Evidence map›Paper›PMID 40697162›Full record

SynthesisAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Toward the Clinical Translation of Implantable Brain-Computer Interfaces for Motor Impairment: Research Trends and Outcome Measures.

Esmee Dohle, Eleanor Swanson, Luka Jovanovic, Suraya Yusuf, Lucy Thompson, Hugo Layard Horsfall, William Muirhead, Luke Bashford, Jamie Brannigan

Abstract readSystematic Review
In one paragraph

Synthesis in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Full-Stack Architectures for Intelligent Brain-Computer Interfaces.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  3. Article
  4. Review of Recent Advances in Implantable Brain-Computer Interfaces for the Restoration of Motor Function in Patients With Paralysis.Medical science monitor : international medical journal of experimental and clinical research · 2026
    Review
  5. Article
  6. Designing Neural Dynamics: From Digital Twin Modeling to Regeneration.International journal of molecular sciences · 2025
    Review
  7. Review
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Esmee DohleOxford University Hospitals, John Radcliffe Hospital, Oxford, OX3 9DU, UK.
Eleanor SwansonUtrecht University Medical Centre, Utrecht, 3584 CX, Netherlands.
Luka JovanovicEast and North Hertfordshire NHS Trust, Lister Hospital, Stevenage, SG1 4AB, UK.
Suraya YusufOxford University Hospitals, John Radcliffe Hospital, Oxford, OX3 9DU, UK.
Lucy ThompsonFaculty of Medicine, Imperial College London, London, SW7 5NH, UK.
Hugo Layard HorsfallDepartment of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, WC1N 3BG, UK.
William MuirheadDepartment of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, WC1N 3BG, UK.
Luke BashfordBioscience Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK.ORCID https://orcid.org/0000-0003-4391-2491
Jamie BranniganOxford University Hospitals, John Radcliffe Hospital, Oxford, OX3 9DU, UK.ORCID https://orcid.org/0000-0003-1697-403X

Funding

Rosetrees Trust and Stoneygate TrustWellcome Trust FC001153
6 · The paper itself

Abstract

Implantable brain-computer interfaces (iBCIs) decode neural signals to control external effectors, offering potential to restore function in individuals with severe motor impairments, such as loss of limb function or speech. This systematic review examines the evolution of iBCI research and key bottlenecks to clinical translation, particularly the absence of standardized, clinically meaningful outcome measures. A comprehensive search of MEDLINE, Embase, and CINAHL identifies 112 studies, nearly half (49.1%) published since 2020. Eighty unique iBCI participants were identified, providing the most up-to-date estimate of global users. Research remains concentrated in the United States (83%), with growing contributions from Europe, China, and Australia. Electrocorticography (ECoG)-based devices increasingly emerge alongside micro-electrode arrays. iBCI devices are now being used to control a broader range of effectors, including robotic prosthetics and digital technologies. Although most (69.6%) studies reported outcome measures prospectively, these primarily related to decoding (69.6%) and task performance (62.5%), with only 17.9% assessing clinical outcomes. When cassessed, clinical outcomes were highly heterogeneous due to varied approaches across target populations. iBCIs show potential to restore functional independence at scale. However, challenges remain around cross-subject generalization, scalable implantation, and outcome standardization. Novel measures should be developed collaboratively with engineers, clinicians, and individuals with lived experience of motor impairment.

Indexed as

Brain-Computer InterfacesTranslational Research, BiomedicalElectrocorticographyHumansOutcome Assessment, Health CareBCIsbrain–computer interfaces (BCIs)outcome measurestrends

Identifiers

PMID40697162
PMCPMC12407270

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.