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

• Published in: Scientific data 2024-06, Vol.11 (1), p.664-11, Article 664
• Main Authors: Ngo, Thi Duyen, Kieu, Hai Dang, Nguyen, Minh Hoa, Nguyen, The Hoang-Anh, Can, Van Mao, Nguyen, Ba Hung, Le, Thanh Ha
• Format: Article
• Language: English
• Subjects: 692/617; 692/700; Amyotrophic lateral sclerosis; Amyotrophic Lateral Sclerosis - physiopathology; Brain-Computer Interfaces; Cortex (motor); Data Descriptor; Datasets; EEG; Electroencephalography; Eye-Tracking Technology; Humanities and Social Sciences; Humans; Mental task performance; multidisciplinary; Paralysis; Science; Science (multidisciplinary); Speech
• ISSN: 2052-4463; 2052-4463
• DOI: 10.1038/s41597-024-03501-y

This 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.