Abstract

The aim of this paper is to present a novel platform for advanced transmission of medical image and video, introducing context awareness in telemedicine systems. Proper scalable image and video compression schemes are applied to the content according to environmental properties (i.e., the underlying network status, content type, and the patient status). The transmission of medical images and video for telemedicine purposes is optimized since better content delivery is achieved even in the case of low-bandwidth networks. An evaluation platform has been developed based on scalable wavelet compression with region-of-interest support for images and adaptive H.264 coding for video. Corresponding results of content transmission over wireless networks (i.e., IEEE 802.11e, WiMAX, and UMTS) have proved the effectiveness and efficiency of the platform.

Highlights

  • IntroductionA number of telemedicine applications exist nowadays, providing remote medical action systems (e.g., remote surgery systems), patient remote telemonitoring facilities (e.g., homecare of chronic disease patients), and transmission of medical content for remote assessment [1,2,3,4,5]

  • A number of telemedicine applications exist nowadays, providing remote medical action systems, patient remote telemonitoring facilities, and transmission of medical content for remote assessment [1,2,3,4,5]

  • The main components of which the platform consists are the attached biosensors to the patient, the software modules responsible for collecting the corresponding signals and determining the appropriate video coding depending on the patient and network statuses, and the simulated network infrastructures (i.e., IEEE 802.11g (WLAN), UMTS, and WiMAX) for data transmission to the monitoring units

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Summary

Introduction

A number of telemedicine applications exist nowadays, providing remote medical action systems (e.g., remote surgery systems), patient remote telemonitoring facilities (e.g., homecare of chronic disease patients), and transmission of medical content for remote assessment [1,2,3,4,5] Such platforms have been proved to be significant tools for the optimization of patient treatment offering better possibilities for managing chronic care, controlling health delivery costs, and increasing quality of life and quality of health services in underserved populations. Appropriate content coding techniques (e.g., video and image compression) have been introduced in order to assess such issues [11,12,13]; the latter are highly associated with specific content type and cannot be applied in general They do not consider the underlying network status for appropriate coding and still cannot resolve the case of unnecessary data transmission

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