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IoT-Enabled Early Prediction System for Epileptic Seizure in Human Being

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Soft Computing: Theories and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1154))

Abstract

The paper reports a hardware-based system for the prediction of epilepsy in the human subject under test. EEG signals from the dataset are analyzed to predict epilepsy status. The EEG signal database is analyzed with the help of support vector machine and thresholding to classify the human subject under test as normal or else. The reported technique is very simple and demonstrates a reasonable agreement with the existing methodologies.

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Acknowledgements

This work is partially funded by the “IoT-Based Consumer Behaviour Analytics Project” by DigitalDojo Pvt. Ltd. Mumbai-India.

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Authors and Affiliations

  1. Department of E&TC Engineering, Dr. Babasaheb Ambedkar Technological University, Lonere, 402103, India

    Sayali Shinde & Brijesh Iyer

Authors
  1. Sayali Shinde
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  2. Brijesh Iyer
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Corresponding author

Correspondence to Brijesh Iyer .

Editor information

Editors and Affiliations

  1. Department of Paper Technology, IIT Roorkee, Roorkee, India

    Millie Pant

  2. Graphic Era Hill University, Dehradun, Uttarakhand, India

    Tarun Kumar Sharma

  3. NIT Patna, Patna, India

    Rajeev Arya

  4. NIT Patna, Patna, India

    B.C. Sahana

  5. Ryerson University, Toronto, ON, Canada

    Hossein Zolfagharinia

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Shinde, S., Iyer, B. (2020). IoT-Enabled Early Prediction System for Epileptic Seizure in Human Being. In: Pant, M., Kumar Sharma, T., Arya, R., Sahana, B., Zolfagharinia, H. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol 1154. Springer, Singapore. https://doi.org/10.1007/978-981-15-4032-5_5

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