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...
| 出版年: | Computers |
|---|---|
| 主要な著者: | , , |
| フォーマット: | 論文 |
| 言語: | 英語 |
| 出版事項: |
MDPI AG
2020-08-01
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| 主題: | |
| オンライン・アクセス: | https://www.mdpi.com/2073-431X/9/3/68 |
| _version_ | 1849877437010149376 |
|---|---|
| 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. |
| format | Article |
| id | doaj-art-3f7e8e8cb56348bbb08c8d3f37013e2d |
| institution | Directory of Open Access Journals |
| issn | 2073-431X |
| language | English |
| publishDate | 2020-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| 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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