ReviewFrontiers in cellular neuroscience2015
Current Challenges Facing the Translation of Brain Computer Interfaces from Preclinical Trials to Use in Human Patients.
Review in Frontiers in cellular neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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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.
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.
Who cites it
12 citing papers in PubMed.
- Towards neuromorphic neurotechnologies: integrating brain-inspired computing with brain-computer interfaces.npj biomedical innovations · 2026Review
- Full-Stack Architectures for Intelligent Brain-Computer Interfaces.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Decoding multi-class motor attempt from the affected unilateral limbs in chronic stroke patients.Journal of neuroengineering and rehabilitation · 2026Article
- Increasing Robustness of Brain-Computer Interfaces Through Automatic Detection and Removal of Corrupted Input Signals.Frontiers in neuroscience · 2022Article
- A cortical injury model in a non-human primate to assess execution of reach and grasp actions: implications for recovery after traumatic brain injury.Journal of neuroscience methods · 2021Article
- Evaluation of a P300-Based Brain-Machine Interface for a Robotic Hand-Orthosis Control.Frontiers in neuroscience · 2020Article
- Decoding Movement From Electrocorticographic Activity: A Review.Frontiers in neuroinformatics · 2019Review
- Real-time decoding of covert attention in higher-order visual areas.NeuroImage · 2018Article
- Keeping Disability in Mind: A Case Study in Implantable Brain-Computer Interface Research.Science and engineering ethics · 2018Article
- Artificial neural network EMG classifier for functional hand grasp movements prediction.The Journal of international medical research · 2017Article
- Workshops of the Sixth International Brain-Computer Interface Meeting: brain-computer interfaces past, present, and future.Brain computer interfaces (Abingdon, England) · 2017Article
- The Evolution of Neuroprosthetic Interfaces.Critical reviews in biomedical engineering · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Current research in brain computer interface (BCI) technology is advancing beyond preclinical studies, with trials beginning in human patients. To date, these trials have been carried out with several different types of recording interfaces. The success of these devices has varied widely, but different factors such as the level of invasiveness, timescale of recorded information, and ability to maintain stable functionality of the device over a long period of time all must be considered in addition to accuracy in decoding intent when assessing the most practical type of device moving forward. Here, we discuss various approaches to BCIs, distinguishing between devices focusing on control of operations extrinsic to the subject (e.g., prosthetic limbs, computer cursors) and those focusing on control of operations intrinsic to the brain (e.g., using stimulation or external feedback), including closed-loop or adaptive devices. In this discussion, we consider the current challenges facing the translation of various types of BCI technology to eventual human application.
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What OpenQuestion holds
Registered trials
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.