Currently submitted to: JMIR Rehabilitation and Assistive Technologies
Date Submitted: Oct 9, 2026
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Brain-computer interfaces: barriers and opportunities to widespread clinical adoption
ABSTRACT
Background:
Brain-computer interfaces (BCIs) could address unmet clinical needs in neurological disorders, particularly for communication and rehabilitation, yet their use remains largely confined to research settings. The views of the professionals who develop, deploy, and finance these devices on what hinders wider clinical adoption have received little attention.
Objective:
This study aimed to explore the barriers and opportunities for wider clinical adoption of BCIs as perceived by medical, engineering, and management professionals, and to draw health policy and management implications.
Methods:
We conducted a qualitative study using three online focus groups (n=22) with medical, engineering, and management professionals explored real-world experiences, perceptions, and expectations regarding BCI adoption. Six statements rated on a 5-point Likert scale served as discussion prompts. Transcripts were analyzed using a hybrid deductive-inductive thematic approach, informed by previous evidence of BCI clinical applications.
Results:
Participants agreed most strongly that BCIs can address unmet clinical needs and that current studies have important limitations. Answers on whether regulatory approval ensures reimbursement were mostly neutral, reflecting limited familiarity. Four themes emerged, interpreted alongside comparisons with other healthcare technologies: (1) research, with publication and funding incentives favoring novelty over translation; (2) healthcare ecosystem and adoption, including translational and commercial "valleys of death," the gap between approval and reimbursement, unclear target populations, clinician involvement in design, burdensome setup and unmet expectations (with eye trackers as competing communication tools), and unsettled quality-of-life measurement; (3) artificial intelligence and data, including ownership, liability, and cross-border rules; and (4) society, including media hype, repair-versus-enhancement tensions, and stigma.
Conclusions:
According to these professionals, barriers to wider clinical adoption of BCIs lie as much in the surrounding ecosystem as in the technology. Reimbursement evidence should be planned alongside regulatory work, policy should be application-specific, and clinicians should be involved early in design. For rehabilitation and assistive technology, trials should report sustained use, setup time, and caregiver burden, and compare BCIs with existing assistive tools. The data were collected in 2022 from a small sample with few physicians; future work should include patients, rehabilitation clinicians, payers, and regulators. Clinical Trial: brain-computer interfaces, brain-machine interfaces, neurotechnology, medical devices, innovation, quality-of-care
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Copyright
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