Design of an Edge-based Portable EHR System for Anemia Screening in Remote Health Applications
This addresses the problem of poor interoperability and lack of offline support in digital health for frontline health workers in underserved regions, though it is incremental as it builds on existing edge and diagnostic methods.
The paper tackled the problem of designing a medical system for remote, resource-limited environments by presenting a portable, edge-enabled Electronic Health Record platform with an integrated anemia screening module, achieving a test RMSE of 1.969 g/dL and MAE of 1.490 g/dL for the Random Forest model and reducing inference latency from 46.96 ms to 21.50 ms with quantized YOLOv8n.
The design of medical systems for remote, resource-limited environments faces persistent challenges due to poor interoperability, lack of offline support, and dependency on costly infrastructure. Many existing digital health solutions neglect these constraints, limiting their effectiveness for frontline health workers in underserved regions. This paper presents a portable, edge-enabled Electronic Health Record platform optimized for offline-first operation, secure patient data management, and modular diagnostic integration. Running on small-form factor embedded devices, it provides AES-256 encrypted local storage with optional cloud synchronization for interoperability. As a use case, we integrated a non-invasive anemia screening module leveraging fingernail pallor analysis. Trained on 250 patient cases (27\% anemia prevalence) with KDE-balanced data, the Random Forest model achieved a test RMSE of 1.969 g/dL and MAE of 1.490 g/dL. A severity-based model reached 79.2\% sensitivity. To optimize performance, a YOLOv8n-based nail bed detector was quantized to INT8, reducing inference latency from 46.96 ms to 21.50 ms while maintaining mAP@0.5 at 0.995. The system emphasizes low-cost deployment, modularity, and data privacy compliance (HIPAA/GDPR), addressing critical barriers to digital health adoption in disconnected settings. Our work demonstrates a scalable approach to enhance portable health information systems and support frontline healthcare in underserved regions.