Epilepsy wearables must detect pre-seizure EEG patterns in 50ms, not 2 seconds

Wearable EEG monitors for epilepsy patients can detect pre-ictal brainwave patterns 30-90 seconds before a seizure, but only if the classification happens within 50ms of each EEG sample -- slow enough to miss the pattern and the patient falls without warning, potentially into traffic or down stairs. Cloud-based seizure detection adds 1-3 seconds of latency per inference, which collapses the detection window and produces alerts after the seizure has already begun, making them useless for fall prevention. The deeper issue is that patients wear these devices 24/7 in locations with unreliable connectivity -- subway commutes, rural areas, airplane flights -- where a cloud API call may not complete at all. A sub-1W edge chip running a quantized Gemma model processes each 50ms EEG window on-device, maintaining continuous seizure surveillance regardless of connectivity, and the data never leaves the wearable, preserving medical privacy without HIPAA-compliant cloud infrastructure.