Cognitive priority model for advanced telemedical support in Limited Bandwidth Applications

Telemedicine offers the ability to provide real-time medical support, education, and care to remote and austere locations under limited bandwidth restrictions. These types of communication channels can easily be overwhelmed and delays or interruptions make communication difficult, if not impossible. These interruptions destroy the temporal orientation of communication resulting in significant cognitive loading. The objective of this research was to lower cognitive load and minimize digital communication bandwidth by developing a priority model from perceptual quality and content focus of telemedical video. H.264/AVC encoding was used to encode two types of medical context with varying bitrates, frame rates, and frame sizes. Telemedical video contexts were room awareness, and medical procedure. Objective quality and subjective quality tests were performed using Structural Similarity (SSIM) and perceptual feedback, respectively. The objective of this research is to develop context specific telemedicine communication models for the highest perceptual quality for available bandwidth for the purpose of increased temporal orientation and decreased cognitive load. Our research presents a method to select the best encoding parameters (maximum bitrate, frame rate and frame size) for the medical context to minimize bandwidth and maintain diagnostic and education quality.