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

Andres Jaramillo-Gonzalez, Shizhe Wu, Alessandro Tonin, Aygul Rana, Majid Khalili Ardali, Niels Birbaumer, Ujwal Chaudhary

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number8
JournalScientific data
Volume8
Issue number1
DOIs
Publication statusPublished - Dec 2021

ASJC Scopus subject areas

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

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