Future body-to-body networks for ubiquitous healthcare: a survey, taxonomy and challenges

Abstract

Abstract-Smart mobile people have a great potential to extend the existing Internet of Things infrastructures by implementing genuine ubiquitous healthcare (U-health) applications, ensuring anywhere and anytime patients connectivity. Through the forwarding of sensing data from person to person until reaching a connected medical server, concrete U-health becomes true with the emerging of future Body-to-Body Networks. Indeed, the coexistence of multiple WBANs (Wireless Body Area Networks), the communication and interactions between them extend the classical concept of WBAN and present the new paradigm referred to as Body-to-Body Network (BBN). This paradigm supports a number of innovative applications such as U-health, entertainment, interactive gaming and military, to cite a few.In this paper, we present a survey of BBNs focusing on three principal axes: energy efficiency, mobility prediction, and quality of service (QoS). Then, we present and discuss different candidate protocols that can be used in BBNs, while illustrating main BBN design challenges and several open issues.

Cross-layer optimized routing with low duty cycle TDMA across multiple wireless body area networks

“…where h sc (τ ) is the equivalent channel gain at the output of SC, at time instant τ . h sd is the channel gain from sourceto-destination (direct link), h srid = min{h sri , h rid } are the channel gains of the first and second cooperative relayed links (with two link-hops, s to r i , and r i to d) for i = [1,2], respectively.…”

Experimental Analysis of Cross-Layer Optimization for Distributed Wireless Body-to-Body Networks

“…The main motivation behind BBNs is to make use of body-to-body (B2B) communications to overcome the problems of coexistence and general performance degradation for closely located BANs. As stated in [4], a body-to-body network is theoretically a mesh network that uses people (with body-worn sensors) to transmit or relay data within a limited geographic area, by creating their own centralized or decentralized network connection. This type of self-organizing, intelligent network could provide cost-effective solutions for remote monitoring of a group of patients wearing BAN sensors, for instance, by relaying physiological data/information up to the access point of the medical service, without depending on any external coordination.…”

A systematic literature review of data forecast and internet of things on the e-health landscape

“…The relation of the research with prediction is in the results, since as the authors did not find an approach for prediction of chronic disorders in wearable devices context, they proposed a methodology for this. Another study is a survey conducted by Meharouech et al (2015) on ubiquitous healthcare. The focus of the research was on the use of ubiquitous devices for the health area, and some of the several studies addressed, provided approaches for the mobility prediction of patients.…”

“…Based on this, we can note that although there are surveys that address the use of IoT in the health area, there are still no surveys which combine data forecast in this area of study, that means there is no global view of it in the literature. Although there are taxonomies such as the one proposed by Meharouech et al (2015), they focus only on IoT in the healthcare area and do not address data forecast.…”