ArticleIEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society2018
A Noninvasive Brain-Computer Interface for Real-Time Speech Synthesis: The Importance of Multimodal Feedback.
Article in IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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.
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Who cites it
13 citing papers in PubMed.
- Brain-computer Interaction in the Smart Era.Current medical science · 2024Review
- Volitional inspiration is mediated by two independent output channels in the primary motor cortex.The Journal of comparative neurology · 2023Article
- Article
- Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier.Brain computer interfaces (Abingdon, England) · 2022Article
- Cutting-edge communication and learning assistive technologies for disabled children: An artificial intelligence perspective.Frontiers in artificial intelligence · 2022Review
- Brain-Computer Interfaces in Neurorecovery and Neurorehabilitation.Seminars in neurology · 2021Article
- What External Variables Affect Sensorimotor Rhythm Brain-Computer Interface (SMR-BCI) Performance?HCA healthcare journal of medicine · 2021Review
- Human visual skills for brain-computer interface use: a tutorial.Disability and rehabilitation. Assistive technology · 2020Review
- 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
- Motor-Induced Suppression of the N100 Event-Related Potential During Motor Imagery Control of a Speech Synthesizer Brain-Computer Interface.Journal of speech, language, and hearing research : JSLHR · 2019Article
- New and emerging access technologies for adults with complex communication needs and severe motor impairments: State of the science.Augmentative and alternative communication (Baltimore, Md. : 1985) · 2019Review
- Considering Augmentative and Alternative Communication Research for Brain-Computer Interface Practice.Assistive technology outcomes and benefits · 2019Article
- Guidelines for Feature Matching Assessment of Brain-Computer Interfaces for Augmentative and Alternative Communication.American journal of speech-language pathology · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
We conducted a study of a motor imagery brain-computer interface (BCI) using electroencephalography to continuously control a formant frequency speech synthesizer with instantaneous auditory and visual feedback. Over a three-session training period, sixteen participants learned to control the BCI for production of three vowel sounds (/ textipa i/ [heed], / textipa A/ [hot], and / textipa u/ [who'd]) and were split into three groups: those receiving unimodal auditory feedback of synthesized speech, those receiving unimodal visual feedback of formant frequencies, and those receiving multimodal, audio-visual (AV) feedback. Audio feedback was provided by a formant frequency artificial speech synthesizer, and visual feedback was given as a 2-D cursor on a graphical representation of the plane defined by the first two formant frequencies. We found that combined AV feedback led to the greatest performance in terms of percent accuracy, distance to target, and movement time to target compared with either unimodal feedback of auditory or visual information. These results indicate that performance is enhanced when multimodal feedback is meaningful for the BCI task goals, rather than as a generic biofeedback signal of BCI progress.
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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.