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

Author:

Jaramillo-Gonzalez AndresORCID,Wu Shizhe,Tonin Alessandro,Rana Aygul,Ardali Majid KhaliliORCID,Birbaumer Niels,Chaudhary UjwalORCID

Abstract

AbstractThe 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.

Funder

Bundesministerium für Bildung und Forschung

Deutsche Forschungsgemeinschaft

EC | Horizon 2020 Framework Programme

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability

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