NeuroCommTrainer: Toward an Adaptive and Wearable Multimodal Brain-Computer Interface

To date, brain-computer interfaces (BCIs) have not achieved reliable real-time communication through auditory or tactile modalities. Such interfaces would be crucial for brain-injured patients with severe motor impairments who are also blind or deaf. This study validates the functionality of the NeuroCommTrainer, a mobile and easy-to-use multimodal BCI with flex-printed electrode strips that does not require vision and adapts to users' attentiveness levels to initiate stimulation.

In a study of 20 healthy participants, we evaluated auditory and vibrotactile oddball paradigms to train the system to differentiate rare and frequent event-related potentials (ERPs). In real-time online sessions, the system detected participants' mental focus to adaptively initiate stimulation through attentiveness monitoring.

The NeuroCommTrainer successfully captured auditory and tactile ERPs, achieving a classification accuracy of 75% for stimuli in the calibration session, which is not yet reflected in the online session with 34% of found targets (chance level = 16.7%).

The presented early-stage prototype of the NeuroCommTrainer requires several improvements before clinical application in brain-damaged patients, which include refined algorithms to reduce classification variance across participants, and enhanced attentiveness detection specifically tuned to brain activity of the targeted patient group. The present study makes a critical step in this direction and shows that a transition into a practicable communication system for brain-damaged patients may be achievable in the future.