What is a Brain-Computer Interface (BCI)?

From the Guidelines

A brain-computer interface (BCI) is a technology that creates a direct communication pathway between the brain and an external device, allowing people to control computers or other machines using only their thoughts. BCIs work by detecting and interpreting brain signals, typically using sensors that measure electrical activity in the brain through methods like electroencephalography (EEG), electrocorticography (ECoG), or implanted electrodes. These systems translate brain signals into commands that can operate computers, prosthetic limbs, or other devices. BCIs have significant medical applications, particularly for people with paralysis, ALS, or other conditions that limit physical movement, enabling them to communicate and interact with their environment. The technology ranges from non-invasive systems that use external headsets to invasive approaches requiring surgical implantation of electrodes directly into brain tissue. While current BCIs are primarily used in research and specialized medical settings, ongoing advancements aim to make these systems more accurate, portable, and accessible for broader applications in healthcare, communication, and human-computer interaction.

Key Features of BCIs

• Detect and interpret brain signals using sensors like EEG, ECoG, or implanted electrodes
• Translate brain signals into commands to operate computers, prosthetic limbs, or other devices
• Have significant medical applications for people with paralysis, ALS, or other conditions that limit physical movement
• Range from non-invasive systems using external headsets to invasive approaches requiring surgical implantation of electrodes

Current State and Future Directions

The development of BCIs is an active area of research, with studies focusing on improving the accuracy, portability, and accessibility of these systems 1. As noted in a recent perspective on neural interfaces, the number of addressable neurological disorders is increasing steadily, and new healthcare opportunities powered by personalized neuroprosthetic medicine have the potential to greatly improve the quality of life in our aging society 1. However, to bridge progress in bioelectronic interfaces into long-term use in healthcare practice, it will be paramount to gather quantitative knowledge on the performance of soft bioelectronic interfaces in vivo and their mechanisms of interaction with the host biology.

Medical Applications and Quality of Life

BCIs have the potential to significantly improve the quality of life for people with paralysis, ALS, or other conditions that limit physical movement. By enabling them to communicate and interact with their environment, BCIs can help to reduce morbidity, mortality, and improve overall quality of life. As noted in a recent study on the design and implementation of virtual reality for acquired brain injury rehabilitation, the development of VR tasks for TBI rehabilitation should incorporate co-design design principles, which is lacking in the current literature 1. This highlights the need for further research and development in the field of BCIs and their applications in healthcare.

From the Research

Definition and Purpose of Brain-Computer Interfaces

• Brain-Computer Interfaces (BCIs) acquire brain signals, analyze them, and translate them into commands that are relayed to output devices to carry out desired actions 2.
• The main goal of BCI is to replace or restore useful function to people disabled by neuromuscular disorders such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury 2.
• BCIs aim to help paralyzed patients interact with their environment by controlling external devices using brain activity, thereby bypassing the dysfunctional motor system 3.

Types and Applications of Brain-Computer Interfaces

• BCIs can be invasive or non-invasive, using electroencephalography (EEG), intracortical, electrocorticographic, and other brain signals for control of cursors, robotic arms, prostheses, wheelchairs, and other devices 2.
• BCIs may also prove useful for rehabilitation after stroke and for other disorders, and might augment the performance of surgeons or other medical professionals in the future 2.
• Noninvasive BCIs using EEG or event-related brain potentials can transmit up to 80 bits/min of information, but their use in severely or totally paralyzed patients has met unforeseen difficulties 4.

Challenges and Future Developments

• The development of BCIs faces challenges such as the need for convenient, portable, and safe signal-acquisition hardware, and the need for long-term studies of real-world use by people with severe disabilities 2.
• Effective and viable models for the widespread dissemination of BCIs must be implemented, and the day-to-day and moment-to-moment reliability of BCI performance must be improved 2.
• Despite promising results, the effectiveness of BCIs in amyotrophic lateral sclerosis (ALS) patients has not been reliably established, and methodological issues among studies must be addressed 5.