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351.#.#.b: Journal of Applied Research and Technology

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856.4.0.u: http://jart.icat.unam.mx/index.php/jart/article/view/1085/771

100.1.#.a: Jeyabharathi, D.; Kesavaraja, D.; Sasirekac, D.

524.#.#.a: Jeyabharathi, D., et al. (2020). iEpilepsy monitoring and alerting system using machine learning algorithm and WHMS. Journal of Applied Research and Technology; Vol 18 No 3, 2020. Recuperado de https://repositorio.unam.mx/contenidos/4110247

245.1.0.a: iEpilepsy monitoring and alerting system using machine learning algorithm and WHMS

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Instituto de Ciencias Aplicadas y Tecnología, UNAM

264.#.0.c: 2020

264.#.1.c: 2020-06-26

506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY 4.0 Internacional, https://creativecommons.org/licenses/by/4.0/legalcode.es, fecha de asignación de la licencia 2020-06-26, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico revistas@unam.mx

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520.3.#.a: Advances in wireless electronics devices have led to easy design and develop of wearable sensor systems for health monitoring. These wireless sensors have been considered as one of the most important technologies that can change the future and has garnered lots of attention in the scientific community and the industry during the last years. These devices consist of small battery with limited computation and radio communication capabilities. These wireless sensor systems has become essential in such domains as industrial operations, health care, environmental infrastructure and research and development. Accelerometer sensor added with these wireless devices value to automatically detect seizures in temporal lobe epilepsy patients. The accelerometer sensor that is used in the wireless device is used to calculate the vibration threshold developed in the body. After calculating the threshold with various thresholds factors that has occurred in the body using seizure detection algorithm the device sends alerts to emergency contacts. In the future, we’ll see the mixing of a huge array of wireless networks into existing specialised medical technology. The aim of this paper is not to criticize, but to serve as a reference for researchers and developers in this scientific area and to provide direction for future research improvements.

773.1.#.t: Journal of Applied Research and Technology; Vol 18 No 3 (2020)

773.1.#.o: http://jart.icat.unam.mx/index.php/jart

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264.#.1.b: Instituto de Ciencias Aplicadas y Tecnología, UNAM

758.#.#.1: http://jart.icat.unam.mx/index.php/jart

doi: https://doi.org/10.22201/icat.24486736e.2020.18.3.1085

handle: 00e68947a558f721

harvesting_date: 2021-03-08 00:00:00.0

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Artículo

iEpilepsy monitoring and alerting system using machine learning algorithm and WHMS

Jeyabharathi, D.; Kesavaraja, D.; Sasirekac, D.

Instituto de Ciencias Aplicadas y Tecnología, UNAM, publicado en Journal of Applied Research and Technology, y cosechado de Revistas UNAM

Licencia de uso

Procedencia del contenido

Cita

Jeyabharathi, D., et al. (2020). iEpilepsy monitoring and alerting system using machine learning algorithm and WHMS. Journal of Applied Research and Technology; Vol 18 No 3, 2020. Recuperado de https://repositorio.unam.mx/contenidos/4110247

Descripción del recurso

Autor(es)
Jeyabharathi, D.; Kesavaraja, D.; Sasirekac, D.
Tipo
Artículo de Investigación
Área del conocimiento
Ingenierías
Título
iEpilepsy monitoring and alerting system using machine learning algorithm and WHMS
Fecha
2020-06-26
Resumen
Advances in wireless electronics devices have led to easy design and develop of wearable sensor systems for health monitoring. These wireless sensors have been considered as one of the most important technologies that can change the future and has garnered lots of attention in the scientific community and the industry during the last years. These devices consist of small battery with limited computation and radio communication capabilities. These wireless sensor systems has become essential in such domains as industrial operations, health care, environmental infrastructure and research and development. Accelerometer sensor added with these wireless devices value to automatically detect seizures in temporal lobe epilepsy patients. The accelerometer sensor that is used in the wireless device is used to calculate the vibration threshold developed in the body. After calculating the threshold with various thresholds factors that has occurred in the body using seizure detection algorithm the device sends alerts to emergency contacts. In the future, we’ll see the mixing of a huge array of wireless networks into existing specialised medical technology. The aim of this paper is not to criticize, but to serve as a reference for researchers and developers in this scientific area and to provide direction for future research improvements.
Idioma
eng
ISSN
ISSN electrónico: 2448-6736; ISSN: 1665-6423

Enlaces