Multiple Video Delivery in m-Health Emergency Applications

Abstract

M-health services are expected to become increasingly relevant in the management of emergency situations by enabling real-time support of remote medical experts. In this context, the transmission of multiple health-related video streams from an ambulance to a remote hospital can improve the efficacy of the teleconsultation service, but requires a large bandwidth to meet the desired quality, not always guaranteed by the mobile network. In order to deliver the multiple streams over a single bandwidth-limited wireless access channel, in this paper we propose a novel optimization framework that enables to classify the available video sources and to automatically select and adapt the best streams to transmit. The camera ranking algorithm jointly works with a cross-layer adaptation strategy for multiple scalable streams to achieve different objectives and/or tradeoffs in terms of number and target quality of the transmitted videos. The final goal of the optimization is to dynamically adjust the overall transmitted throughput to meet the actual available bandwidth, while being able to provide high quality to diagnostic video sequences and lower quality to less critical ambient videos. Numerical simulations considering a realistic emergency scenario with long term evolution advanced (LTE-A) connectivity show that the proposed content/context-aware solution is able to automatically select the best sources of information from a visual point of view and to achieve optimal end-to-end video quality for both the diagnostic and the ambient videos

A Systematic Review on Recent Advances in mHealth Systems: Deployment Architecture for Emergency Response

“…It was also common to find environmental sensors to monitor ambient conditions at the emergency location. The reported ambient conditions were temperature, light, noise, and humidity [ 10 , 11 , 20 , 24 ]. In terms of sensor data sampling, authors in [ 8 ] reported AN error-free transmission of biomedical signals.…”

Toward Physiology-Aware DASH: Bandwidth-Compliant Prioritized Clinical Multimedia Communication in Ambulances

“…Researches on adaptive streaming have been mostly applied to video context, and generally range from network coding, bandwidth detection, and rate determinations [2], [3], [4], [5], [6] to quality of service and user experience [7], [8], [9]; many also have been applied to video-based tele-medicine systems [10], [11], [12], [13], [14], [15]. In [13], [14], and [15] for instance, the authors study bandwidth adaptation techniques for adaptive transmission of medical videos over the bandwidth-limited mobile networks, some targeting 4G and beyond small cells. Also, the authors in [16] target lower network layers in mobile tele-medicine, and propose a TDMA-based MAC layer scheme for bandwidth reservation among cells for tele-medicine traffic handoff.…”

Scheduling for telemedicine traffic transmission over WLANs

“…Recent research efforts on different types of networks include [10][11][12][13], which focus on the problem of medical video streaming over 4G cellular networks, as well as [14], which proposes a framework for transmitting medical multimedia over cognitive radio networks.…”

“…The authors point out, however, that AVC (which is used in our work) provides better picture quality. The work in [12], which focuses on cellular networks, also uses SVC.…”