Epilepsy Seizure Detection and Prediction Based on Device Hive
K. Nanthini1, T. Kavitha2, D. Sivabalaselvamani3, M. Pyingkodi4, Gourav Kumar5
1K. Nanthini, Assistant Professor, Department of Computer Applications, Kongu Engineering College, Tamilnadu, India.
2T. Kavitha, Assistant Professor, Department of Computer Applications, Kongu Engineering College, Tamilnadu, India.
3Dr. D. Sivabalaselvamani , Assistant Professor, Department of Computer Applications, Kongu Engineering College, Tamilnadu, India.
4M. Pyingkodi, Assistant Professor, Department of Computer Applications, Kongu Engineering College, Tamilnadu, India.
5Gourav Kumar, PG Student, Department of Computer Applications, Kongu Engineering College, Tamilnadu, India.

Manuscript received on November 20, 2019. | Revised Manuscript received on November 28, 2019. | Manuscript published on 30 November, 2019. | PP: 7463-7466 | Volume-8 Issue-4, November 2019. | Retrieval Number: D5320118419/2019©BEIESP | DOI: 10.35940/ijrte.D5320.118419

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Unpredictable nature of epilepsy, patients only has more need of awareness about precautions and how to handle the occurrence. Epilepsy belongs to have a recurrent seizures tendency throughout the life. Seizure may happen due to number of reasons like tumor, head injury, pregnancy time, genetic etc. It can be curable with proper diagnosis, incurable but controllable with lifelong medication and remaining are uncontrollable that leads to death. Recording of alert symptoms like auras, prodromes and precipitant factors are helped to self-alert the patient, create positive impact on quality of life and increase the efficacy of treatments. The need of enhancing early seizure detection and developing wearable monitoring product with low cost is used to create fear free environment among the affected people. In this connection, my proposed work reviewed on existing and currently available IOT based seizure detection and alert systems feasibility.
Keywords: Epileptic Seizure, Seizure Detection, Seizure Alert, IOT, IONT
Scope of the Article: Regression and Prediction.