EEG Waveform Analysis of P300 ERP with Applications to Brain Computer Interfaces
The Electroencephalography (EEG) is not just a mere clinical tool anymore. It has become the de-facto mobile, portable, non-invasive brain imaging sensor to harness brain information in real time. It is now being used to translate or decode brain signals, to diagnose diseases or to implement Brain C...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-11-01
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| Series: | Brain Sciences |
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| Online Access: | https://www.mdpi.com/2076-3425/8/11/199 |
| _version_ | 1818896589630996480 |
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| author | Rodrigo Ramele Ana Julia Villar Juan Miguel Santos |
| author_facet | Rodrigo Ramele Ana Julia Villar Juan Miguel Santos |
| author_sort | Rodrigo Ramele |
| collection | DOAJ |
| description | The Electroencephalography (EEG) is not just a mere clinical tool anymore. It has become the de-facto mobile, portable, non-invasive brain imaging sensor to harness brain information in real time. It is now being used to translate or decode brain signals, to diagnose diseases or to implement Brain Computer Interface (BCI) devices. The automatic decoding is mainly implemented by using quantitative algorithms to detect the cloaked information buried in the signal. However, clinical EEG is based intensively on waveforms and the structure of signal plots. Hence, the purpose of this work is to establish a bridge to fill this gap by reviewing and describing the procedures that have been used to detect patterns in the electroencephalographic waveforms, benchmarking them on a controlled pseudo-real dataset of a P300-Based BCI Speller and verifying their performance on a public dataset of a BCI Competition. |
| first_indexed | 2024-12-19T19:02:41Z |
| format | Article |
| id | doaj.art-57807924b69e4ffca6332ab6008e288e |
| institution | Directory Open Access Journal |
| issn | 2076-3425 |
| language | English |
| last_indexed | 2024-12-19T19:02:41Z |
| publishDate | 2018-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Brain Sciences |
| spelling | doaj.art-57807924b69e4ffca6332ab6008e288e2022-12-21T20:09:31ZengMDPI AGBrain Sciences2076-34252018-11-0181119910.3390/brainsci8110199brainsci8110199EEG Waveform Analysis of P300 ERP with Applications to Brain Computer InterfacesRodrigo Ramele0Ana Julia Villar1Juan Miguel Santos2Computer Engineering Department, Instituto Tecnológico de Buenos Aires (ITBA), Buenos Aires 1441, ArgentinaComputer Engineering Department, Instituto Tecnológico de Buenos Aires (ITBA), Buenos Aires 1441, ArgentinaComputer Engineering Department, Instituto Tecnológico de Buenos Aires (ITBA), Buenos Aires 1441, ArgentinaThe Electroencephalography (EEG) is not just a mere clinical tool anymore. It has become the de-facto mobile, portable, non-invasive brain imaging sensor to harness brain information in real time. It is now being used to translate or decode brain signals, to diagnose diseases or to implement Brain Computer Interface (BCI) devices. The automatic decoding is mainly implemented by using quantitative algorithms to detect the cloaked information buried in the signal. However, clinical EEG is based intensively on waveforms and the structure of signal plots. Hence, the purpose of this work is to establish a bridge to fill this gap by reviewing and describing the procedures that have been used to detect patterns in the electroencephalographic waveforms, benchmarking them on a controlled pseudo-real dataset of a P300-Based BCI Speller and verifying their performance on a public dataset of a BCI Competition.https://www.mdpi.com/2076-3425/8/11/199electroencephalographybrain-computer interfaceswaveformp300SIFTPEMPSHCC |
| spellingShingle | Rodrigo Ramele Ana Julia Villar Juan Miguel Santos EEG Waveform Analysis of P300 ERP with Applications to Brain Computer Interfaces Brain Sciences electroencephalography brain-computer interfaces waveform p300 SIFT PE MP SHCC |
| title | EEG Waveform Analysis of P300 ERP with Applications to Brain Computer Interfaces |
| title_full | EEG Waveform Analysis of P300 ERP with Applications to Brain Computer Interfaces |
| title_fullStr | EEG Waveform Analysis of P300 ERP with Applications to Brain Computer Interfaces |
| title_full_unstemmed | EEG Waveform Analysis of P300 ERP with Applications to Brain Computer Interfaces |
| title_short | EEG Waveform Analysis of P300 ERP with Applications to Brain Computer Interfaces |
| title_sort | eeg waveform analysis of p300 erp with applications to brain computer interfaces |
| topic | electroencephalography brain-computer interfaces waveform p300 SIFT PE MP SHCC |
| url | https://www.mdpi.com/2076-3425/8/11/199 |
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