Real time telemedical health care systems with wearable sensors

The time between detection and response to chronic diseases could go a long way in saving lives. The current trend in health monitoring systems is to move from the hospital centered device to eventually portable personal devices. Hence,Telemedical health care involves the remote delivery of medical care service to either out-of-hospital or admitted patients through wireless network and computer information technology. This paper systematically reviews the most recent works in telemedical health care system to propose a more efficient model. The focus is more on wearable sensors and devices with most attention given to cardiovascular patients in recent times. The huge literature available reflects the size of activity and attention given to telemedicine. The reviewed works are published within the last five years. Furthermore, the proposed systems are compared in terms of their connectivity, targeted application, type of sensor used, etc. Our study reveals Telemedicine to be a profound field with researchers from multidisciplinary sectors. However, there are still many gaps that need to be filled before maturity. Factors such as efficient wireless transmission, cyber data security, sensor design and integration, device miniaturization and intelligent algorithm for multi parameter data fusion require further considerations

A patient agent controlled customized blockchain based framework for internet of things

Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.Doctor of Philosoph

Designing an Artifact to Empower Chronic Patients for Monitoring Health During a Pandemic: A COVID-19 Screening App

Chronic diseases have been declared an invisible epidemic by the World Health Organization (WHO, 2005). Over the past fifty years, the prevalence of chronic conditions has increased, leading to the disease burden caused by cancer, cardiovascular diseases, diabetes, and mental and substance use disorders (DOH, 2021). Chronic patients need to reimagine how they will empower themselves to effectively manage and monitor their health and wellbeing in a COVID-19 era when frequent in-person health care visits will no longer be feasible. In this study, we propose the dimensions for the design of a mobile-based application that will aid chronic patients and end-users in self-managing and monitoring their health during the pandemic era. Based on an empirical investigation involving pharmacists and researchers, we designed and developed a prototype capable of empowering chronic patients. This study particularly focuses on how technological interventions can help chronic patients self-manage and monitor their health and well-being related to COVID-19 where the user expectations are met with less attrition rates

Context-aware system for cardiac condition monitoring and management: a survey

Health monitoring assists physicians in the decision-making process, which in turn, improves quality of life. As technology advances, the usage and applications of context-aware systems continue to spread across different areas in patient monitoring and disease management. It provides a platform for healthcare professionals to assess the health status of patients in their care using multiple relevant parameters. In this survey, we consider context-aware systems proposed by researchers for health monitoring and management. More specifically, we investigate different technologies and techniques used for cardiac condition monitoring and management. This paper also propose "mCardiac", an enhanced context-aware decision support system for cardiac condition monitoring and management during rehabilitation