI headsets, and explore how battery life can be made to last for approximately a whole day. The key challenge that we address is enabling the headset to operate in a near-sleep mode but still reliably detect and interpret an EEG-based wake-up command from the user. Towards addressing the challenge, we present a solution that is built upon eye-blinks. Our core contribution is Trance, a user-friendly and robust wake-up command for BCI headsets that is computationally lightweight. We show using experimental results coupled with multiple data sets collected through user-studies that Trance can extend battery life by approximately 2.7x or to approximately 10 hours for a typical wearable battery, while remaining user-friendly.
https://doi.org/10.1145/3313831.3376738
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)