ReviewAmerican journal of speech-language pathology2018
Guidelines for Feature Matching Assessment of Brain-Computer Interfaces for Augmentative and Alternative Communication.
Review in American journal of speech-language pathology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled 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.
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, 1 synthesis or guideline pooled it.
- A systematic review of research on augmentative and alternative communication brain-computer interface systems for individuals with disabilities.Frontiers in human neuroscience · 2022Pooled it
- Considering whether brain-computer interfaces have prospective potential to support children who have the physical abilities for touch-based AAC access: a forum manuscript.Augmentative and alternative communication (Baltimore, Md. : 1985) · 2026Article
- Supporting effective alternative access for individuals with physical disabilities: state of the science, emerging technologies, and future research directions.Augmentative and alternative communication (Baltimore, Md. : 1985) · 2025Review
- A flexible intracortical brain-computer interface for typing using finger movements.bioRxiv : the preprint server for biology · 2024Article
- Evaluating the perspectives of those with severe physical impairments while learning BCI control of a commercial augmentative and alternative communication paradigm.Assistive technology : the official journal of RESNA · 2023Article
- Evaluating person-centered factors associated with brain-computer interface access to a commercial augmentative and alternative communication paradigm.Assistive technology : the official journal of RESNA · 2022Article
- EEG hybrid brain-computer interfaces: A scoping review applying an existing hybrid-BCI taxonomy and considerations for pediatric applications.Frontiers in human neuroscience · 2022Article
- Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier.Brain computer interfaces (Abingdon, England) · 2022Article
- Analysis of Prognostic Risk Factors Determining Poor Functional Recovery After Comprehensive Rehabilitation Including Motor-Imagery Brain-Computer Interface Training in Stroke Patients: A Prospective Study.Frontiers in neurology · 2021Article
- Behind the Scenes of Noninvasive Brain-Computer Interfaces: A Review of Electroencephalography Signals, How They Are Recorded, and Why They Matter.Perspectives of the ASHA special interest groups · 2019Article
- Examining sensory ability, feature matching and assessment-based adaptation for a brain-computer interface using the steady-state visually evoked potential.Disability and rehabilitation. Assistive technology · 2019Article
- Considering Augmentative and Alternative Communication Research for Brain-Computer Interface Practice.Assistive technology outcomes and benefits · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Purpose: Brain-computer interfaces (BCIs) can provide access to augmentative and alternative communication (AAC) devices using neurological activity alone without voluntary movements. As with traditional AAC access methods, BCI performance may be influenced by the cognitive-sensory-motor and motor imagery profiles of those who use these devices. Therefore, we propose a person-centered, feature matching framework consistent with clinical AAC best practices to ensure selection of the most appropriate BCI technology to meet individuals' communication needs. Method: The proposed feature matching procedure is based on the current state of the art in BCI technology and published reports on cognitive, sensory, motor, and motor imagery factors important for successful operation of BCI devices. Results: Considerations for successful selection of BCI for accessing AAC are summarized based on interpretation from a multidisciplinary team with experience in AAC, BCI, neuromotor disorders, and cognitive assessment. The set of features that support each BCI option are discussed in a hypothetical case format to model possible transition of BCI research from the laboratory into clinical AAC applications. Conclusions: This procedure is an initial step toward consideration of feature matching assessment for the full range of BCI devices. Future investigations are needed to fully examine how person-centered factors influence BCI performance across devices.
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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.