Linear vs nonlinear classification of social joint attention in autism using VR P300-based brain computer interfaces
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ID-3's LDA outperformed the other classifiers and was used to classify the target object.
“LDA outperformed the other classifiers and was used to classify the target object.”
From BCIAUT-P300: A Multi-Session and Multi-Subject Benchmark Dataset on Autism for P300-Based Brain-Computer-Interfaces (2020) · cites this paper as de Arancibia et al., 2020
Cites
Farwell, L. A., & Donchin, E. (1988) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(88)90149-6 · Cited by 3,228 · see citing works
A comparison of classification techniques for the P300 Speller
Krusienski, D. J., Sellers, E. W., Cabestaing, F., Bayoudh, S., McFarland, D. J., Vaughan, T. M., & Wolpaw, J. R. (2006) · Journal of Neural Engineering · doi:10.1088/1741-2560/3/4/007 · Cited by 762 · see citing works
Brief Report: Forecasting the Economic Burden of Autism in 2015 and 2025 in the United States
Leigh, J. P., & Du, J. (2015) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-015-2521-7 · Cited by 424 · see citing works
Deep learning based on Batch Normalization for P300 signal detection
Liu, M., Wu, W., Gu, Z., Yu, Z., Qi, F., & Li, Y. (2018) · Neurocomputing · doi:10.1016/j.neucom.2017.08.039 · Cited by 230 · see citing works
Convolutional Neural Network for Multi-Category Rapid Serial Visual Presentation BCI
Manor, R., & Geva, A. B. (2015) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2015.00146 · Cited by 144 · see citing works
Detection of P300 Waves in Single Trials by the Wavelet Transform (WT)
Demıralp, T., Ademoğlu, A., Schürmann, M., Başar‐Eroğlu, C., & Başar, E. (1999) · Brain and Language · doi:10.1006/brln.1998.2027 · Cited by 127 · see citing works
Amaral, C., Mouga, S., Simões, M., Pereira, H. C., Bernardino, I., Quental, H., Playle, R., McNamara, R., Oliveira, G., & Castelo-Branco, M. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00477 · Cited by 94 · see citing works
Amaral, C. P., Simões, M. A., Mouga, S., Andrade, J., & Castelo-Branco, M. S. (2017) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2017.07.029 · Cited by 86 · see citing works
Bostanov, V., & Kotchoubey, B. (2006) · Clinical Neurophysiology · doi:10.1016/j.clinph.2006.08.012 · Cited by 52 · see citing works
Wavelet algorithm for the identification of P300 ERP componentPreprint
Agapov, S. N., Bulanov, V., Zakharov, A. V., & Sergeeva, M. S. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1611.00033 · Cited by 4 · see citing works
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Simões, M., Borra, D., Santamaría-Vázquez, E., GBT-UPM, Bittencourt-Villalpando, M., Krzemiński, D., Miladinović, A., Neural_Engineering_Group, Schmid, T., Zhao, H., et al. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.568104 · Cited by 72 · see citing works
XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019
(2019) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-3-030-31635-8 · Cited by 59 · see citing works
Hatim, H. A., Alyasseri, Z. A. A., & Jamil, N. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-025-11302-x · Cited by 46 · see citing works
Borra, D., Magosso, E., Castelo-Branco, M. S., & Simões, M. A. (2022) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac7908 · Cited by 40 · see citing works
A Practical EEG-Based Human-Machine Interface to Online Control an Upper-Limb Assist Robot
Song, Y., Cai, S., Yang, L., Li, G., Wu, W., & Xie, L. (2020) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2020.00032 · Cited by 40 · see citing works
Leveraging Deep Learning Techniques to Improve P300-Based Brain Computer Interfaces
Da, I., Dui, L. G., Ferrante, S., Pedrocchi, A., & Antonietti, A. (2022) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2022.3174771 · Cited by 24 · see citing works
CNN-FEBAC: A framework for attention measurement of autistic individuals
Patel, M., Bhatt, H., Munshi, M., Pandya, S., Jain, S., Thakkar, P., & Yoon, S. W. (2023) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2023.105018 · Cited by 16 · see citing works
A survey on technological tools and systems for diagnosis and therapy of autism spectrum disorder
Bondioli, M., Chessa, S., Kocian, A., & Pelagatti, S. (2023) · Human-Computer Interaction · doi:10.1080/07370024.2023.2242345 · Cited by 12 · see citing works
Design of Transcranial Electromagnetic Therapy Device Based on Kano
Chang, M., Yan, D., Wang, Y., & Chen, S. (2023) · International Conference on Mechatronics and Electrical Engineering (MEEE) · doi:10.1109/meee57080.2023.10126737
An Optimal EEG Features Extraction Methods for Autism Detection
Hatim, H. A., & Alyasseri, Z. A. A. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-96-3942-7_47
Wilson, S. M., & Kannan, K. S. (2025) · Optical Memory and Neural Networks · doi:10.3103/s1060992x25600454
- Authors
- de Arancibia, L., Sánchez-González, P., Gómez, E. J., Hernando, M. E., & Oropesa, I.
- Affiliations
- Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (ES)
- Venue
- IFMBE Proceedings
- Publisher
- Springer International Publishing
- Published
- 2019-09-25
- Pages
- 1869-1874
- ISSN
- 1433-9277 (ISSN-L)
- 1680-0737
- OpenAlex
- W2976551994
- Cited by
- 11
- References
- 10
- Citations by year
- 2025: 3 · 2023: 3 · 2022: 2 · 2020: 2 · 2019: 1
- FWCI
- 2.15
- Type
- conference paper
- Language
- en
- Open access
- green
- oa.upm.es
- Licence
- cc-by-nc-nd
- www.springer.com/tdm (tdm)
- Locations
- World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany (publishedVersion)
- Hispana (acceptedVersion, cc-by-nc-nd)
- UPM Digital Archive (Technical University of Madrid) (submittedVersion, cc-by-nc-nd)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Keywords
- autism spectrum disorder, virtual reality, P300, brain-computer interface, EEG, linear discriminant analysis, time-frequency features, neurorehabilitation, attention training
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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