Resumen

JEYABHARATHI, D.; KESAVARAJA, D.  y  SASIREKAC, D.. iEpilepsy monitoring and alerting system using machine learning algorithm and WHMS. J. appl. res. technol [online]. 2020, vol.18, n.3, pp.154-160.  Epub 30-Jul-2021. ISSN 2448-6736.  https://doi.org/10.22201/icat.24486736e.2020.18.3.1085.

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.

Palabras llave : detection; home monitoring; wearables; accelerometer; sensors; wireless devices.

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