Mostrar el registro sencillo del ítem
Silla de ruedas eléctrica a escala controlada por señales electrooculográficas
| dc.contributor.author | Escobar Valencia, David | |
| dc.contributor.author | Regino Ubarnes, Fernando Jesús | |
| dc.contributor.author | Gómez Camperos, July Andrea | |
| dc.coverage.spatial | Colombia | en_US |
| dc.date.accessioned | 2025-10-27T20:44:48Z | |
| dc.date.available | 2025-10-27T20:44:48Z | |
| dc.date.issued | 2022-06-01 | |
| dc.identifier.issn | 1735-188X | en_US |
| dc.identifier.uri | https://repositorioinstitucional.ufpso.edu.co/xmlui/handle/20.500.14167/5956 | |
| dc.description.abstract | Las señales electrooculográficas o EOG son ampliamente utilizadas para desarrollar equipos robóticos para atender a personas que han perdido parcial o totalmente la funcionalidad de uno o varios miembros de su cuerpo debido a enfermedades neurodegenerativas como la Esclerosis Lateral Amiotrófica o accidentes graves. Estas señales se aplican en el control de brazos robóticos, juegos serios, sillas de ruedas robóticas, entre otros. Asimismo, estas señales requieren circuitos electrónicos especializados para su amplificación y filtrado, además de requerir un microcontrolador para su procesamiento. En este trabajo se presentan los resultados del desarrollo de un prototipo de un electrooculógrafo para el movimiento de una báscula de silla de ruedas, el diseño de adquisición de datos, el sistema de transmisión vía Bluetooth y el control de la silla de ruedas con el movimiento ocular. La adquisición de datos se realiza mediante electrodos de gel para EOG, un sistema de acondicionamiento de señal y la caracterización de este, también se presenta el sistema de transmisión de datos vía Bluetooth y la etapa de potencia. | en_US |
| dc.language.iso | en_US | en_US |
| dc.relation | https://www.webology.org/abstract.php?id=4201 | en_US |
| dc.title | Silla de ruedas eléctrica a escala controlada por señales electrooculográficas | en_US |
| dc.title.translated | Scaled Electric Wheelchair Controlled By Electro-Oculographic Signals | en_US |
| dc.contributor.cvlac | David Escobar Valencia [0000154045] | en_US |
| dc.contributor.cvlac | Fernando Jesús Regino Ubarnes [0001508915] | en_US |
| dc.contributor.cvlac | July Andrea Gómez Camperos [0001164287] | en_US |
| dc.contributor.googlescholar | Fernando Jesús Regino Ubarnes [l6g9NY8AAAAJ] | en_US |
| dc.contributor.orcid | David Escobar Valencia [0000-0002-1076-1597] | en_US |
| dc.contributor.orcid | Fernando Jesús Regino Ubarnes [0000-0003-0414-8654] | en_US |
| dc.contributor.orcid | July Andrea Gómez Camperos [0000-0003-3894-144X] | en_US |
| dc.contributor.researchgate | Fernando Jesús Regino Ubarnes [Fernando-Regino] | en_US |
| dc.contributor.scopus | Fernando Jesús Regino Ubarnes [57212414222] | en_US |
| dc.contributor.scopus | July Andrea Gómez Camperos [57220550902] | en_US |
| dc.description.abstractenglish | The electrooculographic signals or EOG are widely used to develop robotic equipment to serve people who have partially or totally lost the functionality of one or several members of their body due to neurodegenerative diseases such as Amyotrophic Lateral Sclerosis or serious accidents. These signals are applied in the control of robotic arms, serious games, robotic wheelchairs, among others. Also, these signals require specialized electronic circuits for amplification and filtering, in addition to requiring a microcontroller for processing them. This paper presents the results of the development of a prototype of an elctrooculography for the movement of a wheelchair scale, the design of data acquisition, the transmission system via Bluetooth and control of the wheelchair with eye movement is presented. The data acquisition is performed using gel electrodes for EOG, a signal conditioning system and the characterization of this, also presents the data transmission system via Bluetooth and the power stage. | en_US |
| dc.subject.proposal | Electrooculografía | en_US |
| dc.subject.proposal | Señales biológicas | en_US |
| dc.subject.proposal | Dipolo | en_US |
| dc.subject.proposal | Control | en_US |
| dc.subject.keywords | Electro oculography | en_US |
| dc.subject.keywords | Bio signals | en_US |
| dc.subject.keywords | Dipole | en_US |
| dc.subject.keywords | Control | en_US |
| dc.publisher.faculty | Facultad ingenierías | en_US |
| dc.type.redcol | http://purl.org/redcol/resource_type/ART | en_US |
| dc.relation.references | Alvarez-Estevez, D., van Velzen, I., Ottolini-Capellen, T., & Kemp, B. (2017). Derivation and modeling of two new features for the characterization of rapid and slow eye movements in electrooculographic sleep recordings. Biomedical Signal Processing and Control, 35, 87–99. https://doi.org/10.1016/j.bspc.2017.02.014 | en_US |
| dc.relation.references | Aungsakul, S., Phinyomark, A., Phukpattaranont, P., & Limsakul, C. (2012). Evaluating Feature Extraction Methods of Electrooculography (EOG) Signal for Human-Computer Interface. Procedia Engineering, 32, 246–252. https://doi.org/10.1016/j.proeng.2012.01.1264 | en_US |
| dc.relation.references | Barea, R., Boquete, L., Ortega, S., López, E., & Rodríguez-Ascariz, J. M. (2012). EOG-based eye movements codification for human computer interaction. Expert Systems with Applications, 39(3), 2677–2683. https://doi.org/10.1016/j.eswa.2011.08.123 | en_US |
| dc.relation.references | Bertomeu-Motos, A., Ezquerro, S., Barios, J. A., Lledó, L. D., Domingo, S., Nann, M., Martin, S., Soekadar, S. R., & Garcia-Aracil, N. (2019). User activity recognition system to improve the performance of environmental control interfaces: A pilot study with patients. Journal of NeuroEngineering and Rehabilitation, 16(1), 1–9. https://doi.org/10.1186/s12984-018-0477-5 | en_US |
| dc.relation.references | Horacio, A. (2014). Interfaz humano-computadora basada en señales de electrooculografía para personas con discapacidad motriz. ReCIBE. Revista Electrónica de Computación, Informática, Biomédica y Electrónica, 3(2). | en_US |
| dc.relation.references | Li, Y., He, S., Huang, Q., Gu, Z., & Yu, Z. L. (2018). A EOG-based switch and its application for “start/stop” control of a wheelchair. Neurocomputing, 275, 1350–1357. https://doi.org/10.1016/j.neucom.2017.09.085 | en_US |
| dc.relation.references | Lv, Z., Wang, Y., Zhang, C., Gao, X., & Wu, X. (2018). An ICA-based spatial filtering approach to saccadic EOG signal recognition. Biomedical Signal Processing and Control, 43, 9–17. https://doi.org/10.1016/j.bspc.2018.01.003 | en_US |
| dc.relation.references | Mehra, D., Tiwari, A., & Joshi, D. (2021). Investigating neural correlates of locomotion transition via temporal relation of EEG and EOG-recorded eye movements. Computers in Biology and Medicine, 132, 104350. https://doi.org/10.1016/j.compbiomed.2021.104350 | en_US |
| dc.relation.references | Mohammadi Fathabad, S., & Shahri, F. (2021). BH hysteresis measurement system for thin soft magnetic materials. Measurement, 172, 108896. https://doi.org/10.1016/j.measurement.2020.108896 | en_US |
| dc.relation.references | Ramli, R., Arof, H., Ibrahim, F., Mokhtar, N., & Idris, M. Y. I. (2015). Using finite state machine and a hybrid of EEG signal and EOG artifacts for an asynchronous wheelchair navigation. Expert Systems with Applications, 42(5), 2451–2463. https://doi.org/10.1016/j.eswa.2014.10.052 | en_US |
| dc.relation.references | Sharma, K., Jain, N., & Pal, P. K. (2020). Detection of eye closing/opening from EOG and its application in robotic arm control. Biocybernetics and Biomedical Engineering, 40(1), 173–186. https://doi.org/10.1016/j.bbe.2019.10.004 | en_US |
| dc.relation.references | Tang, W., Wang, A., Ramkumar, S., & Nair, R. K. R. (2020). Signal identification system for developing rehabilitative device using deep learning algorithms. Artificial Intelligence in Medicine, 102, 101755. https://doi.org/10.1016/j.artmed.2019.101755 | en_US |
| dc.relation.references | Wangmo, P., Ramyavani, G., Iyer, K. S., & Karthik Raj, V. (2019). Two electrode ECG and EOG system for monitoring applications. International Journal of Innovative Technology and Exploring Engineering, 8(11), 262–265. https://doi.org/10.35940/ijitee.K1315.0981119 | en_US |
Ficheros en el ítem
Este ítem aparece en la(s) siguiente(s) colección(ones)
-
Artículos [45]



