Epilert: Epilepsy Tracker and Detector

Year : 2025 | Volume : 12 | Issue : 01 | Page : 1 8
    By

    Leora Dias,

  • Samuel Dsouza,

  • Reuben Fernandes,

  • Joshua Michael,

  1. Student, Department of Computer Engineering, Fr. Conceicao Rodrigues COE, Fr. Agnel Ashram, Bandra West, Mumbai, Maharashtra, India
  2. Student, Department of Computer Engineering, Fr. Conceicao Rodrigues COE, Fr. Agnel Ashram, Bandra West, Mumbai, Maharashtra, India
  3. Student, Department of Computer Engineering, Fr. Conceicao Rodrigues COE, Fr. Agnel Ashram, Bandra West, Mumbai, Maharashtra, India
  4. Student, Department of Computer Engineering, Fr. Conceicao Rodrigues COE, Fr. Agnel Ashram, Bandra West, Mumbai, Maharashtra, India

Abstract

Epilepsy, affecting over 50 million individuals worldwide, necessitates innovative solutions for effective monitoring and intervention. Current systems face challenges such as inaccuracy, limited accessibility, and discomfort, leaving patients and caregivers vulnerable. Epilert, a wearable device, addresses these gaps by employing advanced sensors and machine-learning algorithms for real-time epilepsy detection and monitoring. The device integrates electromyography (EMG) and motion sensors to capture and analyze physiological and movement data. Preprocessing techniques ensure noise-free signals, while a 5-layer Convolutional Neural Network (CNN) identifies seizure patterns with high precision. Dual-modality detection reduces false positives by cross-verifying muscle activity and abnormal movements. Real-time alerts and notifications to caregivers enhance timely interventions, improving patient safety. Epilert’s mobile application complements the wearable device, providing a user-friendly interface for data visualization, customization, and secure cloud-based storage. The collected data enables long-term tracking and facilitates personalized treatment planning. The system achieves 96.5% accuracy in seizure detection, validated through robust testing methods, demonstrating its reliability and efficacy. Future developments include enhanced personalization through additional biomarkers and advanced AI models, improved wearable design for accessibility, and regulatory certifications to ensure safety and widespread adoption. By addressing the limitations of existing systems, Epilert revolutionizes epilepsy care, combining technological innovation with compassionate patient support to improve the quality of life for individuals with epilepsy and their families.

Keywords: Epilepsy, electromyography, mobile application, Convolutional Neural Network

[This article belongs to Recent Trends in Sensor Research & Technology ]

How to cite this article:
Leora Dias, Samuel Dsouza, Reuben Fernandes, Joshua Michael. Epilert: Epilepsy Tracker and Detector. Recent Trends in Sensor Research & Technology. 2025; 12(01):1-8.
How to cite this URL:
Leora Dias, Samuel Dsouza, Reuben Fernandes, Joshua Michael. Epilert: Epilepsy Tracker and Detector. Recent Trends in Sensor Research & Technology. 2025; 12(01):1-8. Available from: https://journals.stmjournals.com/rtsrt/article=2025/view=195044


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Regular Issue Subscription Review Article
Volume 12
Issue 01
Received 14/01/2025
Accepted 20/01/2025
Published 24/01/2025
Publication Time 10 Days
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