Virtual Booth

Epilepsy is a chronic neurological disorder marked by unpredictable seizures affecting millions worldwide. Traditional management relies on clinical visits and patient-reported seizure logs, often delayed or inaccurate, reducing timely intervention and patient safety. Wearable sensors and mobile-health platforms offer continuous, real-time monitoring and insights. Current systems face low detection accuracy, user discomfort, high false alarms, and integration challenges. This study develops a SmartHealth Care system called EpiWatch which it combining wearable sensors, a mobile app, and cloud analytics, evaluates seizure-detection performance, assesses usability, and examines effects on medication adherence and overall safety.

Methodology

A mixed-methods design was employed with a four-week pilot trial. Participants were recruited via purposive sampling from a neurology clinic. The system included a wearable sensor for physiological signals, a mobile app for alerts, and cloud-based analytics. Data included sensor readings, alert timestamps, and clinically confirmed seizures. Usability was evaluated via questionnaires. Quantitative analysis computed detection accuracy, sensitivity, specificity, and false alarms. Limitations include the small sample and short monitoring period.

EpiWatch worked well overall. It detected seizures accurately, sent alerts quickly, and users were happy with it. The results show it can help make epilepsy monitoring safer and more reliable.

Conclusion

The EpiWatch system provides reliable seizure detection, timely alerts, and strong user acceptance. It addresses gaps in traditional epilepsy care, enhancing safety and quality of life. Future work should expand to larger populations, longer trials, and personalized algorithms.

References

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[3]Varghese A, Menon V, Zahid U, et al. Mobile health applications across neurological disorders: design considerations and clinical potential. Neurology. 2021;97(9):e908–e920.

[4]Dorsey ER, Papapetropoulos S, Pillai L, et al. The rise of digital health in neurology. The Lancet Neurology. 2018;17(5):465–475.