Abstract

Severe motor impairments can affect the ability to communicate. The ability to see has a decisive influence on the augmentative and alternative communication (AAC) systems available to the user. To better understand the initial impressions users have of AAC systems we asked naïve healthy participants to compare two visual (a visual P300 brain-computer interface (BCI) and an eye-tracker) and two non-visual systems (an auditory and a tactile P300 BCI). Eleven healthy participants performed 20 selections in a five choice task with each system. The visual P300 BCI used face stimuli, the auditory P300 BCI used Japanese Hiragana syllables and the tactile P300 BCI used a stimulator on the small left finger, middle left finger, right thumb, middle right finger and small right finger. The eye-tracker required a dwell time of 3 s on the target for selection. We calculated accuracies and information-transfer rates (ITRs) for each control method using the selection time that yielded the highest ITR and an accuracy above 70% for each system. Accuracies of 88% were achieved with the visual P300 BCI (4.8 s selection time, 20.9 bits/min), of 70% with the auditory BCI (19.9 s, 3.3 bits/min), of 71% with the tactile BCI (18 s, 3.4 bits/min) and of 100% with the eye-tracker (5.1 s, 28.2 bits/min). Performance between eye-tracker and visual BCI correlated strongly, correlation between tactile and auditory BCI performance was lower. Our data showed no advantage for either non-visual system in terms of ITR but a lower correlation of performance which suggests that choosing the system which suits a particular user is of higher importance for non-visual systems than visual systems.

Highlights

  • Injuries or neurodegenerative diseases may lead to an interruption of the output of the central nervous system to the muscles

  • Visual alternative communication (AAC) (Visual P300 brain-computer interface (BCI) and Eye-Tracker) Online accuracy for the visual P300 BCI was 96% and for the eye-tracker 100%

  • A surprising result was that after determining the selection time that yields the highest information-transfer rates (ITRs) and an accuracy above 70% for the visual P300 BCI we found that the time needed for an average selection with the eye-tracker was only 6% higher (4.8 s with the BCI compared to 5.1 s with the eye-tracker)

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Summary

Introduction

Injuries or neurodegenerative diseases may lead to an interruption of the output of the central nervous system to the muscles Diseases such as amyotrophic lateral sclerosis (ALS) or injuries caused e.g., by brain-stem stroke may lead to the locked-in state (LIS), in which the affected person is conscious but will no longer be able to communicate without assistance (Plum and Posner, 1972; Storm et al, 2017; Juel et al, 2018). To provide access to BCI technology for persons who lost vision, systems that are independent of muscle control and vision are needed. Such a system can be implemented by using event-related potentials (ERPs) elicited with non-visual stimulation to control a BCI (Furdea et al, 2009; Brouwer and van Erp, 2010)

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