Nocturnal Seizure Detection Using Off-the-Shelf WiFi

The detection of nocturnal seizures in epilepsy patients is essential, both for the quick management seizure complications, and assessment ongoing treatment. Traditional products (e.g., wearables), however, are either very costly, uncomfortable, or unreliable. In this article, we then propose to utilize everyday WiFi signals robust, fast, noninvasive seizures. We first present a new rigorous mathematical characterization spectral content/bandwidth signal, measured on device placed near sleeping patient, during different kinds sleep motions: seizures, normal movements posture adjustments), breathing. Based modeling, novel pipeline processing received robustly detect all nonbreathing movements, classify them into body order validate this, carry out extensive experiments seven typical bedroom locations, where set 20 actors simulate state having (a total 260 instances), as well 410 instances). Our proposed system detects 93.85% with mean response time (MRT) only 5.69 s since onset seizure. Moreover, our achieves probability false alarm 0.0097, when classifying movements. Overall, modeling experimental results show great potential ubiquitous have detecting which can provide better support their caregivers.