Internet of Things has been one of the catalysts in revolutionizing conventional healthcare services. With the growing society, traditional healthcare systems reach their capacity in providing sufficient and high-quality services. The world is facing the aging population and the inherent need for assisted-living environments for senior citizens. There is also a commitment by national healthcare organizations to increase support for personalized, integrated care to prevent and manage chronic conditions. Many applications related to In-Home Health Monitoring have been introduced over the last few decades, thanks to the advances in mobile and Internet of Things technologies and services. Such advances include improvements in optimized network architecture, indoor networks coverage, increased device reliability and performance, ultra-low device cost, low device power consumption, and improved device and network security and privacy. Current studies of in-home health monitoring systems presented many benefits including improved safety, quality of life and reduction in hospitalization and cost. However, many challenges of such a paradigm shift still exist, that need to be addressed to support scale-up and wide uptake of such systems, including technology acceptance and adoption by patients, healthcare providers and policymakers. The aim of this paper is three folds: First, review of key factors that drove the adoption and growth of the IoT-based in-home remote monitoring; Second, present the latest advances of IoT based in-home remote monitoring system architecture and key building blocks; Third, discuss future outlook and our recommendations of the in-home remote monitoring applications going forward.

Under the pressure of the growing millennial population and senior citizens are aging, which is one of the top societal priorities in many countries, the provision of healthcare needs to evolve and improve. A roadmap paved by World Health Organization (WHO) in March 2019 called Global Strategy on Digital Health 2020-2024, specified a grand vision of promoting healthy lives and well-beings for everyone, everywhere, at all ages[1]. WHO urges all nations to work hand in hand in developing and delivering Digital Health initiatives supported by robust government strategies that amalgamate financial, organizational, human and technological resources[2]. In particular, there are some niches areas in the strategies such as the adoption of distributed sensors and assisted living emerging in recent years. To this end, a lot of efforts both from the research community and industrial providers are anticipated to put forth in the coming decade, in implementing the concept of assisted living using hardware devices into meaningful solutions for fulfilling the growing needs of assisted living.

Small cell technology is expected to be an integral part of future 5G networks in order to meet the increasingly high user demands for traffic volume, frequency efficiency, and energy and cost reductions. Small cell networks can play an important role in enhancing the Quality of Service (QoS) and Quality of Experience (QoE) in m-health applications, and in particular, in medical video streaming. In this paper, we propose a hybrid medical QoE prediction model based on a Fuzzy Inference System (FIS) that correlates the network QoS (NQoS) and application QoS (AQoS) parameters to the QoE. The model is tested on the transmission of medical ultrasound video over small cell technology. The results show that the predicted QoE scores of our proposed model have a high correlation with the subjective scores of medical experts.

This paper presents the design and evaluation of a COPD mobile application which forms part of the WELCOME project (Wearable Sensing and Smart Cloud Computing for Integrated Care to COPD Patients with Comorbidities). A first prototype of this application has been implemented and is currently being evaluated with patients, human computer interaction experts and healthcare professionals in the UK and the Netherlands. The application allows COPD patients suffering also from different comorbidities to self-manage their disease by taking regular measurement, fill questionnaires requested by their healthcare professionals and follow different programs remotely. The usability and acceptability of the system by COPD patients in the UK are discussed in this paper.

End-to-end delay is an important consideration of the design of wireless tele-ultrasonography systems because such systems support delay-sensitive applications and require critical delay constraints. This paper addresses the characterisation and estimation of end-to-end delay distributions by using the Effective Capacity (EC) technique. A cross-layer simulation platform is built to 1) represent a scenario of remote medical ultrasound video streaming over fixed WiMAX networks, 2) transmit a real ultrasound medical video and 3) verify the accuracy of the EC-based delay distribution estimation for video frames. The results show that in most cases, the simulation results and estimation results are in good agreement.

It is well known that the evolution of 4G-based mobile multimedia network systems will contribute significantly to future mobile healthcare (m-health) applications that require high bandwidth and fast data rates. Central to the success of such emerging applications is the compatibility of broadband networks, such as mobile Worldwide Interoperability For Microwave Access (WiMAX) and High-Speed Uplink Packet Access (HSUPA), and especially their rate adaption issues combined with the acceptable real-time medical quality of service requirements. In this paper, we address the relevant challenges of cross-layer design requirements for real-time rate adaptation of ultrasound video streaming in mobile WiMAX and HSUPA networks. A comparative performance analysis of such approach is validated in two experimental m-health test bed systems for both mobile WiMAX and HSUPA networks. The experimental results have shown an improved performance of mobile WiMAX compared to the HSUPA using the same cross-layer optimization approach.

The application of advanced error concealment techniques applied as a post-process to conceal lost video information in error-prone channels, such as the wireless channel, demand additional processing at the receiver. This increases the delivery delay and needs more computational power. However, in general, only a small region within medical video is of interest to the physician and thus if only this area is considered, the number of computations can be curtailed. In this paper we present a technique whereby the Region of Interest (ROI) specified by the physician is used to delimit the area where the more complex concealment techniques are applied. A cross layer design approach in mobile WiMAX wireless communication environment is adopted in this paper to provide an optimized Quality of Experience (QoE) in the region that matters most to the mobile physician while relaxing the requirements in the background, ensuring real-time delivery. Results show that a diagnostically acceptable Peak Signal-to-Noise-Ratio (PSNR) of about 36 dB can still be achieved within reasonable decoding time.

M-health is an emerging area of research and one of the key challenges in future research in this area is medical video streaming over wireless channels. Contrasting requirements of almost lossless compression and low available bandwidth have to be tackled in medical quality video streaming in ultrasound and radiology applications. On one side, compression techniques need to be conservative, in order to avoid removing perceptively important information; on the other side, error resilience and correction should be provided, with the constraint of a limited bandwidth. A quality-driven, network-aware approach for joint source and channel coding based on a controller structure specifically designed for enhanced video streaming in a robotic teleultrasonography system is presented. The designed application based on robotic teleultrasonography is described and the proposed method is simulated in a wireless environment in two different scenarios; the video quality improvement achievable through the proposed scheme in such an application is remarkable, resulting in a peak signal-to-noise ratio (PSNR) improvement of more than 4 dB in both scenarios.

The design of an efficient mobile healthcare system using 3.5G and 4G wireless networks is a challenging problem especially for bandwidth demanding telemedical applications. In this paper, we focus on the concept of medical quality of service (m-QoS) applied to a typical bandwidth demanding m-health application. Based on this concept, we propose a novel multiobjective rate-control mechanism for the optimized delivery of diagnostically acceptable ultrasound video images over 3.5G wireless networks. The performance of the proposed algorithm has been evaluated via both simulations and experimental studies. The proposed optimal rate control algorithm achieved performance improvements that are compatible with the medical QoS requirements.