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A dataset of EEG and EOG from an auditory EOG-based communication system for patients in locked-in state

The dataset presented here contains recordings of electroencephalogram (EEG) and electrooculogram (EOG) from four advanced locked-in state (LIS) patients suffering from ALS (amyotrophic lateral sclerosis). These patients could no longer use commercial eye-trackers, but they could still move their ey...

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Autores principales: Jaramillo-Gonzalez, Andres, Wu, Shizhe, Tonin, Alessandro, Rana, Aygul, Ardali, Majid Khalili, Birbaumer, Niels, Chaudhary, Ujwal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801642/
https://www.ncbi.nlm.nih.gov/pubmed/33431874
http://dx.doi.org/10.1038/s41597-020-00789-4
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author Jaramillo-Gonzalez, Andres
Wu, Shizhe
Tonin, Alessandro
Rana, Aygul
Ardali, Majid Khalili
Birbaumer, Niels
Chaudhary, Ujwal
author_facet Jaramillo-Gonzalez, Andres
Wu, Shizhe
Tonin, Alessandro
Rana, Aygul
Ardali, Majid Khalili
Birbaumer, Niels
Chaudhary, Ujwal
author_sort Jaramillo-Gonzalez, Andres
collection PubMed
description The dataset presented here contains recordings of electroencephalogram (EEG) and electrooculogram (EOG) from four advanced locked-in state (LIS) patients suffering from ALS (amyotrophic lateral sclerosis). These patients could no longer use commercial eye-trackers, but they could still move their eyes and used the remnant oculomotor activity to select letters to form words and sentences using a novel auditory communication system. Data were recorded from four patients during a variable range of visits (from 2 to 10), each visit comprised of 3.22 ± 1.21 days and consisted of 5.57 ± 2.61 sessions recorded per day. The patients performed a succession of different sessions, namely, Training, Feedback, Copy spelling, and Free spelling. The dataset provides an insight into the progression of ALS and presents a valuable opportunity to design and improve assistive and alternative communication technologies and brain-computer interfaces. It might also help redefine the course of progression in ALS, thereby improving clinical judgement and treatment.
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spelling pubmed-78016422021-01-21 A dataset of EEG and EOG from an auditory EOG-based communication system for patients in locked-in state Jaramillo-Gonzalez, Andres Wu, Shizhe Tonin, Alessandro Rana, Aygul Ardali, Majid Khalili Birbaumer, Niels Chaudhary, Ujwal Sci Data Data Descriptor The dataset presented here contains recordings of electroencephalogram (EEG) and electrooculogram (EOG) from four advanced locked-in state (LIS) patients suffering from ALS (amyotrophic lateral sclerosis). These patients could no longer use commercial eye-trackers, but they could still move their eyes and used the remnant oculomotor activity to select letters to form words and sentences using a novel auditory communication system. Data were recorded from four patients during a variable range of visits (from 2 to 10), each visit comprised of 3.22 ± 1.21 days and consisted of 5.57 ± 2.61 sessions recorded per day. The patients performed a succession of different sessions, namely, Training, Feedback, Copy spelling, and Free spelling. The dataset provides an insight into the progression of ALS and presents a valuable opportunity to design and improve assistive and alternative communication technologies and brain-computer interfaces. It might also help redefine the course of progression in ALS, thereby improving clinical judgement and treatment. Nature Publishing Group UK 2021-01-11 /pmc/articles/PMC7801642/ /pubmed/33431874 http://dx.doi.org/10.1038/s41597-020-00789-4 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.
spellingShingle Data Descriptor
Jaramillo-Gonzalez, Andres
Wu, Shizhe
Tonin, Alessandro
Rana, Aygul
Ardali, Majid Khalili
Birbaumer, Niels
Chaudhary, Ujwal
A dataset of EEG and EOG from an auditory EOG-based communication system for patients in locked-in state
title A dataset of EEG and EOG from an auditory EOG-based communication system for patients in locked-in state
title_full A dataset of EEG and EOG from an auditory EOG-based communication system for patients in locked-in state
title_fullStr A dataset of EEG and EOG from an auditory EOG-based communication system for patients in locked-in state
title_full_unstemmed A dataset of EEG and EOG from an auditory EOG-based communication system for patients in locked-in state
title_short A dataset of EEG and EOG from an auditory EOG-based communication system for patients in locked-in state
title_sort dataset of eeg and eog from an auditory eog-based communication system for patients in locked-in state
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801642/
https://www.ncbi.nlm.nih.gov/pubmed/33431874
http://dx.doi.org/10.1038/s41597-020-00789-4
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