Challenges and applications of wearable brain-computer interface technologies

Brain-computer interfaces (BCIs) bridge the gap between the mind and its surroundings to allow humans to communicate directly with computers, enabling not only clinical monitoring of the brain’s activity but also touch-free operation of electronic devices. The most promising of these for widespread adoption are electroencephalography (EEG)-based BCIs (eBCIs), which monitor the brain’s electrical activity, noninvasive and easy to use.

To address the rapid integration of these technologies into everyday life, Portillo-Lara et al. conducted a review of state-of-the-art eBCIs and other wearable EEGs, providing commentary on key challenges and concerns.

“Despite being in the early stages of development, BCIs for motor rehabilitation and restoration are already making a significant impact on the quality of life of patients affected by a variety of conditions,” said author Rylie Green. “Currently, eBCIs are routinely used to actively control external devices such as robotic limbs, drones, autonomous navigation robots or wheelchairs.”

Beyond patient use, a multitude of practical and recreational activities can benefit from advancements to BCIs. This potentially includes monitoring a user’s brain activity to ensure their well-being and safety, and optimizing videogaming experiences to an individual player.

Prior to more widespread application, several technical limitations remain to be addressed. Currently, the necessary hardware is heavy and expensive to manufacture, and the software needs to be adapted to commercial mobile devices.

“The most exciting and transcendental applications of this technology could lie beyond what can be foreseen by the scientific community today,” said author Roberto Portillo-Lara. “BCIs could one day evolve into enabling platforms that foster the emergence of multiple transformative applications that we cannot conceive with our current knowledge and perspective.”

Source: “Mind the gap: State-of-the-art technologies and applications for EEG-based brain-computer interfaces,” by Roberto Portillo-Lara, Bogachan Tahirbegi, Christopher AR Chapman, Josef A. Goding, and Rylie A. Green, APL Bioengineering (2021). The article can be accessed at https://doi.org/10.1063/5.0047237 .