Connecting CPAP patients and their doctors through continuous data and AI. Clinical-grade biosensors embedded in the mask you already wear, delivering nightly insights that improve therapy and sleep quality.
10 million Americans use CPAP, yet their machines only track airflow and leak. Roya turns the mask into a comprehensive sleep monitor, giving patients nightly insights and giving doctors continuous, actionable data to improve therapy outcomes.
AI-powered analysis enables Remote Patient Monitoring (RPM) billing under existing CMS codes. Sleep practices gain a new recurring revenue stream. Patients get better care without extra devices, extra visits, or out-of-pocket cost.
CPAP machines track airflow and mask leak, but not the patient. Clinicians have no visibility into oxygen desaturation, arousal burden, or how sleep architecture is changing night to night.
Patients sleep alone with no feedback loop. Doctors wait months between visits to learn therapy is failing. The data that could bridge this gap simply is not being collected.
Asking a CPAP user to add a ring, wristband, or headband creates friction. Adherence to extra wearables drops within months, leaving gaps in the data clinicians need most.
Consumer sleep trackers lock data in consumer apps. Without physician access and standardized clinical formats, there is no pathway to RPM billing or insurance coverage.
Embedded Biosensors — PPG, accelerometer, and temperature sensors in the mask frame. SpO2, HR, HRV, body position, and skin temperature collected passively every night.
AI Sleep Analysis — Cloud-based deep learning performs sleep staging, arousal detection, and respiratory event classification, connecting raw data to clinical insight.
Doctor-Patient Data Bridge — A clinician dashboard delivers longitudinal data in standardized formats, enabling RPM workflows and reimbursement while keeping doctors in the loop between visits.
AI Sleep Coach — Patient-facing LLM app translates nightly data into personalized, plain-language guidance that improves engagement and therapy adherence.
The building blocks behind the Smart CPAP Mask platform.
Medical-grade PPG sensor, multi-axis accelerometer, and temperature sensor. Low-power BLE 5.0 streams data to a companion app. Designed for nasal pillow and cradle mask form factors.
Deep learning models for automated sleep staging, respiratory event detection, and arousal scoring from PPG-derived signals. Validated against polysomnography datasets.
Physician-facing Medical Summary Output (MSO) generates clinical summaries. Patient-facing AI coach translates complex sleep metrics into actionable personal guidance.
End-to-end encryption, HIPAA-compliant cloud, role-based access, audit logging, and BAA-ready architecture from day one.
Bridging consumer sleep trackers and clinical-grade monitoring in one device.
| Capability |  SMART MASK |
 STANDARD CPAP |
 CONSUMER TRACKERS |
|---|---|---|---|
| Sleep Stage Tracking | ✓ AI-powered | ✗ | ~ Limited |
| Arousal Detection | ✓ Clinical-grade | ✗ | ✗ |
| SpO2 Monitoring | ✓ Continuous | ✗ | ~ Spot / wrist |
| HR / HRV Tracking | ✓ PPG-based | ✗ | ✓ |
| FDA Clearance Path | ✓ 510(k) | ✓ Mask only | ~ Wellness |
| Nothing Extra to Wear | ✓ Built-in | ✓ | ✗ Ring/band |
| Physician Data Access | ✓ Dashboard+RPM | ~ Compliance | ✗ Consumer |
| Insurance Reimbursement | ✓ RPM codes | ✓ DME | ✗ OOP |
Working 3D-printed prototype with embedded biosensors producing clean PPG signals.
Signal quality validation using clinical-grade reference devices across parameters and wear conditions.
Deep learning training on PSG-correlated datasets for sleep staging, arousal detection, and event classification.
Formal oxygen saturation accuracy validation at an accredited clinical laboratory.
Multi-site polysomnography clinical study validating AI against gold-standard scored PSG data.
FDA 510(k) submission for physiological data collection and AI-assisted sleep analysis.
Whether you run a sleep lab, invest in medtech, or are interested in connected CPAP therapy, we would love to hear from you.