Elfi-Tech
Elfi-Tech is dedicated to developing non-invasive blood flow monitoring solutions for in-hospital, clinical research, and home care. Their innovative technology utilizes miniaturized dynamic light scattering (mDLS) to provide continuous, versatile, and accurate physiological parameter measurements, aiming to improve patient outcomes and reduce healthcare costs.
Industries
Nr. of Employees
small (1-50)
Products
Miniaturized non‑invasive peripheral flow sensor (dynamic light scattering based)
A compact optical sensor that measures blood flow and derived hemodynamic indices continuously; designed for placement at multiple body sites and integration into wearable or implantable form‑factors.
Analytical software and ML platform for hemodynamic data
Software algorithms and machine‑learning models for processing optical sensor data to produce predictive analytics, alerts and clinical decision support.
Miniaturized non‑invasive peripheral flow sensor (dynamic light scattering based)
A compact optical sensor that measures blood flow and derived hemodynamic indices continuously; designed for placement at multiple body sites and integration into wearable or implantable form‑factors.
Analytical software and ML platform for hemodynamic data
Software algorithms and machine‑learning models for processing optical sensor data to produce predictive analytics, alerts and clinical decision support.
Services
Clinical validation and trial deployment
Support for clinical studies and validation of non‑invasive hemodynamic measurements across multiple clinical sites, producing peer‑reviewed publications and trial data.
Machine‑learning analytics and alerting
Development and deployment of machine‑learning models for real‑time hemodynamic analytics, risk prediction, alarm optimization and personalized treatment suggestions.
Clinical validation and trial deployment
Support for clinical studies and validation of non‑invasive hemodynamic measurements across multiple clinical sites, producing peer‑reviewed publications and trial data.
Machine‑learning analytics and alerting
Development and deployment of machine‑learning models for real‑time hemodynamic analytics, risk prediction, alarm optimization and personalized treatment suggestions.
Expertise Areas
- Non‑invasive hemodynamic monitoring
- Peripheral blood‑flow assessment
- Wearable and implantable sensor miniaturization
- Machine‑learning analytics for physiological data
Key Technologies
- Dynamic light scattering optical sensing
- Optical blood‑flow measurement
- Miniaturized wearable sensor hardware
- Real‑time signal processing algorithms