Classification of Cognitive Evoked Potentials for ADHD Detection in Children using Recurrence Plots and CNNs
Attention-deficit/hyperactivity disorder (ADHD) is a common childhood-onset condition characterized by difficulty paying attention and hyperactivity. The diagnosis of ADHD is made from psychological tests and electroencephalography (EEG). However, patient cooperation is necessary, which is a challen...
- Autores:
-
Cabarcas-Mena, Yina P.
Marrugo, Andres G.
Contreras-Ortiz, Sonia H.
- Tipo de recurso:
- Fecha de publicación:
- 2021
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/12347
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/12347
- Palabra clave:
- Evoked Potentials;
Electroencephalography;
Approximate Entropy
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Classification of Cognitive Evoked Potentials for ADHD Detection in Children using Recurrence Plots and CNNs |
| title |
Classification of Cognitive Evoked Potentials for ADHD Detection in Children using Recurrence Plots and CNNs |
| spellingShingle |
Classification of Cognitive Evoked Potentials for ADHD Detection in Children using Recurrence Plots and CNNs Evoked Potentials; Electroencephalography; Approximate Entropy LEMB |
| title_short |
Classification of Cognitive Evoked Potentials for ADHD Detection in Children using Recurrence Plots and CNNs |
| title_full |
Classification of Cognitive Evoked Potentials for ADHD Detection in Children using Recurrence Plots and CNNs |
| title_fullStr |
Classification of Cognitive Evoked Potentials for ADHD Detection in Children using Recurrence Plots and CNNs |
| title_full_unstemmed |
Classification of Cognitive Evoked Potentials for ADHD Detection in Children using Recurrence Plots and CNNs |
| title_sort |
Classification of Cognitive Evoked Potentials for ADHD Detection in Children using Recurrence Plots and CNNs |
| dc.creator.fl_str_mv |
Cabarcas-Mena, Yina P. Marrugo, Andres G. Contreras-Ortiz, Sonia H. |
| dc.contributor.author.none.fl_str_mv |
Cabarcas-Mena, Yina P. Marrugo, Andres G. Contreras-Ortiz, Sonia H. |
| dc.subject.keywords.spa.fl_str_mv |
Evoked Potentials; Electroencephalography; Approximate Entropy |
| topic |
Evoked Potentials; Electroencephalography; Approximate Entropy LEMB |
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LEMB |
| description |
Attention-deficit/hyperactivity disorder (ADHD) is a common childhood-onset condition characterized by difficulty paying attention and hyperactivity. The diagnosis of ADHD is made from psychological tests and electroencephalography (EEG). However, patient cooperation is necessary, which is a challenge with ADHD children. This work proposes a method for classification of ADHD and control cases from cognitive event-related potentials using recurrence plots and deep learning. A total of 44 children were included in this study (22 children with ADHD and 22 case controls). The signals were processed by a high-pass filter to eliminate DC components, wavelets transform with six decomposition levels, and synchronized averaging for each of the six channels (F3, AF3, F4, AF4, F7 and F8). Subsequently, the recurrence plot of each of the processed signals was obtained and used as inputs for two convolutional neural networks (CNN). The proposed models showed accuracies of 69.44% and 77,78%. © 2021 IEEE |
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2021 |
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2021 |
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2023-07-21T16:25:40Z |
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2023-07-21T16:25:40Z |
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2023 |
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Cabarcas-Mena, Y. P., Marrugo, A. G., & Contreras-Ortiz, S. H. (2021, September). Classification of cognitive evoked potentials for adhd detection in children using recurrence plots and cnns. In 2021 XXIII Symposium on Image, Signal Processing and Artificial Vision (STSIVA) (pp. 1-6). IEEE. |
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https://hdl.handle.net/20.500.12585/12347 |
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10.1109/STSIVA53688.2021.9592021 |
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Universidad Tecnológica de Bolívar |
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Repositorio Universidad Tecnológica de Bolívar |
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Cabarcas-Mena, Y. P., Marrugo, A. G., & Contreras-Ortiz, S. H. (2021, September). Classification of cognitive evoked potentials for adhd detection in children using recurrence plots and cnns. In 2021 XXIII Symposium on Image, Signal Processing and Artificial Vision (STSIVA) (pp. 1-6). IEEE. 10.1109/STSIVA53688.2021.9592021 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
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https://hdl.handle.net/20.500.12585/12347 |
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eng |
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eng |
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6 páginas |
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Cabarcas-Mena, Yina P.d03500fe-1d90-4e09-8e23-190978d9e262Marrugo, Andres G.3d6cd388-d48f-4669-934f-49ca4179f542Contreras-Ortiz, Sonia H.1d56d7f5-97c9-4429-b47d-48ebe97de2a82023-07-21T16:25:40Z2023-07-21T16:25:40Z20212023Cabarcas-Mena, Y. P., Marrugo, A. G., & Contreras-Ortiz, S. H. (2021, September). Classification of cognitive evoked potentials for adhd detection in children using recurrence plots and cnns. In 2021 XXIII Symposium on Image, Signal Processing and Artificial Vision (STSIVA) (pp. 1-6). IEEE.https://hdl.handle.net/20.500.12585/1234710.1109/STSIVA53688.2021.9592021Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarAttention-deficit/hyperactivity disorder (ADHD) is a common childhood-onset condition characterized by difficulty paying attention and hyperactivity. The diagnosis of ADHD is made from psychological tests and electroencephalography (EEG). However, patient cooperation is necessary, which is a challenge with ADHD children. This work proposes a method for classification of ADHD and control cases from cognitive event-related potentials using recurrence plots and deep learning. A total of 44 children were included in this study (22 children with ADHD and 22 case controls). The signals were processed by a high-pass filter to eliminate DC components, wavelets transform with six decomposition levels, and synchronized averaging for each of the six channels (F3, AF3, F4, AF4, F7 and F8). Subsequently, the recurrence plot of each of the processed signals was obtained and used as inputs for two convolutional neural networks (CNN). The proposed models showed accuracies of 69.44% and 77,78%. © 2021 IEEE6 páginasapplication/pdfenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf22021 XXIII Symposium on Image, Signal Processing and Artificial Vision (STSIVA)Classification of Cognitive Evoked Potentials for ADHD Detection in Children using Recurrence Plots and CNNsinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/drafthttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_2df8fbb1Evoked Potentials;Electroencephalography;Approximate EntropyLEMBCartagena de IndiasVásquez, J., Cárdenas, E.M., Feria, M., Benjet, C., Palacios, L., De La Peñ, F. 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