EonFlow provides real‑time central bio‑electrical monitoring for high‑risk industries, replacing annual exams and consumer wearables with chest‑mounted ECG sensors that work in extreme cold and altitude. Its EonPredict system validates fatigue and cognitive fitness in under 30 seconds, automatically blocking unsafe personnel and integrating results into HL7 FHIR R5 health records.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional occupational health exams and consumer wearables cannot reliably monitor fatigue and cardiovascular health in extreme cold and high‑altitude mining environments because peripheral optical sensors fail due to vasoconstriction and increased blood viscosity.
Solution
EonFlow replaces periodic medical exams and wrist‑based wearables with a central, real‑time bioelectrical monitoring platform that captures ECG signals directly from the thorax using dry‑contact sensors. The system validates an operator’s fatigue and health status in under 30 seconds and automatically blocks RFID‑controlled access points for personnel who do not meet safety thresholds. Data are transmitted to a cloud service that applies edge AI and predictive analytics, then integrates the results into HL7 FHIR R5 electronic health records for immediate clinical review. The platform also offers a home‑based rehabilitation module that guides users through nasal breathing and masticatory exercises to reduce chronic fatigue and improve sleep quality. By providing continuous, climate‑resilient monitoring, EonFlow enables proactive fatigue management and remote health support for high‑risk workers and their families.
Target Audience
Primary customers are safety and health managers in high‑risk industries such as mining, heavy equipment operation, and remote industrial sites, as well as occupational health clinics that need real‑time fatigue screening for their workforce.
Features
- Dry‑contact thoracic ECG sensors that operate reliably below –10 °C and up to 3,800 m above sea level
- 30‑second pre‑shift biological and cognitive fatigue assessment with immutable RFID/turnstile access blocking
- Edge AI algorithms that extract HRV (RMSSD) and detect latent arrhythmias, sympathetic collapse, and extreme fatigue
- Native HL7 FHIR R5 integration for instant update of electronic health records and compliance reporting
- Cloud‑hosted analytics pipeline providing predictive fatigue scores and alerts for safety managers
- EonHome module delivering guided respiratory and masticatory exercises for longitudinal health rehabilitation
- OEM‑agnostic hardware architecture that requires no additional capital expenditure for sensor deployment