Adrien Combaz
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Adrien Combaz has a total of 13 co-authors. Here are the top co-authors by number of shared publications:
- Marc M. Van Hulle
Laboratory for Neuro- & Psychophysiology, Department of Neurosciences, KU Leuven—University of Leuven, B-3000 Leuven, Belgium
3 shared publications - Nikolay V. Manyakov
Janssen Pharmaceutica NV, Beerse, Belgium
2 shared publications A. Robben
K.U. Leuven, Laboratorium voor Neuro- en Psychofysiologie, Herestraat 49, B-3000 Leuven, Belgium
1 shared publicationAnn Goeleven
Department of Speech Language Pathology, ENT Head and Neck Surgery, University Hospitals Leuven, Leuven, Belgium
1 shared publicationArne Robben
Computational Neuroscience Group, Laboratory for Neuro- and Psychophysiology, KU Leuven, Leuven, Belgium
1 shared publication- Camille Chatelle
Coma Science Group, GIGA-consciousness, University of Liège, Liège, Belgium
1 shared publication
Latest Publications
- Open Access
- 27 March 2015
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 10 (3) , e0121481
Simultaneous Detection of P300 and Steady-State Visually Evoked Potentials for Hybrid Brain-Computer Interface
We study the feasibility of a hybrid Brain-Computer Interface (BCI) combining simultaneous visual oddball and Steady-State Visually Evoked Potential (SSVEP) paradigms, where both types of stimuli are superimposed on a computer screen. Potentially, such a combination could result in a system being able to operate faster than a purely P300-based BCI and encode more targets than a purely SSVEP-based BCI. We analyse the interactions between the brain responses of the two paradigms, and assess the possibility to detect simultaneously the brain activity evoked by both paradigms, in a series of 3 experiments where EEG data are analysed offline. Despite differences in the shape of the P300 response between pure oddball and hybrid condition, we observe that the classification accuracy of this P300 response is not affected by the SSVEP stimulation. We do not observe either any effect of the oddball stimulation on the power of the SSVEP response in the frequency of stimulation. Finally results from the last experiment show the possibility of detecting both types of brain responses simultaneously and suggest not only the feasibility of such hybrid BCI but also a gain over pure oddball- and pure SSVEP-based BCIs in terms of communication rate.
- 27 March 2015
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 10 (3) , e0121481
Open AccessSimultaneous Detection of P300 and Steady-State Visually Evoked Potentials for Hybrid Brain-Computer Interface
We study the feasibility of a hybrid Brain-Computer Interface (BCI) combining simultaneous visual oddball and Steady-State Visually Evoked Potential (SSVEP) paradigms, where both types of stimuli are superimposed on a computer screen. Potentially, such a combination could result in a system being able to operate faster than a purely P300-based BCI and encode more targets than a purely SSVEP-based BCI. We analyse the interactions between the brain responses of the two paradigms, and assess the possibility to detect simultaneously the brain activity evoked by both paradigms, in a series of 3 experiments where EEG data are analysed offline. Despite differences in the shape of the P300 response between pure oddball and hybrid condition, we observe that the classification accuracy of this P300 response is not affected by the SSVEP stimulation. We do not observe either any effect of the oddball stimulation on the power of the SSVEP response in the frequency of stimulation. Finally results from the last experiment show the possibility of detecting both types of brain responses simultaneously and suggest not only the feasibility of such hybrid BCI but also a gain over pure oddball- and pure SSVEP-based BCIs in terms of communication rate.
- Open Access
- 25 September 2013
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 8 (9) , e73691
A Comparison of Two Spelling Brain-Computer Interfaces Based on Visual P3 and SSVEP in Locked-In Syndrome
We study the applicability of a visual P3-based and a Steady State Visually Evoked Potentials (SSVEP)-based Brain-Computer Interfaces (BCIs) for mental text spelling on a cohort of patients with incomplete Locked-In Syndrome (LIS). Seven patients performed repeated sessions with each BCI. We assessed BCI performance, mental workload and overall satisfaction for both systems. We also investigated the effect of the quality of life and level of motor impairment on the performance. All seven patients were able to achieve an accuracy of 70% or more with the SSVEP-based BCI, compared to 3 patients with the P3-based BCI, showing a better performance with the SSVEP BCI than with the P3 BCI in the studied cohort. Moreover, the better performance of the SSVEP-based BCI was accompanied by a lower mental workload and a higher overall satisfaction. No relationship was found between BCI performance and level of motor impairment or quality of life. Our results show a better usability of the SSVEP-based BCI than the P3-based one for the sessions performed by the tested population of locked-in patients with respect to all the criteria considered. The study shows the advantage of developing alternative BCIs with respect to the traditional matrix-based P3 speller using different designs and signal modalities such as SSVEPs to build a faster, more accurate, less mentally demanding and more satisfying BCI by testing both types of BCIs on a convenience sample of LIS patients.
- 25 September 2013
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 8 (9) , e73691
Open AccessA Comparison of Two Spelling Brain-Computer Interfaces Based on Visual P3 and SSVEP in Locked-In Syndrome
We study the applicability of a visual P3-based and a Steady State Visually Evoked Potentials (SSVEP)-based Brain-Computer Interfaces (BCIs) for mental text spelling on a cohort of patients with incomplete Locked-In Syndrome (LIS). Seven patients performed repeated sessions with each BCI. We assessed BCI performance, mental workload and overall satisfaction for both systems. We also investigated the effect of the quality of life and level of motor impairment on the performance. All seven patients were able to achieve an accuracy of 70% or more with the SSVEP-based BCI, compared to 3 patients with the P3-based BCI, showing a better performance with the SSVEP BCI than with the P3 BCI in the studied cohort. Moreover, the better performance of the SSVEP-based BCI was accompanied by a lower mental workload and a higher overall satisfaction. No relationship was found between BCI performance and level of motor impairment or quality of life. Our results show a better usability of the SSVEP-based BCI than the P3-based one for the sessions performed by the tested population of locked-in patients with respect to all the criteria considered. The study shows the advantage of developing alternative BCIs with respect to the traditional matrix-based P3 speller using different designs and signal modalities such as SSVEPs to build a faster, more accurate, less mentally demanding and more satisfying BCI by testing both types of BCIs on a convenience sample of LIS patients.
- 6 November 2011
- Published by Elsevier in Neurocomputing
- Vol. 80, 73-82
Towards the detection of error-related potentials and its integration in the context of a P300 speller brain–computer interface
- 6 November 2011
- Published by Elsevier in Neurocomputing
- Vol. 80, 73-82
Towards the detection of error-related potentials and its integration in the context of a P300 speller brain–computer interface
- 1 January 2011
- Published by INSTICC
- p. 328-334
COMPARISON OF LINEAR CLASSIFICATION METHODS FOR P300 BRAIN-COMPUTER INTERFACE ON DISABLED SUBJECTS
- 1 January 2011
- Published by INSTICC
- p. 328-334
COMPARISON OF LINEAR CLASSIFICATION METHODS FOR P300 BRAIN-COMPUTER INTERFACE ON DISABLED SUBJECTS