Vivalink, a leading provider of real-world evidence-based digital healthcare solutions, has launched an enhanced Biometrics Data Platform to accelerate the development and deployment of patient monitoring and data analysis apps for the ambulatory and remote setting market. As part of its end-to-end solution, Vivalink’s Biometrics Data Platform combines both advanced data services and medical wearable sensors.
Vivalink’s integrated Biometrics Data Platform is the world’s first real-time proof-of-concept data platform offering data and insights services to virtual care providers and drug developers. Platforms that enable wearable sensors, edge networks, data integration, and data analytics can speed up time-to-market by removing development and regulatory complexity.
A mobile app for clinical patients, advanced data processing, and machine learning (ML) technologies are included in Vivalink’s Biometrics Data Platform, along with the company’s best-in-class medical wearable sensors. The system collects a continuous stream of vital signs and biometric information automatically during real-world settings, like at home or while ambulatory, and ensures that the data can be analyzed and processed from any location in real-time or retrospectively.
The platform’s patient-friendly sensors have been cleared for use in major geographic regions including the United States, the European Union, and China. With a wide variety of reusable sensors for monitoring human vital signs, including multi-vital ECG sensors with a data cache and stronger network connectivity, Vivalink is the leading provider of human vital sign monitoring. The improvements resulting from their experience in real-world patient applications were based on their years of experience.
Biometrics Data Platform features include:
- Patient-friendly wearable sensors for capturing continuous human vital signs and metrics
- Ensure data ingestion and delivery with remote data transfer and synchronization technologies
- Provides both live and retrospective access to data through the use of an advanced biometric data lake for AI and machine learning
- Integration of clinical databases via automated data transformation
- Data integration tools including FHIR, web service APIs, and webhooks
- Data visualization tools
- Complete systems management of sessions and sensors
