Core technology
Reading the autonomic signal, continuously.
A small sensor listens to your heartbeat, and our research looks for patterns in it that relate to seizure activity. Everything below explains how, one step at a time.
How it works
From heartbeat to insight, in four steps.
1. Wear
A chest patch reads the heartbeat continuously.
2. Measure
HRV patterns are studied against a research model.
3. Detect
Notable patterns are surfaced for review.
4. Notify
The patient sees it on the app.
Our framework
The Quadruple Speciality is S.A.F.E.
Four disciplines, one acronym. Tap each letter to see what it means.
In short: a small patch listens to your heartbeat, all day.
Worn on the chest, it’s built for continuous, precision-focused capture — always listening, so nothing about the signal is missed between visits.
In short: your heartbeat’s rhythm is a window into your nervous system.
We study Heart Rate Variability (HRV) — the subtle beat-to-beat variation in heart rhythm. It’s controlled by the same nerves that respond during a seizure, so changes in that rhythm can reflect what’s happening in the nervous system.
By studying HRV across many states — rest, activity, sleep, and the periods around seizures — we’re researching patterns that may help tell ordinary variability apart from seizure-related activity.
No. A standard heart-rate monitor counts beats per minute. HRV looks at the tiny differences in time between beats — a much finer signal that reflects nervous-system activity, not just how fast the heart is beating.
Seizures involve the autonomic nervous system, which also governs heart rhythm. That makes the heartbeat a continuously wearable, comfortable signal — without needing electrodes on the scalp.
Patients and caregivers who live with unpredictable seizures, clinicians and researchers studying autonomic biomarkers, and partners evaluating where this research is headed.
In short: the aim is to see it coming, so there’s time to act.
Rather than only recording what has already happened, our research is directed at anticipation — studying whether HRV patterns can indicate a seizure ahead of time, creating the minutes a person needs to reach safety, sit down, or call someone.
That predictive direction is what we are working toward, grounded in ongoing research rather than promised outcomes.
Research in progress
We’re not claiming a finished predictive product — this is where our ongoing clinical research is headed.
In short: you and your caregiver see it first, on your phone.
The companion app puts the data — and ultimately the decision — in the patient’s hands, with the option to share trends with a trusted caregiver.
See the app
Visit the Product page for the full companion-app walkthrough.
Academic foundation
Built on peer-reviewed evidence.
Our core technologies — AI informatics and biomedical sensors — trace back to research at Kyoto University and Kumamoto University, and we continue collaborative research with specialist facilities nationwide.
2020Wearable Epileptic Seizure Prediction System with Machine-Learning-Based Anomaly Detection of Heart Rate VariabilityYamakawa T. et al. · Sensors (Basel) · 20(14):3987 · PMID 32709064 View 2016Epileptic Seizure Prediction Based on Multivariate Statistical Process Control of Heart Rate Variability FeaturesFujiwara K. et al. · IEEE Trans Biomed Eng · 63(6):1321-32 · PMID 26841385 View