A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI
Steady state visual evoked potentials (SSVEPs)-based Brain-Computer interfaces (BCIs), as well as eyetracking devices, provide a pathway for re-establishing communication for people with severe disabilities. We fused these control techniques into a novel eyetracking/SSVEP hybrid system, which utiliz...
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MDPI AG
2017-04-01
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Series: | Brain Sciences |
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Online Access: | http://www.mdpi.com/2076-3425/7/4/35 |
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author | Piotr Stawicki Felix Gembler Aya Rezeika Ivan Volosyak |
author_facet | Piotr Stawicki Felix Gembler Aya Rezeika Ivan Volosyak |
author_sort | Piotr Stawicki |
collection | DOAJ |
description | Steady state visual evoked potentials (SSVEPs)-based Brain-Computer interfaces (BCIs), as well as eyetracking devices, provide a pathway for re-establishing communication for people with severe disabilities. We fused these control techniques into a novel eyetracking/SSVEP hybrid system, which utilizes eye tracking for initial rough selection and the SSVEP technology for fine target activation. Based on our previous studies, only four stimuli were used for the SSVEP aspect, granting sufficient control for most BCI users. As Eye tracking data is not used for activation of letters, false positives due to inappropriate dwell times are avoided. This novel approach combines the high speed of eye tracking systems and the high classification accuracies of low target SSVEP-based BCIs, leading to an optimal combination of both methods. We evaluated accuracy and speed of the proposed hybrid system with a 30-target spelling application implementing all three control approaches (pure eye tracking, SSVEP and the hybrid system) with 32 participants. Although the highest information transfer rates (ITRs) were achieved with pure eye tracking, a considerable amount of subjects was not able to gain sufficient control over the stand-alone eye-tracking device or the pure SSVEP system (78.13% and 75% of the participants reached reliable control, respectively). In this respect, the proposed hybrid was most universal (over 90% of users achieved reliable control), and outperformed the pure SSVEP system in terms of speed and user friendliness. The presented hybrid system might offer communication to a wider range of users in comparison to the standard techniques. |
first_indexed | 2024-12-23T20:46:24Z |
format | Article |
id | doaj.art-32f552677ef04fe096d034cc3c15fe4a |
institution | Directory Open Access Journal |
issn | 2076-3425 |
language | English |
last_indexed | 2024-12-23T20:46:24Z |
publishDate | 2017-04-01 |
publisher | MDPI AG |
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series | Brain Sciences |
spelling | doaj.art-32f552677ef04fe096d034cc3c15fe4a2022-12-21T17:31:46ZengMDPI AGBrain Sciences2076-34252017-04-01743510.3390/brainsci7040035brainsci7040035A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCIPiotr Stawicki0Felix Gembler1Aya Rezeika2Ivan Volosyak3Faculty of Technology and Bionics, Rhine-Waal University of Applied Sciences, 47533 Kleve, GermanyFaculty of Technology and Bionics, Rhine-Waal University of Applied Sciences, 47533 Kleve, GermanyFaculty of Technology and Bionics, Rhine-Waal University of Applied Sciences, 47533 Kleve, GermanyFaculty of Technology and Bionics, Rhine-Waal University of Applied Sciences, 47533 Kleve, GermanySteady state visual evoked potentials (SSVEPs)-based Brain-Computer interfaces (BCIs), as well as eyetracking devices, provide a pathway for re-establishing communication for people with severe disabilities. We fused these control techniques into a novel eyetracking/SSVEP hybrid system, which utilizes eye tracking for initial rough selection and the SSVEP technology for fine target activation. Based on our previous studies, only four stimuli were used for the SSVEP aspect, granting sufficient control for most BCI users. As Eye tracking data is not used for activation of letters, false positives due to inappropriate dwell times are avoided. This novel approach combines the high speed of eye tracking systems and the high classification accuracies of low target SSVEP-based BCIs, leading to an optimal combination of both methods. We evaluated accuracy and speed of the proposed hybrid system with a 30-target spelling application implementing all three control approaches (pure eye tracking, SSVEP and the hybrid system) with 32 participants. Although the highest information transfer rates (ITRs) were achieved with pure eye tracking, a considerable amount of subjects was not able to gain sufficient control over the stand-alone eye-tracking device or the pure SSVEP system (78.13% and 75% of the participants reached reliable control, respectively). In this respect, the proposed hybrid was most universal (over 90% of users achieved reliable control), and outperformed the pure SSVEP system in terms of speed and user friendliness. The presented hybrid system might offer communication to a wider range of users in comparison to the standard techniques.http://www.mdpi.com/2076-3425/7/4/35Brain-Computer Interface (BCI)Electroencephalogram (EEG)Steady State Visual Evoked Potential (SSVEP)Eye TrackingHybrid BCI |
spellingShingle | Piotr Stawicki Felix Gembler Aya Rezeika Ivan Volosyak A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI Brain Sciences Brain-Computer Interface (BCI) Electroencephalogram (EEG) Steady State Visual Evoked Potential (SSVEP) Eye Tracking Hybrid BCI |
title | A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI |
title_full | A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI |
title_fullStr | A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI |
title_full_unstemmed | A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI |
title_short | A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI |
title_sort | novel hybrid mental spelling application based on eye tracking and ssvep based bci |
topic | Brain-Computer Interface (BCI) Electroencephalogram (EEG) Steady State Visual Evoked Potential (SSVEP) Eye Tracking Hybrid BCI |
url | http://www.mdpi.com/2076-3425/7/4/35 |
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