MYND: Unsupervised Evaluation of Novel BCI Control Strategies on Consumer Hardware
This addresses the problem of limited ecological validity and scalability in BCI research for developers and users, though it is incremental as it builds on existing BCI methods with a new evaluation platform.
The paper tackles the challenge of evaluating brain-computer interface (BCI) control strategies in unsupervised, real-world settings by introducing MYND, a framework that enables subjects to self-administer multi-day studies at home using consumer-grade hardware, resulting in median signal quality of 90.2% and offline decoding accuracies of 68.5% and 64.0% for two strategies.
Neurophysiological studies are typically conducted in laboratories with limited ecological validity, scalability, and generalizability of findings. This is a significant challenge for the development of brain-computer interfaces (BCIs), which ultimately need to function in unsupervised settings on consumer-grade hardware. We introduce MYND: A framework that couples consumer-grade recording hardware with an easy-to-use application for the unsupervised evaluation of BCI control strategies. Subjects are guided through experiment selection, hardware fitting, recording, and data upload in order to self-administer multi-day studies that include neurophysiological recordings and questionnaires. As a use case, we evaluate two BCI control strategies ("Positive memories" and "Music imagery") in a realistic scenario by combining MYND with a four-channel electroencephalogram (EEG). Thirty subjects recorded 70.4 hours of EEG data with the system at home. The median headset fitting time was 25.9 seconds, and a median signal quality of 90.2% was retained during recordings.Neural activity in both control strategies could be decoded with an average offline accuracy of 68.5% and 64.0% across all days. The repeated unsupervised execution of the same strategy affected performance, which could be tackled by implementing feedback to let subjects switch between strategies or devise new strategies with the platform.