The Effect That Auditory Distractions Have on a Visual P300 Speller While Utilizing Low-Cost Off-the-Shelf Equipment

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 cate...

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出版年:Computers
主要な著者: Patrick Schembri, Maruisz Pelc, Jixin Ma
フォーマット: 論文
言語:英語
出版事項: MDPI AG 2020-08-01
主題:
オンライン・アクセス:https://www.mdpi.com/2073-431X/9/3/68
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author Patrick Schembri
Maruisz Pelc
Jixin Ma
author_facet Patrick Schembri
Maruisz Pelc
Jixin Ma
author_sort Patrick Schembri
collection DOAJ
container_title Computers
description 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 (<i>LC</i>) at 100%, followed by music at 90% (<i>M90</i>) at 98%, trailed by music at 30% (<i>M30</i>) and music at 60% (<i>M60</i>) equally at 96%, and shadowed by ambient noise (<i>AN</i>) at 92.5%, passive talking (<i>PT</i>) at 90%, and finally by active listening (<i>AL</i>) at 87.5%. The subjects’ preference prodigiously shows that the preferred condition was <i>LC</i> as originally expected, followed by <i>M90</i>, <i>M60</i>, <i>AN</i>, <i>M30</i>, <i>AL</i>, and <i>PT</i>. 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.
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spelling doaj-art-3f7e8e8cb56348bbb08c8d3f37013e2d2025-08-20T01:11:13ZengMDPI AGComputers2073-431X2020-08-01936810.3390/computers9030068The Effect That Auditory Distractions Have on a Visual P300 Speller While Utilizing Low-Cost Off-the-Shelf EquipmentPatrick Schembri0Maruisz Pelc1Jixin Ma2Department of Computing and Mathematical Sciences, University of Greenwich, London SE10 9LS, UKDepartment of Computing and Mathematical Sciences, University of Greenwich, London SE10 9LS, UKDepartment of Computing and Mathematical Sciences, University of Greenwich, London SE10 9LS, UKThis 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 (<i>LC</i>) at 100%, followed by music at 90% (<i>M90</i>) at 98%, trailed by music at 30% (<i>M30</i>) and music at 60% (<i>M60</i>) equally at 96%, and shadowed by ambient noise (<i>AN</i>) at 92.5%, passive talking (<i>PT</i>) at 90%, and finally by active listening (<i>AL</i>) at 87.5%. The subjects’ preference prodigiously shows that the preferred condition was <i>LC</i> as originally expected, followed by <i>M90</i>, <i>M60</i>, <i>AN</i>, <i>M30</i>, <i>AL</i>, and <i>PT</i>. 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.https://www.mdpi.com/2073-431X/9/3/68brain-computer interface (BCI)electroencephalography (EEG)event-related potential (ERP)P300 speller (P3)distractionstaxonomy
spellingShingle Patrick Schembri
Maruisz Pelc
Jixin Ma
The Effect That Auditory Distractions Have on a Visual P300 Speller While Utilizing Low-Cost Off-the-Shelf Equipment
brain-computer interface (BCI)
electroencephalography (EEG)
event-related potential (ERP)
P300 speller (P3)
distractions
taxonomy
title The Effect That Auditory Distractions Have on a Visual P300 Speller While Utilizing Low-Cost Off-the-Shelf Equipment
title_full The Effect That Auditory Distractions Have on a Visual P300 Speller While Utilizing Low-Cost Off-the-Shelf Equipment
title_fullStr The Effect That Auditory Distractions Have on a Visual P300 Speller While Utilizing Low-Cost Off-the-Shelf Equipment
title_full_unstemmed The Effect That Auditory Distractions Have on a Visual P300 Speller While Utilizing Low-Cost Off-the-Shelf Equipment
title_short The Effect That Auditory Distractions Have on a Visual P300 Speller While Utilizing Low-Cost Off-the-Shelf Equipment
title_sort effect that auditory distractions have on a visual p300 speller while utilizing low cost off the shelf equipment
topic brain-computer interface (BCI)
electroencephalography (EEG)
event-related potential (ERP)
P300 speller (P3)
distractions
taxonomy
url https://www.mdpi.com/2073-431X/9/3/68
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