Dynamic Network Adaptation for Real-Time Medical Video Communication

The wider adoption of mHealth video communication systems in standard clinical practice requires adequate levels of clinical video quality to support reliable diagnosis. The latter dictates that real-time adaptation to time-varying wireless networks' state to guarantee clinically acceptable performance throughout the streaming session, while conforming to device capabilities for supporting real-time encoding. In this study we propose a multi-objective optimization framework that jointly maximizes the encoded video's quality while minimizing bitrate demands and encoding time. Experimental investigation shows that the proposed framework can provide for efficient real-time adaptation at a Group of Pictures (GOP) level, demonstrating significant gains over static approaches.