Preemptive Epidemic Information Transmission Model Using Nonreplication Edge Node Connectivity in Health Care Networks.

The reliability in medical data organization and transmission is eased with the inheritance of information and communication technologies in recent years. The growth of digital communication and sharing medium imposes the necessity for optimizing the accessibility and transmission of sensitive medical data to the end-users. In this article, the Preemptive Information Transmission Model (PITM) is introduced for improving the promptness in medical data delivery. This transmission model is designed to acquire the least communication in an epidemic region for seamless information availability. The proposed model makes use of a noncyclic connection procedure and preemptive forwarding inside and outside the epidemic region. The first is responsible for replication-less connection maximization ensuring better availability of the edge nodes. The connection replications are reduced using the pruning tree classifiers based on the communication time and delivery balancing factor. The later process is responsible for the reliable forwarding of the acquired data using a conditional selection of the infrastructure units. Both the processes of PITM are accountable for improving the delivery of observed medical data, over better transmissions, communication time, and achieving fewer delays.

Towards an optimized security approach to IoT devices with confidential healthcare data exchange.

Reliable data exchange and efficient image transfer are currently significant research challenges in health care systems. To incentivize data exchange within the Internet of Things (IoT) framework, we need to ensure data sovereignty by facilitating secure data exchange between trusted parties. The security and reliability of data-sharing infrastructure require a community of trust. Therefore, this paper introduces an encryption frame based on data fragmentation. It also presents a novel, deterministic grey-scale optical encryption scheme based on fundamental mathematics. The objective is to use encryption as the underlying measure to make the data unintelligible while exploiting fragmentation to break down sensitive relationships between attributes. Thus, sensitive data distributed in separate data repositories for decryption and reconstruction using interpolation by knowing polynomial coefficients and personal values from the DBMS Database Management System. Aims also to ensure the secure acquisition of diagnostic images, micrography, and all types of medical imagery based on probabilistic approaches. Visual sharing of confidential medical imageries based on implementing a novel method, where transparencies ≤k - 1 out of n cannot reveal the original image.

On Analyzing Routing Selection for Aerial Autonomous Vehicles Connected to Mobile Network.

This paper proposes a two-phase algorithm for multi-criteria selection of packet forwarding in unmanned aerial vehicles (UAV), which communicate with the control station through commercial mobile network. The selection of proper data forwarding in the two radio link: From UAV to the antenna and from the antenna to the control station, are independent but subject to constrains. The proposed approach is independent of the intra-domain forwarding, so it may be useful for a number of different scenarios of Unmanned Aerial Vehicles connectivity (e.g., a swarm of drones). In the implementation developed in this paper, the connection is served by three different mobile network operators in order to ensure reliable connectivity. The proposed algorithm makes use of Machine Learning tools that are properly trained for predicting the behavior of the link connectivity during the flight duration. The results presented in the last section validate the algorithm and the training process of the machines.

Shaping the Future of Digitally Enabled Health and Care.

People generally need more support as they grow older to maintain healthy and active lifestyles. Older people living with chronic conditions are particularly dependent on healthcare services. Yet, in an increasingly digital society, there is a danger that efforts to drive innovations in eHealth will neglect the needs of those who depend on healthcare the most-our ageing population. The SHAPES (Smart and Healthy Ageing through People Engaging in Supportive Systems) Innovation Action aims to create an open European digital platform that facilitates the provision of meaningful, holistic support to older people living independently. A pan-European pilot campaign will evaluate a catalogue of digital solutions hosted on the platform that have been specifically adapted for older people. 'Medicines control and optimisation' is one of seven themes being explored in the campaign and will investigate the impact of digital solutions that aim to optimise medicines use by way of fostering effective self-management, while facilitating timely intervention by clinicians based on remote monitoring and individualised risk assessments powered by artificial intelligence. If successful, the SHAPES Innovation Action will lead to a greater sense of self-sufficiency and empowerment in people living with chronic conditions as they grow older.

Design of a Continuous Blood Pressure Measurement System Based on Pulse Wave and ECG Signals.

With increasingly fierce competition for jobs, the pressures on people have risen in recent years, leading to lifestyle and diet disorders that result in significantly higher risks of cardiovascular disease. Hypertension is one of the common chronic cardiovascular diseases; however, mainstream blood pressure measurement devices are relatively heavy. When multiple measurements are required, the user experience and the measurement results may be unsatisfactory. In this paper, we describe the design of a signal collection module that collects pulse waves and electrocardiograph (ECG) signals. The collected signals are input into a signal processing module to filter the noise and amplify the useful physiological signals. Then, we use a wavelet transform to eliminate baseline drift noise and detect the feature points of the pulse waves and ECG signals. We propose the concept of detecting the wave shape associated with an instance, an approach that minimizes the impact of atypical pulse waves on blood pressure measurements. Finally, we propose an improved method for measuring blood pressure based on pulse wave velocity that improves the accuracy of blood pressure measurements by 58%. Moreover, the results meet the american medical instrument promotion association standards, which demonstrate the feasibility of our measurement system.