# Individualized brain-computer interface for people with disabilities: a review

## TL;DR

This paper reviews brain-computer interfaces for people with disabilities, focusing on how individual needs influence design and ethical considerations.

## Contribution

The paper provides a user-needs-informed discussion of BCI-based assistive technologies, emphasizing adaptable designs for diverse users.

## Key findings

- BCI-based ARTs offer mobility, cognition, and communication benefits for people with disabilities.
- Adaptable designs are essential to meet individual user needs but may hinder scalability.
- Non-implantable BCIs are more accessible and transferable due to standardized signal acquisition.

## Abstract

Brain-computer interfaces (BCIs) facilitate functional interaction between the brain and external devices, enabling users to bypass their typical peripheral motor actions to control assistive and rehabilitative technologies (ARTs). This review critically evaluates the state-of-the-art BCI-based ARTs by integrating the psychosocial and health-related factors impacting user needs, highlighting the influence of brain changes during development and aging on the design and ethical use of BCI technologies. As direct human-computer interfaces, BCI-based ARTs offer extended degrees of freedom via augmented mobility, cognition and communication, especially to people with disabilities. However, the innovation in BCI-based ARTs is guided by the complexity of disability types and levels of function across users that define individual needs. Therefore, an adaptable design is essential for tailoring a BCI-based ART that can fulfill user-specific requirements, which may hinder the scalability of BCIs for their widespread adoption across users with disabilities. The trade-offs between implantable and non-implantable BCIs are explored along with complex decisions around informed consent for people with communication or cognitive disabilities and pediatric settings. Non-implantable BCIs offer broader accessibility and transferability across users due to wider standardized signal acquisition and algorithm generalization, making them suited for a more comprehensive user group. This review contributes to the field by providing individualized user needs-informed discussion of BCI-based ARTs, emphasizing the need for adaptable designs that align the evolving functional and developmental needs of users with disabilities.