Brain-computer interface for the communication of acute patients: a feasibility study and a randomized controlled trial comparing performance with healthy participants and a traditional assistive device-Reference-Cited by-同舟云学术

Brain-computer interface for the communication of acute patients: a feasibility study and a randomized controlled trial comparing performance with healthy participants and a traditional assistive device

Published:2016-10 Issue:4 Volume:3 Page:197-215
ISSN:2326-263X
Container-title:Brain-Computer Interfaces
language:en
Short-container-title:Brain-Computer Interfaces

Author:

Mayaud Louis¹²³⁴,Cabanilles Salvador³,Van Langhenhove Aurélien¹²³,Congedo Marco⁵,Barachant Alexandre⁵,Pouplin Samuel¹²³,Filipe Sabine⁶,Pétégnief Lucie⁷,Rochecouste Olivier⁸,Azabou Eric²³,Hugeron Caroline³,Lejaille Michèle¹,Orlikowski David¹²³,Annane Djillali¹²³

Affiliation:

1. INSERM, Centre d’Investigation Clinique et d’Innovation technologique (CIC-IT), UMR805, Garches, France

2. INSERM, Equipes Thérapeutiques innovantes et Technologies appliquées aux troubles neuromoteurs, U. 1179, Garches, France

3. Hôpital Raymond Poincaré, APHP, Garches, France

4. Mensia Technologies SA, Paris, France

5. GIPSA-Lab, CNRS, University of Grenoble-Alpes, Grenoble Institute of Technology, Grenoble, France

6. Department DTBS, CEA/LETI, Grenoble, France

7. DIXI Microtechniques Medical, Besançon, France

8. Davidson Consulting, Rennes, France

Funder

Agence Nationale de la Recherche

AFM-Téléthon (FR)

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Behavioral Neuroscience,Human-Computer Interaction,Biomedical Engineering

Link

https://tandfonline.com/doi/pdf/10.1080/2326263X.2016.1254403

Reference61 articles.

1. Communication in the ICU

2. Assistive technology for cognitive rehabilitation: State of the art

3. Evaluation of an adaptive row/column scanning system

4. Adaptive one-switch row-column scanning

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Transfer Learning for P300 Brain-Computer Interfaces by Joint Alignment of Feature Vectors;IEEE Journal of Biomedical and Health Informatics;2023-10

2. Frequency Domain Filtering Method for SSVEP-EEG Preprocessing;IEEE Transactions on Neural Systems and Rehabilitation Engineering;2023

3. Tangent space alignment: Transfer learning for Brain-Computer Interface;Frontiers in Human Neuroscience;2022-12-02

4. The perspectives of augmentative and alternative communication experts on the clinical integration of non-invasive brain-computer interfaces;Brain-Computer Interfaces;2022-04-11

5. A few filters are enough: Convolutional neural network for P300 detection;Neurocomputing;2021-02