Scyntek provides a non-invasive device utilizing integrated PPG sensors for proactive deep vein thrombosis detection. The system employs dynamic signal analysis to identify abnormal blood flow patterns before symptoms manifest. This user-centric solution enables cost-effective, real-time monitoring to facilitate early intervention and reduce pulmonary embolism risks.
Funding
Funding not disclosed
Founders
Product
Problem
Deep vein thrombosis (DVT) often goes undetected until symptoms appear, requiring costly hospital-based imaging and specialist oversight. Delayed diagnosis increases the risk of pulmonary embolism and places a burden on patients who lack easy access to clinical facilities, especially in high‑risk groups such as post‑operative patients, frequent travelers, and the elderly.
Solution
Scyntek delivers a non‑invasive, at‑home DVT detection system that continuously monitors peripheral blood flow using integrated photoplethysmography (PPG) sensors. The device captures dynamic flow signals and applies proprietary signal‑analysis algorithms to identify early clot formation patterns. Detected abnormalities trigger instant alerts to the user’s mobile device, enabling timely medical follow‑up. The hardware is compact, comfortable for brief self‑checks, and does not require continuous wear or clinical supervision. Data are encrypted and transmitted to a cloud platform where clinicians can review trends and intervene before complications develop. By shifting screening to the point of need, the solution reduces reliance on expensive imaging studies and supports proactive health management.
Target Audience
The primary users are high‑risk individuals—post‑operative patients, frequent travelers, and seniors in underserved or remote areas—who benefit from proactive DVT monitoring. Healthcare providers such as primary‑care clinics, ambulatory surgery centers, and tele‑medicine platforms also adopt the system to reduce diagnostic referrals and improve patient outcomes.
Features
- Integrated multi‑wavelength PPG sensor array for high‑resolution peripheral blood flow measurement
- Real‑time signal processing engine that extracts dynamic flow parameters and flags deviations indicative of early DVT
- Cloud‑hosted analytics pipeline with secure end‑to‑end encryption and HIPAA‑compliant storage
- Mobile application delivering push notifications, test guidance, and visual trend dashboards for patients and providers
- Compact, ergonomically designed wearable that supports quick self‑administered checks without continuous attachment
- Automated reporting API enabling integration with electronic health record (EHR) systems for clinician review