Cardiac intelligence that acts when you can't.
An open-source platform that combines wearable biosensors, artificial intelligence, and satellite communication to detect cardiac arrest and alert emergency services autonomously — even in areas with zero cell coverage.
The Problem
Half are unwitnessed — nobody calls 911.
Every second counts. Most victims have minutes, not hours.
Existing devices detect arrest but can't call for help in remote areas.
The Solution
6 wearable biosensors monitoring heart rate, SpO2, ECG, skin temperature, respiration, and movement simultaneously.
On-device AI learns your personal cardiac baseline over 24-48 hours. Detects 19 clinical conditions in real time.
If cardiac arrest detected: 20-second cancel window → auto-transmits GPS + vitals via satellite from 40+ miles away.
Capabilities
Heart rate, SpO2, ECG, temperature, respiration, and accelerometer analyzed through a multi-factor engine with personal baseline learning.
Multi-factor death confidence scoring combining pulse absence, movement cessation, temperature decline, oxygen loss, and respiratory failure — up to 99% confidence.
Detects deteriorating trends 30 seconds before critical events. Identifies dangerous tachy-brady sequences that precede arrest.
256-byte emergency packet with GPS, vitals, AI status, and event timeline transmitted via satellite or LoRa when the wearer can't respond.
Single base station monitors 50+ people simultaneously with independent AI engines per person. Auto-triage sorts by severity.
Every state transition logged with full sensor context for first responders. Complete event history from onset to alert.
AI Detection
Real-time monitoring across critical, high, and moderate severity levels.
Critical
High
Moderate
Use Cases
Monitor lost hikers from base camp with real-time vitals and GPS.
Oil rigs, mines, forestry, fishing boats — anywhere cell towers don't reach.
Solo seniors in rural areas without cell coverage get autonomous protection.
Mountaineering, polar, and desert teams with satellite-linked cardiac monitoring.
Monitor entire team, auto-alert if someone goes down in the field.
When cell towers are destroyed, RESQ keeps transmitting via satellite.
Specs
| Sensors | PPG, ECG, temperature, accelerometer, gyroscope, respiration |
| AI | Personal baseline learning, sequence pattern detection, RMSSD rhythm analysis, Z-score anomaly detection |
| Transmission | LoRa SX1276 915MHz SF12 (40+ mi), Satellite SOS, Cellular fallback |
| SOS Packet | 256 bytes (GPS + vitals + AI status + timeline) |
| Battery | 2-4 days continuous monitoring |
| Base Station | Raspberry Pi 4 + LoRa receiver |
| Fleet | 50+ simultaneous patients |
| Wearable Cost | ~$28 in components |
| License | MIT open source |
Origin
In April 2026, the CIA reportedly deployed a classified system called Ghost Murmur to detect a downed airman's heartbeat from 40 miles away. Whether real or disinformation, it revealed a truth:
This capability shouldn't only exist behind classified walls.
RESQ is the civilian answer — open source, under $100, for everyone. Because the technology to save lives in remote areas shouldn't require a security clearance.
RESQ is a prototype for research and development. Not a medical device.
An IronGate Studios project by Jonathan Colon
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