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An EEG & eye-tracking dataset of ALS patients & healthy people during eye-tracking-based spelling system usage

مجموعة بيانات تخطيط كهربية الدماغ وتتبع العين لمرضى التصلب الجانبي الضموري والأشخاص الأصحاء أثناء استخدام نظام الإملاء القائم على تتبع العين
Authors: Thi Duyen Ngo; Hai-Dang Kieu; Minh Hoa Nguyen; The Hoang-Anh Nguyen; Văn Mão Cấn; Nguyen Ba Hung; Le Thanh Ha;

An EEG & eye-tracking dataset of ALS patients & healthy people during eye-tracking-based spelling system usage

Abstract

AbstractThis research presents a dataset consisting of electroencephalogram and eye tracking recordings obtained from six patients with amyotrophic lateral sclerosis (ALS) in a locked-in state and one hundred seventy healthy individuals. The ALS patients exhibited varying degrees of disease progression, ranging from partial mobility and weakened speech to complete paralysis and loss of speech. Despite these physical impairments, the ALS patients retained good eye function, which allowed them to use a virtual keyboard for communication. Data from ALS patients was recorded multiple times at their homes, while data from healthy individuals was recorded once in a laboratory setting. For each data recording, the experimental design involved nine recording sessions per participant, each corresponding to a common human action or demand. This dataset can serve as a valuable benchmark for several applications, such as improving spelling systems with brain-computer interfaces, investigating motor imagination, exploring motor cortex function, monitoring motor impairment progress in patients undergoing rehabilitation, and studying the effects of ALS on cognitive and motor processes.

Keywords

Data Descriptor, Artificial intelligence, Science, Cognitive Neuroscience, Spelling, Epilepsy Detection, EEG Analysis, Tracking (education), Health Sciences, Humans, Eye Tracking in Human-Computer Interaction, Psychology, Deep Learning for EEG, Eye-Tracking Technology, Eye tracking, Pedagogy, Q, Amyotrophic Lateral Sclerosis, Eye Tracking, Eye Movement Analysis, Life Sciences, Electroencephalography, Linguistics, Brain-Computer Interfaces in Neuroscience and Medicine, Diagnosis and Management of Alzheimer's Disease, Computer science, FOS: Philosophy, ethics and religion, Human-Computer Interaction, FOS: Psychology, Psychiatry and Mental health, Philosophy, Brain-Computer Interfaces, Computer Science, Physical Sciences, FOS: Languages and literature, Medicine, Computer vision, Neuroscience

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Average
Top 10%
Green
hybrid