Skip navigation

The effect that auditory distractions have on a visual P300 speller while utilizing low-cost off-the-shelf equipment

The effect that auditory distractions have on a visual P300 speller while utilizing low-cost off-the-shelf equipment

Schembri, Patrick ORCID: 0000-0002-7808-5871 , Pelc, Maruisz and Ma, Jixin (2020) The effect that auditory distractions have on a visual P300 speller while utilizing low-cost off-the-shelf equipment. Computers, 9 (3):68. ISSN 2073-431X (Online) (doi:https://doi.org/10.3390/computers9030068)

[img]
Preview
PDF (Open Access Article)
29686 MA_Effect_That_Auditory_Distractions_Have_On_A_Visual_P300_Speller_(OA)_2020.pdf - Published Version
Available under License Creative Commons Attribution.

Download (2MB) | Preview

Abstract

This paper investigates the effect that selected auditory distractions have on the signal of a visual P300 Speller in terms of accuracy, amplitude, latency, user preference, signal morphology, and overall signal quality. In addition, it ensues the development of a hierarchical taxonomy aimed at categorizing distractions in the P300b domain and the effect thereof. This work is part of a larger electroencephalography based project and is based on the P300 speller brain–computer interface (oddball) paradigm and the xDAWN algorithm, with eight to ten healthy subjects, using a non-invasive brain–computer interface based on low-fidelity electroencephalographic (EEG) equipment. Our results suggest that the accuracy was best for the lab condition (LC) at 100%, followed by music at 90% (M90) at 98%, trailed by music at 30% (M30) and music at 60% (M60) equally at 96%, and shadowed by ambient noise (AN) at 92.5%, passive talking (PT) at 90%, and finally by active listening (AL) at 87.5%. The subjects’ preference prodigiously shows that the preferred condition was LC as originally expected, followed by M90, M60, AN, M30, AL, and PT. Statistical analysis between all independent variables shows that we accept our null hypothesis for both the amplitude and latency. This work includes data and comparisons from our previous papers. These additional results should give some insight into the practicability of the aforementioned P300 speller methodology and equipment to be used for real-world applications.

Item Type: Article
Uncontrolled Keywords: brain-computer interface (BCI), electroencephalography (EEG), event-related potential (ERP), P300 speller (P3), distractions, taxonomy
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Faculty of Liberal Arts & Sciences > Computational Science & Engineering Group (CSEH)
Last Modified: 23 May 2022 10:13
URI: http://gala.gre.ac.uk/id/eprint/29686

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics