Desarrollo de un sistema de IoT con machine learning para la detección temprana de crisis epilépticas

Esta investigación aborda la creación de un sistema basado en el Internet de las Cosas (IoT) y optimizado mediante técnicas de aprendizaje automático para la detección temprana de crisis epilépticas. Se desarrolló un algoritmo capaz de capturar señales biológicas a través de sensores portátiles y pr...

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Autores:
Peña Arismendi, Santiago Andrés
Tipo de recurso:
Fecha de publicación:
2024
Institución:
Universidad Distrital Francisco José de Caldas
Repositorio:
RIUD: repositorio U. Distrital
Idioma:
spa
OAI Identifier:
oai:repository.udistrital.edu.co:11349/42172
Acceso en línea:
http://hdl.handle.net/11349/42172
Palabra clave:
Detección temprana de crisis epilépticas
Internet de las Cosas (IoT)
Aprendizaje automático en salud
Sensores portátiles biomédicos
Redes neuronales en epilepsia
Monitoreo cardíaco predictivo
Maestría en Ciencias de la Información y las Comunicaciones -- Tesis y disertaciones académicas
Internet de las Cosas (IoT)
Aprendizaje automático en salud
Detección temprana de crisis epilépticas
Early detection of epileptic seizures
Internet of Things (IoT)
Machine learning in healthcare
Wearable biomedical sensors
Neural networks in epilepsy
Predictive cardiac monitoring
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id UDISTRITA2_1eca552e99e28bcca6064c7f335a2542
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network_acronym_str UDISTRITA2
network_name_str RIUD: repositorio U. Distrital
repository_id_str
dc.title.none.fl_str_mv Desarrollo de un sistema de IoT con machine learning para la detección temprana de crisis epilépticas
dc.title.titleenglish.none.fl_str_mv Development of an IoT system with machine learning for the early detection of epileptic seizures
title Desarrollo de un sistema de IoT con machine learning para la detección temprana de crisis epilépticas
spellingShingle Desarrollo de un sistema de IoT con machine learning para la detección temprana de crisis epilépticas
Detección temprana de crisis epilépticas
Internet de las Cosas (IoT)
Aprendizaje automático en salud
Sensores portátiles biomédicos
Redes neuronales en epilepsia
Monitoreo cardíaco predictivo
Maestría en Ciencias de la Información y las Comunicaciones -- Tesis y disertaciones académicas
Internet de las Cosas (IoT)
Aprendizaje automático en salud
Detección temprana de crisis epilépticas
Early detection of epileptic seizures
Internet of Things (IoT)
Machine learning in healthcare
Wearable biomedical sensors
Neural networks in epilepsy
Predictive cardiac monitoring
title_short Desarrollo de un sistema de IoT con machine learning para la detección temprana de crisis epilépticas
title_full Desarrollo de un sistema de IoT con machine learning para la detección temprana de crisis epilépticas
title_fullStr Desarrollo de un sistema de IoT con machine learning para la detección temprana de crisis epilépticas
title_full_unstemmed Desarrollo de un sistema de IoT con machine learning para la detección temprana de crisis epilépticas
title_sort Desarrollo de un sistema de IoT con machine learning para la detección temprana de crisis epilépticas
dc.creator.fl_str_mv Peña Arismendi, Santiago Andrés
dc.contributor.advisor.none.fl_str_mv Salcedo Parra , Octavio José
Guio Mahecha, Laura Victoria
dc.contributor.author.none.fl_str_mv Peña Arismendi, Santiago Andrés
dc.contributor.orcid.none.fl_str_mv Salcedo Parra , Octavio José []0000-0002-0767-8522
dc.subject.none.fl_str_mv Detección temprana de crisis epilépticas
Internet de las Cosas (IoT)
Aprendizaje automático en salud
Sensores portátiles biomédicos
Redes neuronales en epilepsia
Monitoreo cardíaco predictivo
topic Detección temprana de crisis epilépticas
Internet de las Cosas (IoT)
Aprendizaje automático en salud
Sensores portátiles biomédicos
Redes neuronales en epilepsia
Monitoreo cardíaco predictivo
Maestría en Ciencias de la Información y las Comunicaciones -- Tesis y disertaciones académicas
Internet de las Cosas (IoT)
Aprendizaje automático en salud
Detección temprana de crisis epilépticas
Early detection of epileptic seizures
Internet of Things (IoT)
Machine learning in healthcare
Wearable biomedical sensors
Neural networks in epilepsy
Predictive cardiac monitoring
dc.subject.lemb.none.fl_str_mv Maestría en Ciencias de la Información y las Comunicaciones -- Tesis y disertaciones académicas
Internet de las Cosas (IoT)
Aprendizaje automático en salud
Detección temprana de crisis epilépticas
dc.subject.keyword.none.fl_str_mv Early detection of epileptic seizures
Internet of Things (IoT)
Machine learning in healthcare
Wearable biomedical sensors
Neural networks in epilepsy
Predictive cardiac monitoring
description Esta investigación aborda la creación de un sistema basado en el Internet de las Cosas (IoT) y optimizado mediante técnicas de aprendizaje automático para la detección temprana de crisis epilépticas. Se desarrolló un algoritmo capaz de capturar señales biológicas a través de sensores portátiles y procesarlas en una arquitectura IoT. Los datos obtenidos del Hospital de la Misericordia en Bogotá fueron usados para validar diversos modelos, destacándose un árbol de decisión y una red neuronal perceptrón multicapa, que lograron precisiones de 92.47% y 93.56%, respectivamente. En entornos clínicos reales, estos modelos lograron una precisión del 65%. La arquitectura propuesta permite enviar alertas preventivas en tiempo real, ofreciendo una herramienta potencialmente eficaz para mejorar la calidad de vida de personas con epilepsia.
publishDate 2024
dc.date.accessioned.none.fl_str_mv 2024-10-25T16:09:07Z
dc.date.available.none.fl_str_mv 2024-10-25T16:09:07Z
dc.date.created.none.fl_str_mv 2024-08-29
dc.type.none.fl_str_mv masterThesis
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_7a1f
dc.type.degree.none.fl_str_mv Investigación-Innovación
dc.type.driver.none.fl_str_mv info:eu-repo/semantics/bachelorThesis
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/11349/42172
url http://hdl.handle.net/11349/42172
dc.language.iso.none.fl_str_mv spa
language spa
dc.relation.references.none.fl_str_mv Ali A . Abed. (2017). Internet of Things ( IoT ): Architecture and Design. Computer Engineering Department/University of Basra 1, December.
Andreessen, M., & Bina, E. (1996). NCSA Mosaic. Software: Practice and Experience, 25, 501–506.
Ashton, K. (2009). That “Internet of Things” Thing. RFID Journal.
Barrio Andrés, Moisés. (2020). Internet de las cosas / Moisés Barrio Andrés. In Internet de las cosas / (2a. edición.). Reus,.
Beniczky, S., Aurlien, H., Brøgger, J. C., Fuglsang-Frederiksen, A., Martins-Da-Silva, A., Trinka, E., Visser, G., Rubboli, G., Hjalgrim, H., Stefan, H., Rosén, I., Zarubova, J., Dobesberger, J., Alving, J., Andersen, K. V., Fabricius, M., Atkins, M. D., Neufeld, M., Plouin, P., … Wolf, P. (2013). Standardized Computer-based Organized Reporting of EEG: SCORE. Epilepsia, 54(6), 1112–1124. https://doi.org/10.1111/epi.12135
Bermeo-Ovalle, A. C., Kennedy, J. D., & Schuele, S. U. (2015). Cardiac and autonomic mechanisms contributing to SUDEP. J Clin Neurophysiol. Abstract: Sudden Unexpected Death in Epilepsy Is Likely Caused by a Cascade of Events Affecting the Vegetative Nervous System Leading to Cardiorespiratory Failure and Death, 1(1), 21– 29.
Boyd, D. M., & Ellison, N. B. (2007). Social Network Sites: Definition, History, and Scholarship. Journal of Computer-Mediated Communication, 13, 210–230.
Cerf, V. G., & Kahn, R. E. (1974). A protocol for packet network intercommunication. IEEE Transactions on Communications, 22(5), 637–648.
Chekhmane, G., & Benali, R. (2022). EEG signals analysis using SVM and MLPNN classifiers for epilepsy detection. 2022 5th International Symposium on Informatics and Its Applications (ISIA), 1–6. https://doi.org/10.1109/ISIA55826.2022.9993577
Eggleston, K. S., Olin, B. D., & Fisher, R. S. (2014a). Ictal tachycardia: The head-heart connection. Seizure, 23(7), 496–505. https://doi.org/10.1016/j.seizure.2014.02.012
Evans, D. (2011). The Internet of Things: How the Next Evolution of the Internet Is Changing Everything.
Fisher, R. S., Cross, J. H., French, J. A., Higurashi, N., Hirsch, E., Jansen, F. E., Lagae, L., Moshé, S. L., Peltola, J., Roulet Perez, E., Scheffer, I. E., & Zuberi, S. M. (2017). Operational classification of seizure types by the International League Against Epilepsy: Position Paper of the ILAE Commission for Classification and Terminology. Epilepsia, 58(4), 522–530. https://doi.org/10.1111/epi.13670
Fisher, R. S., Van Emde Boas, W., Blume, W., Elger, C., Genton, P., Lee, P., & Engel, J. (2005). Epileptic seizures and epilepsy: Definitions proposed by the International League Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE). Epilepsia, 46(4), 470–472. https://doi.org/10.1111/j.0013-9580.2005.66104.x
Fujiwara, K., Miyajima, M., Yamakawa, T., Abe, E., Suzuki, Y., Sawada, Y., Kano, M., Maehara, T., Ohta, K., Sasai-Sakuma, T., Sasano, T., Matsuura, M., & Matsushima, E. (2016a). Epileptic Seizure Prediction Based on Multivariate Statistical Process Control of Heart Rate Variability Features. IEEE Transactions on Biomedical Engineering, 63(6), 1321–1332. https://doi.org/10.1109/TBME.2015.2512276
Giannakakis, G., Tsiknakis, M., & Vorgia, P. (2019). Computer Methods and Programs in Biomedicine Focal epileptic seizures anticipation based on patterns of heart rate variability parameters. 178, 123–133. https://doi.org/10.1016/j.cmpb.2019.05.032
González, D. R. (2013). Arquitectura y Gestión de la IoT IoT Network Management / Abstract. Revista Telem@tica, 12(3), 49–60.
Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29, 1645–1660.
Hampel, K. G., Rocamora Zuñiga, R., & Quesada, C. M. (2016). Unravelling the mysteries of sudden unexpected death in epilepsy. Neurologia. https://doi.org/10.1016/j.nrl.2017.02.004
Jansen, K., Varon, C., Van Huffel, S., & Lagae, L. (2013a). Peri-ictal ECG changes in childhood epilepsy: Implications for detection systems. Epilepsy and Behavior, 29(1), 72–76. https://doi.org/10.1016/j.yebeh.2013.06.030
Lasefr, Z., Reddy, R. R., & Elleithy, K. (2017). Smart Phone Application Development for Monitoring Epilepsy Seizure Detection based on EEG signal Classification. 2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON), 83–87.
Leach, J. P., Stephen, L. J., Salveta, C., & Brodie, M. J. (2006a). Which electroencephalography (EEG) for epilepsy? The relative usefulness of different EEG protocols in patients with possible epilepsy. Journal of Neurology, Neurosurgery and Psychiatry, 77(9), 1040–1042. https://doi.org/10.1136/jnnp.2005.084871
Lee, T. M. C., & Chan, J. K. P. (2002). Factores que afectan el estado cognitivo de personas que sufren epilepsia. Departamento de Psicología. Universidad de Hong Kong. Hong Kong, 34(9), 861–865.
Leiner, B. M., Cerf, V. G., Clark, D. D., Kahn, R. E., Kleinrock, L., Lynch, D. C., Postel, J., Roberts, L. G., & Wolff, S. (2009). A brief history of the Internet. ACM SIGCOMM Computer Communication Review, 39(5), 22–31.
López, M. (2019). Internet de las cosas La transformación digital de la sociedad. In de Internet de las cosas La transformación digital de la sociedad, Madrid, Ra-Ma.
Lytton, W. W. (2008). Computer modelling of epilepsy. Nature Reviews Neuroscience, 9(8), 626–637.
Malik, M. (1996). Heart Rate Variability: Standards of Measurement, Physiological Interpretation, and Clinical Use Task Force of The European Society of Cardiology and the North American Society for Pacing and Electrophysiology. https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1542-474X.1996.tb00275.x
Megiddo, I., Colson, A., Chisholm, D., Dua, T., Nandi, A., & Laxminarayan, R. (2016). Health and economic benefits of public financing of epilepsy treatment in India: An agent- based simulation model. Epilepsia, 57(3), 464–474. https://doi.org/10.1111/epi.13294
Ministerio de Salud y Protección Social. (2017, February 13). Epilepsia: mucho más que convulsiones.
Miraz, M. H., Ali, M., Excell, P. S., & Picking, R. (2015). A Review on Internet of Things (loT), Internet of Everything (IoE) and Internet ofNano Things (IoNT). Internet Technologies and Applications (ITA).
Moridani, M. K., & Farhadi, H. (2017). Heart rate variability as a biomarker for epilepsy seizure prediction. Bratislava Medical Journal, 118(1). https://doi.org/10.4149/BLL_2017_001
Nagai, Y., Goldstein, L. H., Fenwick, P. B. C., & Trimble, M. R. (2004). Clinical efficacy of galvanic skin response biofeedback training in reducing seizures in adult epilepsy: A preliminary randomized controlled study. Epilepsy and Behavior, 5(2), 216–223. https://doi.org/10.1016/j.yebeh.2003.12.003
Nagai, Y., Jones, C. I., & Sen, A. (2019). Galvanic Skin Response (GSR)/Electrodermal/Skin Conductance Biofeedback on Epilepsy: A Systematic Review and Meta-Analysis. In Frontiers in Neurology (Vol. 10). Frontiers Media S.A. https://doi.org/10.3389/fneur.2019.00377
Nguyen Thi Anh-Dao, Tran Duc-Nghia, Nguyen Thi-Hao, Tran Duc-Tan, Nguyen Linh- Trung, IEEE Communications Society, International Conference on Advanced Technologies for Communications 6 2013.10.16-18 Ho Chi Minh City, & ATC 6 2013.10.16-18 Ho Chi Minh City. (2013). An Effective Procedure for Reducing EOG and EMG Artefacts from EEG Signals. International Conference on Advanced Technologies for Communications
Organización Mundial de la Salud (OMS). (2023, February 9). Epilepsia. https://www.who.int/es/news-room/fact-sheets/detail/epilepsy
Patel, S., Mancinelli, C., Dalton, A., Patritti, B., Pang, T., Schachter, S., & Bonato, P. (2009). Detecting epileptic seizures using wearable sensors. Bioengineering, Proceedings of the Northeast Conference, 4–5. https://doi.org/10.1109/NEBC.2009.4967771
Rajaguru, H. (2017). EEG features for Epilepsy Detection. Iccmc, 981–984.
Ray, A., Tao, J. X., Hawes-Ebersole, S. M., & Ebersole, J. S. (2007a). Localizing value of scalp EEG spikes: A simultaneous scalp and intracranial study. Clinical Neurophysiology, 118(1), 69–79. https://doi.org/10.1016/j.clinph.2006.09.010
Rushalina, D., Wisana, I. D. G. H., Nugraha, P. C., & Ragimova, N. (2022). Analysis of Transmitted and Received ECG Signal Based on Internet of Thing Using Web Browser and Server-Client HTML Protocol. Jurnal Teknokes, 15(4). https://doi.org/10.35882/teknokes.v15i4.469
Singh, B., Bhattacharya, S., Chowdhary, C. L., & Jat, D. S. (2017a). A review on internet of things and its applications in healthcare. Journal of Chemical and Pharmaceutical Sciences, 10(1), 447–452.
Smith, A. (2011). Smartphone Adoption and Usage. Pew Internet & American Life Project.
Sundmaeker, H., Guillemin, P., Friess, P., & Woelfflé, S. (2010). Vision and Challenges for Realising the Internet of Things. http://europa.eu/information_society
Tatum, W. O., Rubboli, G., Kaplan, P. W., Mirsatari, S. M., Radhakrishnan, K., Gloss, D., Caboclo, L. O., Drislane, F. W., Koutroumanidis, M., Schomer, D. L., Kastelijn-Nolst Trenite, D., Cook, M., & Beniczky, S. (2018). Clinical utility of EEG in diagnosing and monitoring epilepsy in adults. Clinical Neurophysiology, 129, 1056–1082. https://doi.org/10.1016/j.clinph.2018.01.019
Thara, D. K., Premasudha, B. G., & Krivic, S. (n.d.). Detection of epileptic seizure events using pre-trained convolutional neural network, VGGNet and ResNet. Expert Systems, n/a(n/a), e13447. https://doi.org/https://doi.org/10.1111/exsy.13447
Vergara, P. M., De La Cal, E., Villar, J. R., González, V. M., & Sedano, J. (2017a). An IoT Platform for Epilepsy Monitoring and Supervising. Journal of Sensors, 2017. https://doi.org/10.1155/2017/6043069
Wagle, S. (2016). Semantic data extraction over MQTT for IoTcentric wireless sensor networks. 2016 International Conference on Internet of Things and Applications (IOTA), 227–232. https://doi.org/10.1109/IOTA.2016.7562727
Watthanawisuth, N., Maturos, T., Sappat, A., & Tuantranont, A. (2015). The IoT wearable stretch sensor using 3D-Graphene foam. 2015 IEEE SENSORS - Proceedings, 3–6. https://doi.org/10.1109/ICSENS.2015.7370275
What is ICANN? (2020). ICANN. https://www.icann.org/resources/pages/what-2012-02-25- en
Wu, M., Lu, T.-J., Ling, F.-Y., Sun, J., & Du, H.-Y. (2010). Research on the architecture of Internet of Things. 2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE), 5, V5-484-V5-487. https://doi.org/10.1109/ICACTE.2010.5579493
Yamakawa, T., Miyajima, M., Fujiwara, K., Kano, M., Suzuki, Y., Watanabe, Y., Watanabe, S., Hoshida, T., Inaji, M., & Maehara, T. (2020). Wearable epileptic seizure prediction system with machine-learning-based anomaly detection of heart rate variability. Sensors (Switzerland), 20(14), 1–16. https://doi.org/10.3390/s20143987
Zapata Barco, A. M., Restrepo-Martínez, M., & Restrepo, D. (2020). Depression in People with Epilepsy. What is the Connection? In Revista Colombiana de Psiquiatria (Vol. 49, Issue 1, pp. 53–61). Elsevier Doyma. https://doi.org/10.1016/j.rcp.2017.10.004
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spelling Salcedo Parra , Octavio JoséGuio Mahecha, Laura VictoriaPeña Arismendi, Santiago AndrésSalcedo Parra , Octavio José []0000-0002-0767-85222024-10-25T16:09:07Z2024-10-25T16:09:07Z2024-08-29http://hdl.handle.net/11349/42172Esta investigación aborda la creación de un sistema basado en el Internet de las Cosas (IoT) y optimizado mediante técnicas de aprendizaje automático para la detección temprana de crisis epilépticas. Se desarrolló un algoritmo capaz de capturar señales biológicas a través de sensores portátiles y procesarlas en una arquitectura IoT. Los datos obtenidos del Hospital de la Misericordia en Bogotá fueron usados para validar diversos modelos, destacándose un árbol de decisión y una red neuronal perceptrón multicapa, que lograron precisiones de 92.47% y 93.56%, respectivamente. En entornos clínicos reales, estos modelos lograron una precisión del 65%. La arquitectura propuesta permite enviar alertas preventivas en tiempo real, ofreciendo una herramienta potencialmente eficaz para mejorar la calidad de vida de personas con epilepsia.This research addresses the development of a system based on the Internet of Things (IoT) and optimized through machine learning techniques for the early detection of epileptic seizures. An algorithm was developed to capture biological signals through wearable sensors and process them within an IoT architecture. Data obtained from the Hospital de la Misericordia in Bogotá were used to validate various models, with a decision tree and a multilayer perceptron neural network standing out, achieving accuracies of 92.47% and 93.56%, respectively. In real clinical settings, these models achieved an accuracy of 65%. The proposed architecture allows for real-time preventive alerts, offering a potentially effective tool to improve the quality of life for people with epilepsy.pdfspaUniversidad Distrital Francisco José de CaldasDetección temprana de crisis epilépticasInternet de las Cosas (IoT)Aprendizaje automático en saludSensores portátiles biomédicosRedes neuronales en epilepsiaMonitoreo cardíaco predictivoMaestría en Ciencias de la Información y las Comunicaciones -- Tesis y disertaciones académicasInternet de las Cosas (IoT)Aprendizaje automático en saludDetección temprana de crisis epilépticasEarly detection of epileptic seizuresInternet of Things (IoT)Machine learning in healthcareWearable biomedical sensorsNeural networks in epilepsyPredictive cardiac monitoringDesarrollo de un sistema de IoT con machine learning para la detección temprana de crisis epilépticasDevelopment of an IoT system with machine learning for the early detection of epileptic seizuresmasterThesisInvestigación-Innovacióninfo:eu-repo/semantics/bachelorThesishttp://purl.org/coar/resource_type/c_7a1fAbierto (Texto Completo)http://purl.org/coar/access_right/c_abf2Ali A . Abed. (2017). Internet of Things ( IoT ): Architecture and Design. Computer Engineering Department/University of Basra 1, December.Andreessen, M., & Bina, E. (1996). NCSA Mosaic. Software: Practice and Experience, 25, 501–506.Ashton, K. (2009). That “Internet of Things” Thing. RFID Journal.Barrio Andrés, Moisés. (2020). Internet de las cosas / Moisés Barrio Andrés. In Internet de las cosas / (2a. edición.). Reus,.Beniczky, S., Aurlien, H., Brøgger, J. C., Fuglsang-Frederiksen, A., Martins-Da-Silva, A., Trinka, E., Visser, G., Rubboli, G., Hjalgrim, H., Stefan, H., Rosén, I., Zarubova, J., Dobesberger, J., Alving, J., Andersen, K. V., Fabricius, M., Atkins, M. D., Neufeld, M., Plouin, P., … Wolf, P. (2013). Standardized Computer-based Organized Reporting of EEG: SCORE. Epilepsia, 54(6), 1112–1124. https://doi.org/10.1111/epi.12135Bermeo-Ovalle, A. C., Kennedy, J. D., & Schuele, S. U. (2015). Cardiac and autonomic mechanisms contributing to SUDEP. J Clin Neurophysiol. Abstract: Sudden Unexpected Death in Epilepsy Is Likely Caused by a Cascade of Events Affecting the Vegetative Nervous System Leading to Cardiorespiratory Failure and Death, 1(1), 21– 29.Boyd, D. M., & Ellison, N. B. (2007). Social Network Sites: Definition, History, and Scholarship. Journal of Computer-Mediated Communication, 13, 210–230.Cerf, V. G., & Kahn, R. E. (1974). A protocol for packet network intercommunication. IEEE Transactions on Communications, 22(5), 637–648.Chekhmane, G., & Benali, R. (2022). EEG signals analysis using SVM and MLPNN classifiers for epilepsy detection. 2022 5th International Symposium on Informatics and Its Applications (ISIA), 1–6. https://doi.org/10.1109/ISIA55826.2022.9993577Eggleston, K. S., Olin, B. D., & Fisher, R. S. (2014a). Ictal tachycardia: The head-heart connection. Seizure, 23(7), 496–505. https://doi.org/10.1016/j.seizure.2014.02.012Evans, D. (2011). The Internet of Things: How the Next Evolution of the Internet Is Changing Everything.Fisher, R. S., Cross, J. H., French, J. A., Higurashi, N., Hirsch, E., Jansen, F. E., Lagae, L., Moshé, S. L., Peltola, J., Roulet Perez, E., Scheffer, I. E., & Zuberi, S. M. (2017). Operational classification of seizure types by the International League Against Epilepsy: Position Paper of the ILAE Commission for Classification and Terminology. Epilepsia, 58(4), 522–530. https://doi.org/10.1111/epi.13670Fisher, R. S., Van Emde Boas, W., Blume, W., Elger, C., Genton, P., Lee, P., & Engel, J. (2005). Epileptic seizures and epilepsy: Definitions proposed by the International League Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE). Epilepsia, 46(4), 470–472. https://doi.org/10.1111/j.0013-9580.2005.66104.xFujiwara, K., Miyajima, M., Yamakawa, T., Abe, E., Suzuki, Y., Sawada, Y., Kano, M., Maehara, T., Ohta, K., Sasai-Sakuma, T., Sasano, T., Matsuura, M., & Matsushima, E. (2016a). Epileptic Seizure Prediction Based on Multivariate Statistical Process Control of Heart Rate Variability Features. IEEE Transactions on Biomedical Engineering, 63(6), 1321–1332. https://doi.org/10.1109/TBME.2015.2512276Giannakakis, G., Tsiknakis, M., & Vorgia, P. (2019). Computer Methods and Programs in Biomedicine Focal epileptic seizures anticipation based on patterns of heart rate variability parameters. 178, 123–133. https://doi.org/10.1016/j.cmpb.2019.05.032González, D. R. (2013). Arquitectura y Gestión de la IoT IoT Network Management / Abstract. Revista Telem@tica, 12(3), 49–60.Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29, 1645–1660.Hampel, K. G., Rocamora Zuñiga, R., & Quesada, C. M. (2016). Unravelling the mysteries of sudden unexpected death in epilepsy. Neurologia. https://doi.org/10.1016/j.nrl.2017.02.004Jansen, K., Varon, C., Van Huffel, S., & Lagae, L. (2013a). Peri-ictal ECG changes in childhood epilepsy: Implications for detection systems. Epilepsy and Behavior, 29(1), 72–76. https://doi.org/10.1016/j.yebeh.2013.06.030Lasefr, Z., Reddy, R. R., & Elleithy, K. (2017). Smart Phone Application Development for Monitoring Epilepsy Seizure Detection based on EEG signal Classification. 2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON), 83–87.Leach, J. P., Stephen, L. J., Salveta, C., & Brodie, M. J. (2006a). Which electroencephalography (EEG) for epilepsy? The relative usefulness of different EEG protocols in patients with possible epilepsy. Journal of Neurology, Neurosurgery and Psychiatry, 77(9), 1040–1042. https://doi.org/10.1136/jnnp.2005.084871Lee, T. M. C., & Chan, J. K. P. (2002). Factores que afectan el estado cognitivo de personas que sufren epilepsia. Departamento de Psicología. Universidad de Hong Kong. Hong Kong, 34(9), 861–865.Leiner, B. M., Cerf, V. G., Clark, D. D., Kahn, R. E., Kleinrock, L., Lynch, D. C., Postel, J., Roberts, L. G., & Wolff, S. (2009). A brief history of the Internet. ACM SIGCOMM Computer Communication Review, 39(5), 22–31.López, M. (2019). Internet de las cosas La transformación digital de la sociedad. In de Internet de las cosas La transformación digital de la sociedad, Madrid, Ra-Ma.Lytton, W. W. (2008). Computer modelling of epilepsy. Nature Reviews Neuroscience, 9(8), 626–637.Malik, M. (1996). Heart Rate Variability: Standards of Measurement, Physiological Interpretation, and Clinical Use Task Force of The European Society of Cardiology and the North American Society for Pacing and Electrophysiology. https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1542-474X.1996.tb00275.xMegiddo, I., Colson, A., Chisholm, D., Dua, T., Nandi, A., & Laxminarayan, R. (2016). Health and economic benefits of public financing of epilepsy treatment in India: An agent- based simulation model. Epilepsia, 57(3), 464–474. https://doi.org/10.1111/epi.13294Ministerio de Salud y Protección Social. (2017, February 13). Epilepsia: mucho más que convulsiones.Miraz, M. H., Ali, M., Excell, P. S., & Picking, R. (2015). A Review on Internet of Things (loT), Internet of Everything (IoE) and Internet ofNano Things (IoNT). Internet Technologies and Applications (ITA).Moridani, M. K., & Farhadi, H. (2017). Heart rate variability as a biomarker for epilepsy seizure prediction. Bratislava Medical Journal, 118(1). https://doi.org/10.4149/BLL_2017_001Nagai, Y., Goldstein, L. H., Fenwick, P. B. C., & Trimble, M. R. (2004). Clinical efficacy of galvanic skin response biofeedback training in reducing seizures in adult epilepsy: A preliminary randomized controlled study. Epilepsy and Behavior, 5(2), 216–223. https://doi.org/10.1016/j.yebeh.2003.12.003Nagai, Y., Jones, C. I., & Sen, A. (2019). Galvanic Skin Response (GSR)/Electrodermal/Skin Conductance Biofeedback on Epilepsy: A Systematic Review and Meta-Analysis. In Frontiers in Neurology (Vol. 10). Frontiers Media S.A. https://doi.org/10.3389/fneur.2019.00377Nguyen Thi Anh-Dao, Tran Duc-Nghia, Nguyen Thi-Hao, Tran Duc-Tan, Nguyen Linh- Trung, IEEE Communications Society, International Conference on Advanced Technologies for Communications 6 2013.10.16-18 Ho Chi Minh City, & ATC 6 2013.10.16-18 Ho Chi Minh City. (2013). An Effective Procedure for Reducing EOG and EMG Artefacts from EEG Signals. International Conference on Advanced Technologies for CommunicationsOrganización Mundial de la Salud (OMS). (2023, February 9). Epilepsia. https://www.who.int/es/news-room/fact-sheets/detail/epilepsyPatel, S., Mancinelli, C., Dalton, A., Patritti, B., Pang, T., Schachter, S., & Bonato, P. (2009). Detecting epileptic seizures using wearable sensors. Bioengineering, Proceedings of the Northeast Conference, 4–5. https://doi.org/10.1109/NEBC.2009.4967771Rajaguru, H. (2017). EEG features for Epilepsy Detection. Iccmc, 981–984.Ray, A., Tao, J. X., Hawes-Ebersole, S. M., & Ebersole, J. S. (2007a). Localizing value of scalp EEG spikes: A simultaneous scalp and intracranial study. Clinical Neurophysiology, 118(1), 69–79. https://doi.org/10.1016/j.clinph.2006.09.010Rushalina, D., Wisana, I. D. G. H., Nugraha, P. C., & Ragimova, N. (2022). Analysis of Transmitted and Received ECG Signal Based on Internet of Thing Using Web Browser and Server-Client HTML Protocol. Jurnal Teknokes, 15(4). https://doi.org/10.35882/teknokes.v15i4.469Singh, B., Bhattacharya, S., Chowdhary, C. L., & Jat, D. S. (2017a). A review on internet of things and its applications in healthcare. Journal of Chemical and Pharmaceutical Sciences, 10(1), 447–452.Smith, A. (2011). Smartphone Adoption and Usage. Pew Internet & American Life Project.Sundmaeker, H., Guillemin, P., Friess, P., & Woelfflé, S. (2010). Vision and Challenges for Realising the Internet of Things. http://europa.eu/information_societyTatum, W. O., Rubboli, G., Kaplan, P. W., Mirsatari, S. M., Radhakrishnan, K., Gloss, D., Caboclo, L. O., Drislane, F. W., Koutroumanidis, M., Schomer, D. L., Kastelijn-Nolst Trenite, D., Cook, M., & Beniczky, S. (2018). Clinical utility of EEG in diagnosing and monitoring epilepsy in adults. Clinical Neurophysiology, 129, 1056–1082. https://doi.org/10.1016/j.clinph.2018.01.019Thara, D. K., Premasudha, B. G., & Krivic, S. (n.d.). Detection of epileptic seizure events using pre-trained convolutional neural network, VGGNet and ResNet. Expert Systems, n/a(n/a), e13447. https://doi.org/https://doi.org/10.1111/exsy.13447Vergara, P. M., De La Cal, E., Villar, J. R., González, V. M., & Sedano, J. (2017a). An IoT Platform for Epilepsy Monitoring and Supervising. Journal of Sensors, 2017. https://doi.org/10.1155/2017/6043069Wagle, S. (2016). Semantic data extraction over MQTT for IoTcentric wireless sensor networks. 2016 International Conference on Internet of Things and Applications (IOTA), 227–232. https://doi.org/10.1109/IOTA.2016.7562727Watthanawisuth, N., Maturos, T., Sappat, A., & Tuantranont, A. (2015). The IoT wearable stretch sensor using 3D-Graphene foam. 2015 IEEE SENSORS - Proceedings, 3–6. https://doi.org/10.1109/ICSENS.2015.7370275What is ICANN? (2020). ICANN. https://www.icann.org/resources/pages/what-2012-02-25- enWu, M., Lu, T.-J., Ling, F.-Y., Sun, J., & Du, H.-Y. (2010). Research on the architecture of Internet of Things. 2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE), 5, V5-484-V5-487. https://doi.org/10.1109/ICACTE.2010.5579493Yamakawa, T., Miyajima, M., Fujiwara, K., Kano, M., Suzuki, Y., Watanabe, Y., Watanabe, S., Hoshida, T., Inaji, M., & Maehara, T. (2020). Wearable epileptic seizure prediction system with machine-learning-based anomaly detection of heart rate variability. Sensors (Switzerland), 20(14), 1–16. https://doi.org/10.3390/s20143987Zapata Barco, A. M., Restrepo-Martínez, M., & Restrepo, D. (2020). Depression in People with Epilepsy. What is the Connection? In Revista Colombiana de Psiquiatria (Vol. 49, Issue 1, pp. 53–61). 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