W2E--Wellness Warehouse Engine for Semantic Interoperability of Consumer Health Data

Area of Science:

• Digital Health
• Biomedical Informatics
• Wearable Technology

Background:

• Consumer health monitoring devices offer convenient health status tracking.
• Lack of technical and semantic interoperability between devices and services limits health data reusability.
• Proprietary data formats hinder the integration and utilization of health data across different platforms.

Purpose of the Study:

• To design and introduce the Wellness Warehouse Engine (W2E) for seamless health data exchange.
• To address the interoperability challenges in consumer health monitoring data.
• To enable enhanced data utilization and analysis through a unified platform.

Main Methods:

• Developed the Wellness Warehouse Engine (W2E) with interfaces for diverse data sources.
• Implemented a unified Representational State Transfer (REST) API for data accessibility.
• Integrated the Unifier engine for transforming data into generic units and the Analyzer engine for advanced data analysis.

Main Results:

• Successfully unified data from four different consumer activity trackers.
• Demonstrated W2E's applicability with a test base of 20 subjects and three tracking sessions each.
• Validated the capability of combining disparate data sources into new, meaningful output parameters.

Conclusions:

• W2E effectively bridges the interoperability gap in consumer health data.
• The system facilitates seamless data exchange and enhances data reusability across services.
• Challenges remain in scaling the Unifier engine for a growing number of devices.