Home healthcare using ubiquitous computing and robot technologies

The rapid increase of senior population worldwide is challenging the existing healthcare and support systems. Recently, smart home environments are utilized for ubiquitous health monitoring, allowing patients to stay in the comfort of their homes. In this dissertation, a Cloud-based Smart Home Environment (CoSHE) for home healthcare is presented, which consists of ambient intelligence, wearable computing, and robot technologies. The system includes a smart home which is embedded with distributed environmental sensors to support human localization. Wearable units are developed to collect physiological, motion and audio signals through non-invasive wearable sensors and provide contextual information in terms of the resident's daily activity and location in the home. This enables healthcare professionals to study daily activities, behavioral changes and monitor rehabilitation and recovery processes. The sensor data are processed in a smart home gateway and sent to a private cloud, which provides real-time data access for remote caregivers. Our case studies show that contextual information provided by ubiquitous computing can help better understand the patient's health status. With a robot assistant in the loop, we demonstrated that the CoSHE can facilitate healthcare delivery via interaction between human and robot

HealthFog: An ensemble deep learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in integrated IoT and fog computing environments

Cloud computing provides resources over the Internet and allows a plethora of applications to be deployed to provide services for different industries. The major bottleneck being faced currently in these cloud frameworks is their limited scalability and hence inability to cater to the requirements of centralized Internet of Things (IoT) based compute environments. The main reason for this is that latency-sensitive applications like health monitoring and surveillance systems now require computation over large amounts of data (Big Data) transferred to centralized database and from database to cloud data centers which leads to drop in performance of such systems. The new paradigms of fog and edge computing provide innovative solutions by bringing resources closer to the user and provide low latency and energy-efficient solutions for data processing compared to cloud domains. Still, the current fog models have many limitations and focus from a limited perspective on either accuracy of results or reduced response time but not both. We proposed a novel framework called HealthFog for integrating ensemble deep learning in Edge computing devices and deployed it for a real-life application of automatic Heart Disease analysis. HealthFog delivers healthcare as a fog service using IoT devices and efficiently manages the data of heart patients, which comes as user requests. Fog-enabled cloud framework, FogBus is used to deploy and test the performance of the proposed model in terms of power consumption, network bandwidth, latency, jitter, accuracy and execution time. HealthFog is configurable to various operation modes that provide the best Quality of Service or prediction accuracy, as required, in diverse fog computation scenarios and for different user requirements

Towards Smart and Green Features of Cloud Computing in Healthcare Services: A Systematic Literature Review

Background: The healthcare sector has been facing multilateral challenges regarding the quality of services and access to healthcare innovations. As the population grows, the sector requires faster and more reliable services, but the opposite is true in developing countries. As a robust technology, cloud computing has numerous features and benefits that are still to be explored. The intervention of the latest technologies in healthcare is crucial to shifting toward next-generation healthcare systems. In developing countries like Ethiopia, cloud features are still far from being systematically explored to design smart and green healthcare services. Objective: To excavate contextualized research gaps in the existing studies towards smart and green features of cloud computing in healthcare information services. Methods: We conducted a systematic review of research publications indexed in Scopus, Web of Science, IEEE Xplore, PubMed, and ProQuest. 52 research articles were screened based on significant selection criteria and systematically reviewed. Extensive efforts have been made to rigorously review recent, contemporary, and relevant research articles. Results: This study presented a summary of parameters, proposed solutions from the reviewed articles, and identified research gaps. These identified research gaps are related to security and privacy concerns, data repository standardization, data shareability, self-health data access control, service collaboration, energy efficiency/greenness, consolidation of health data repositories, carbon footprint, and performance evaluation. Conclusion: The paper consolidated research gaps from multiple research investigations into a single paper, allowing researchers to develop innovative solutions for improving healthcare services. Based on a rigorous analysis of the literature, the existing systems overlooked green computing features and were highly vulnerable to security violations. Several studies reveal that security and privacy threats have been seriously hampering the exponential growth of cloud computing. 54 percent of the reviewed articles focused on security and privacy concerns. Keywords: Cloud computing, Consolidation, Green computing, Green features, Healthcare services, Systematic literature review

VITASENIOR-MT: a telehealth solution for the elderly focused on the interaction with TV

Remote monitoring of health parameters is a promising approach to improve the health condition and quality of life of particular groups of the population, which can also alleviate the current expenditure and demands of healthcare systems. The elderly, usually affected by chronic comorbidities, are a specific group of the population that can strongly benefit from telehealth technologies, allowing them to reach a more independent life, by living longer in their own homes. Usability of telehealth technologies and their acceptance by end-users are essential requirements for the success of telehealth implementation. Older people are resistant to new technologies or have difficulty in using them due to vision, hearing, sensory and cognition impairments. In this paper, we describe the implementation of an IoT-based telehealth solution designed specifically to address the elderly needs. The end-user interacts with a TV-set to record biometric parameters, and to receive warning and recommendations related to health and environmental sensor recordings. The familiarization of older people with the TV is expected to provide a more user-friendly interaction ensuring the effectiveness integration of the end-user in the overall telehealth solution.This work has been financially supported by the IC&DT project VITASENIOR-MT CENTRO-01-0145-FEDER- 023659 with FEDER funding through programs CENTRO2020 and FCT.info:eu-repo/semantics/publishedVersio

Smart Built Environment Including Smart Home, Smart Building and Smart City: Definitions and Applied Technologies

Technology, particularly over the past decades, has affected the cities and their components, such as building sectors. Consequently, smart building that has currently utilized various technologies which is incorporated into buildings is the core of the present chapter. It provides a comprehensive overview on smart cities, smart buildings and smart home to address what systems and technologies have been incorporated so far. The aim is to review the smart concepts in built environment with the main focus on smart cities, smart buildings, and smart homes. State-of-the-art and current practices in smart buildings were also reviewed to enlighten a set of directions for future studies. The Chapter is primarily focuses on 51 articles in smart buildings/homes, as per collected from various datasets. It represents a summary of systems utilized and incorporared into smart buildings and homes over the past decade (2010–2020). Additional to different features of smart buildings and homes, is the discussion around various fields and system performances currently utilized in smart buildings/homes. Limitations and future trends and directions is also discussed. In total, such building/home systems were categorized into 6 groups, including: security systems, healthcare systems, energy management systems, building/home management systems, automation systems, and activity/movement recognition systems. Furthermore, there are a number of surveys which investigated the user’s acceptance and adoption of the new smart systems in homes and buildings, as presented and summarized thereafter in Tables. The present Chapter is a contribution to a better understanding of the functions and performances of such buildings/homes for further implementation and enhancement so that varying demands of smart citizens are fulfilled and eventually contribute to the development of smart cities

IoT-Enabled Health Monitoring and Assistive Systems for in Place Aging Dementia Patient and Elderly

Hospitals and nursing care homes are facing severe challenges such as lack of skilled workforces and cost explosion, among others. Especially, the western healthcare systems are headed over a cliff. German nursing care houses, hospitals, and government are working hard on solutions to overcome the crucial workforce’s crises. Therefore, they are planning to hire nursing-workforces from abroad. They would also like to motivate families with monetary incentives, such as tax-reduction, if they can care for their elderly and/or dementia family members at home. However, caring for a sick person at home is challenging for a working family member especially in the case the patient requests around-the-clock nursing care since elderly with cognitive impairments, people with physical disabilities, and people with dementia need (medical) assistance around the clock. The present study reveals an increasing tendency for family members to care for their sick family member at home despite the challenges and issues faced like the lack of time to intensively care for the sick person due to today’s family lifestyle, challenging employment market, financial constraints, etc. The study reported in this chapter aims at providing family members willing to care for their sick member at home as long as possible with smart home automation enabled Patient@Home solution to effectively and efficiently care for their sick member despite working full time. People living in nursing care homes can also take benefit of the proposed system. Evidence shows the potential of the proposed system to effectively and efficiently assist in caring for people requesting nursing care around the clock. Though the health-related quality of life is positively impacted, patient’s satisfaction is increased (better quality of experience)

Innovative Business Model for Smart Healthcare Insurance

Information revolution and technology growth have made a considerable contribution to restraining the cost expansion and empowering the customer. They disrupted most business models in different industries. The customer-centric business model has pervaded the different sectors. Smart healthcare has made an enormous shift in patient life and raised their expectations of healthcare services quality. Healthcare insurance is an essential business in the healthcare sector; patients expect a new business model to meet their needs and enhance their wellness. This research develops a holistic smart healthcare architecture based on the recent development of information and communications technology. Then develops a disruptive healthcare insurance business model that adapts to this architecture and classifies the patient according to their technology needs. Finally, and implementing a prototype of a system that matches and suits the healthcare recipient condition to the proper healthcare insurance policy by applying Web Ontology Language (OWL) and rule-based reasoning model using SWRL using Protég

Supporting Health and Wellbeing : Can Smart Housing Help Revolutionise Health and Care?

The concept of future proofing our housing has steadily gained momentum over the last few years as the elderly population continues to grow in Scotland, the UK and the rest of the developed world. In Scotland the number of citizens aged 75 and over has been projected to increase by 27% from 2016-2026 and by 79% between 2016-2041. However, this rise in momentum is not solely attributed to the increasing pressure brought on by an aging population. The commercial demand for more integrated products and services in the home has increased massively as consumers look for further developments in smart technology in the home. These allow for control of multiple home systems ranging from energy and water consumption to entertainment and leisure. These consumer driven advances in smart housing present massive opportunities to support the health and wellbeing of Scotland’s population. This coupled with public policy recognising the benefits of good quality housing to health and wellbeing, and emphasising preventative rather than reactive approaches, presents the smart housing sector with a clear pathway into the Scottish health and care market. Recent research by the Institution of Mechanical Engineers suggests that adapting homes to meet the needs of current elderly residents could help reduce the onset of frailty, which in turn can reduce the risk of hospitalisation [2]. The research claims that physical inactivity costs the NHS £10bn a year UK wide, with £2.5bn spent on care as a result of poor housing. From this, the research infers that allowing vulnerable people to remain in unsuitable homes is costing the NHS some £414 million per year in treatment costs alone