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IoT Contextual Factors on Healthcare
Abstract
With the emergence of the Internet of Things, new services in healthcare will be available and existing systems will be integrated in the IoT framework, providing automated medical supervision and efficient medical treatment. Context awareness plays a critical role in realizing the vision of the IoT, providing rich contextual information that can help the system act more efficiently. Since context in healthcare has its unique characteristics, it is necessary to define an appropriate context aware framework for healthcare IoT applications. We identify this context as perceived in healthcare applications and describe the context aware procedures. We also present an architecture that connects the sensors that measure biometric data with the sensory networks of the environment and the various IoT middleware that reside in the geographical area. Finally, we discuss the challenges for the realization of this vision.
... As examples of challenges related to the use of context awareness in health, we can mention the integration of heterogeneous sensor data, with different technologies, included in these networks and protocols [16,22]. The energy efficiency of the sensors, as well as their responsiveness and robustness, are some of the challenges that arise [17,38,51]. Another challenge is context switching and continuous data delivery, without gaps [8,10]. ...
... In health monitoring systems, security is a critical issue because it involves many processes and components: sensors and actuators, data collection, and communication. Michalakis and Caridakis [38] point out that people show greater sensitivity when sharing their personal health information, that is, privacy and security are of greater importance for health services compared to other similar services. Al-Neyadi and Abawajy [2] propose a mechanism to control access to e-health systems based on context. ...
... Chiang and Liang [13] and Mitchell et al. [40] propose a home care system that stores the required contexts of knowledge in ontologies, including the physiological information and the patient's environmental information, providing a unified query interface with the contextual data on mobile devices and providing interactive user feedback. [7,9,27,33,36,38,41,47,57,59,62] Nursing home [45] Assisted auto care [9,40] Tele-healthcare [9,13,61] ...
The incorporation of information and communication technologies has transformed the health field. With the constant miniaturization of embedded devices, the increase in human–computer interactions and their ubiquity has increased the possibilities of intervention in this field of study. One of the fundamental characteristics of ubiquitous computing applied to health is context awareness. The use of context awareness in healthcare faces many challenges, which has led to the search for several solutions in the integration of sensors from different origins, in data fusion and reasoning algorithms, among others. This paper aims to explore the recent literature related to the use of context awareness in health, defining the taxonomy and identifying challenges and open questions. The method for achieving these objectives is to use the systematic literature review approach, which is characterized by research questions that guide the definition of a taxonomy and the search for challenges in the area. As a result, we have reviewed around 4000 scientific studies published over the last ten years, selecting and researching the most meaningful, in-depth approaches in the field of context-aware health, resulting in a final corpus of 38 articles. We have developed an up-to-date taxonomy that classifies context awareness in the field of health, as well as identifying open questions and issues that can guide future work in the area. These results, unified in one paper, contribute to a significant degree of coverage of the use of context-aware data in health.
... SCADA systems consist of software program additives and hardware [13]. The hardware collects and feeds-built information right into the laptop which has software of SCADA built-in [14], [15]. The SCADA evolution is that past due-era SCADA structures evolved built-into the first technology IoT structures [10]. ...
... Collaboration between detectors, widgets, doors, workers, and customer apps is the core brand that makes the Internet of Things the way it is. Still, what empowers so important shrewd stuff to talk, and associate are the IoT conventions that can be viewed as cants that the IoT gear utilizes to conduct [14]. ...
Many specialists are now looking for ways for commercial development and the introduction of technology and internet applications, especially since many homes in smart and developed cities need a great degree of fitness and electrical control. Now, days the Internet of Things shows a most important potential for commercial development in certain sectors. Therefore, this paper came with the aim of revealing a large variety of constantly evolving protocols for the internet of thing network design in particular three of these are constrained protocols such as message queuing telemetry transfer, application protocol message protocol extended, and message queuing telemetry transfer. To achieve this, the researcher used and followed the qualitative approach that relies on survey tools and theoretical presentation. Among the results obtained that: message queuing telemetry transfer is the best protocol among the three types as it has a high degree of reliability using supportive service quality levels and characterized by the use of neutral packets. The information may also contain binary or text content and has a superior transmission mechanism with efficiencies such as one-to-one, many-to-many or one-to-nothing. In addition, and for ease he uses easy-to-state strategies. Keywords: CoAP IoT MQTT Protocols XMPP This is an open access article under the CC BY-SA license.
... Information about Covid-19 is stored in the cloud server. By analyzing these data and observing the patient's day-to-day activities, caregivers can alert and guide the patient appropriately [8][9][10]. Recently the coronavirus has taken the shape of a global epidemic, called Covid-19. ...
Internet of Things (IoT) technology has brought a revolution in several ways to a common person's life by making everything smart and intelligent. During the Covid-19 crisis, health workers around the world needed to monitor patients' health and needed to provide sufficient oxygen, when necessary, as Covid-19 was responsible for many respiratory cases. Health workers were at high risk of being contaminated while treating Covid-19 patients. The study of this paper is to propose an IoT-based automatic oxygen flow control in response to the Covid-19 crisis. The proposed approach helped to real-time monitoring of SpO2, heartbeat, oxygen quantity of oxygen cylinder, and control of the flow of oxygen based on SpO2 value. A health worker can monitor a patient's health-related parameters and control the flow of oxygen without any physical contact with it. Also, provides an alarm to the health worker when SpO2 is below the threshold and re-measuring oxygen quantity of oxygen cylinder with the help of our developed android app. Implementation of IoT-based low-cost pulse oximeter and IoT-based pressure gauge helps to monitor and control different health parameters. The IoT-based system may potentially be valuable during the Covid-19 pandemic for accurate oxygen flow distribution and for saving people's lives.
... End-to-end connected devices in the architecture are responsible for delivering patient data from home to the hospital and/or caregivers. The SHM framework harness the capabilities of stationary and mobile electronic devices, including laptops, smartphones, and medical terminals, and creates heterogeneous computing networks [73]. ...
During the COVID-19 pandemic, the patient care delivery paradigm rapidly shifted to remote technological solutions. Rising rates of life expectancy of older people, and deaths due to chronic diseases (CDs) such as cancer, diabetes and respiratory disease pose many challenges to healthcare. While the feasibility of Remote Patient Monitoring (RPM) with a Smart Healthcare Monitoring (SHM) framework was somewhat questionable before the COVID-19 pandemic, it is now a proven commodity and is on its way to becoming ubiquitous. More health organizations are adopting RPM to enable CD management in the absence of individual monitoring. The current studies on SHM have reviewed the applications of IoT and/or Machine Learning (ML) in the domain, their architecture, security, privacy and other network related issues. However, no study has analyzed the AI and ubiquitous computing advances in SHM frameworks. The objective of this research is to identify and map key technical concepts in the SHM framework. In this context an interesting and meaningful classification of the research articles surveyed for this work is presented. The comprehensive and systematic review is based on the “Preferred Reporting Items for Systematic Review and Meta-Analysis” (PRISMA) approach. A total of 2540 papers were screened from leading research archives from 2016 to March 2021, and finally, 50 articles were selected for review. The major advantages, developments, distinctive architectural structure, components, technical challenges and possibilities in SHM are briefly discussed. A review of various recent cloud and fog computing based architectures, major ML implementation challenges, prospects and future trends is also presented. The survey primarily encourages the data driven predictive analytics aspects of healthcare and the development of ML models for health empowerment.
... This review paper is the first to highlight 64 the prospects of Industrial Internet of things (IIoT) in the healthcare sector and just second 65 in the area of digital manufacturing. Table 2 highlights novelty of this review paper vis-a- 66 vis increasing interest of the scientific community in this area. 67 Table 2: ...
Industry 4.0 revolution in healthcare involves using a wide range of modern technologies in-cluding digitisation, artificial intelligence, user response data (ergonomics), human psychology, Internet of Things, Machine learning, Big data mining, augmented reality to name a few. The healthcare industry is undergoing a paradigm shift – thanks to Industry 4.0 which is providing better user comfort through proactive intervention in early detection and treatment of various diseases. The sector is now ready to make its next move towards Industry 5.0, but certain aspects need further consideration that motivated this review paper. As a fruitful outcome of this review, we surveyed modern trends in this arena of research and summarised the bits-and-bobs of new features to guide and prepare the sector towards Industry 5.0 ready healthcare system.
... For the sake of the victims, most of the hospitals have initiated the services of telemedicine for infected individuals. Michalakis, K., & Caridakis, G. (2017) ...
Healthcare is an imperative portion of life. Tragically, the exceptional outbreak of the 2019 novel coronavirus, named as COVID-19 by the World Health Organization (WHO), has strained the largest part of health systems and the request for resources from hospital packs to specialists and nurses have become extremely high. However, With the rise of the Internet of Things, new services in healthcare will be accessible and existing systems will be coordinated within the IoT system, giving automated medical supervision and efficient medical treatment, it is evident that a solution is necessary and required to promote the health sector in the era of Covid-19 pandemic whereas proceeding to supply a high-quality care to patients. In this article, we shed light on a few of the issues and challenges related to the appropriation of portable contact tracing and monitoring of patients’ arrangements for fighting COVID-19.
... As everyone knows that lot of COVID deaths taken and this technology can quickly provide information pertaining to health by using sensors. All COVID-19 patient information is stored in cloud which helps to monitor the health activity and alerts to particular person (Michalakis , 2017) ...
As all of us take perceived around the present eruption of COVID-19 that became primary grown from Wuhan-China, happening December 31, 2019. Through unexpectedly dispersal viruses like COVID-19 are the ambitious fears for clinical experts in completely places round the arena. Medical government, as well as citizens, are now the usage of IoT generation to tell people to keep away from taking walks out of doors in the absence of mask and estimate their temperature from a distance with the assist of drones. Various technologies had been acquired via China to handle the deadly virus unfold across the Country. The Wuhan coronavirus eruption has all started to be a global disaster, causing hundreds lifeless, sendoff tens of millions at a danger, economies blocked, factories, as well as cities, are beneath lockdown. The World Health Organization (WHO) statuses the coronavirus (COVID-19) outburst as 'worldwide fitness emergency. With this paper, you'll be successful to understand how technology are being applied inside the several degrees of the outbreak with a number of the possible high-tech ideas. This paper provides the IoT implementation using various devices during COVID-19 scenario and applied in the numerous phases of the outburst.
... This technology can capture the daily activity of a person and make alerts about health problem. [8][9][10] There is an essential requirement for the proper equipment to make a successful operation in the medical field. IoT has a high capability to make successful operations and also analysis the improvement after the surgery. ...
Background/objectives
The Internet of Things (IoT) can create disruptive innovation in healthcare. Thus, during COVID-19 Pandemic, there is a need to study different applications of IoT enabled healthcare. For this, a brief study is required for research directions.
Methods
Research papers on IoT in healthcare and COVID-19 Pandemic are studied to identify this technology's capabilities. This literature-based study may guide professionals in envisaging solutions to related problems and fighting against the COVID-19 type pandemic.
Results
Briefly studied the significant achievements of IoT with the help of a process chart. Then identifies seven major technologies of IoT that seem helpful for healthcare during COVID-19 Pandemic. Finally, the study identifies sixteen basic IoT applications for the medical field during the COVID-19 Pandemic with a brief description of them.
Conclusions
In the current scenario, advanced information technologies have opened a new door to innovation in our daily lives. Out of these information technologies, the Internet of Things is an emerging technology that provides enhancement and better solutions in the medical field, like proper medical record-keeping, sampling, integration of devices, and causes of diseases. IoT's sensor-based technology provides an excellent capability to reduce the risk of surgery during complicated cases and helpful for COVID-19 type pandemic. In the medical field, IoT's focus is to help perform the treatment of different COVID-19 cases precisely. It makes the surgeon job easier by minimising risks and increasing the overall performance. By using this technology, doctors can easily detect changes in critical parameters of the COVID-19 patient. This information-based service opens up new healthcare opportunities as it moves towards the best way of an information system to adapt world-class results as it enables improvement of treatment systems in the hospital. Medical students can now be better trained for disease detection and well guided for the future course of action. IoT's proper usage can help correctly resolve different medical challenges like speed, price, and complexity. It can easily be customised to monitor calorific intake and treatment like asthma, diabetes, and arthritis of the COVID-19 patient. This digitally controlled health management system can improve the overall performance of healthcare during COVID-19 pandemic days.
... It focuses on integrating measurements collected from different sources by using ontology to enable semantic interpretation of events and context awareness. In [23], the authors emphasized the importance of context awareness to the IoT paradigm in general and to healthcare monitoring systems in particular. They proposed an architecture that connects the different layers involved in the IoT platform to realize and deliver context aware healthcare monitoring systems. ...
This paper introduces an investigation of the healthcare monitoring systems and their provisioning in the IoT platform. The different roles that exist in healthcare systems are specified and modeled here. This paper also attempts to introduce and propose a generic framework for the design and development of context aware healthcare monitoring systems in the IoT platform. In such a framework, the fundamental components of the healthcare monitoring systems are identified and modelled as well as the relationship between these components. The paper also stresses on the crucial role played by the AI field in addressing resilient context aware healthcare monitoring systems. Architecturally, this framework is based on a distributed layered architecture where the different components are deployed over the physical layer, fog platform and the cloud platform.
... There has been a massive surge in the use of fitness trackers or wearables in the past few years, and the market data is indicative of the same with the projected increase in the use of these in the future [31]. The evolution of smart health monitoring devices added with improved connectivity to the IoT communication infrastructure has led to the development of a healthcare-oriented system called IoThNet [32]. There is a massive potential for these IoT systems to track the health progress of the users. ...
The impact of the Internet of Things (IoT) on the advancement of the healthcare industry is immense. The ushering of the Medicine 4.0 has resulted in an increased effort to develop platforms, both at the hardware level as well as the underlying software level. This vision has led to the development of Healthcare IoT (H-IoT) systems. The basic enabling technologies include the communication systems between the sensing nodes and the processors; and the processing algorithms for generating an output from the data collected by the sensors. However, at present, these enabling technologies are also supported by several new technologies. The use of Artificial Intelligence (AI) has transformed the H-IoT systems at almost every level. The fog/edge paradigm is bringing the computing power close to the deployed network and hence mitigating many challenges in the process. While the big data allows handling an enormous amount of data. Additionally, the Software Defined Networks (SDNs) bring flexibility to the system while the blockchains are finding the most novel use cases in H-IoT systems. The Internet of Nano Things (IoNT) and Tactile Internet (TI) are driving the innovation in the H-IoT applications. This paper delves into the ways these technologies are transforming the H-IoT systems and also identifies the future course for improving the Quality of Service (QoS) using these new technologies.
... In healthcare, the IoT is driving a revolution to design effective and efficient healthcare delivery by forming a seamless platform for communication between various segments of the healthcare environment, enabling digital support at each step. Embracing digital solutions to support the evolution and transformation of health services is essential [1,2]. Imaging workflow entails seamless integration of data at the level of the patient, scheduling, billing, imaging data acquisition, storage and transfer, and physician for optimal productivity. ...
Radiology by its nature is intricately connected to the Internet and is at the forefront of technology in medicine. The past few years have seen a dramatic rise in Internet-based technology in healthcare, with imaging as a core application. Numerous Internet-based applications and technologies have made forays into medicine, and for radiology it is more seamless than in other clinical specialties. Many applications in the practice of radiology are Internet based and more applications are being added every day. Introduction of mobile devices and their integration into imaging workflow has reinforced the role played by the Internet in radiology. Due to the rapid proliferation of wearable devices and smartphones, IoT-enabled technology is evolving healthcare from conventional hub-based systems to more personalized healthcare systems. This article briefly discusses how the IoT plays a useful role in daily imaging workflow and current and potential future applications, how mobile devices can be integrated into radiology workflows, and the impact of the IoT on resident and medical student education, research, and patient engagement in radiology.
... Restrooms in places with higher traffic such as those in the main hospital received higher requests for cleaning in comparison with restrooms on an inpatient ward. These findings suggest that the IoT button system can enable contextual awareness of restroom cleanliness to enable real-time housekeeping staffing levels based on requests for cleaning [14]. For example, during times of high public traffic, if there is a real-time increase in requests for clean in one part of the hospital, this could be an indication to housekeeping leadership to move a housekeeper to that area from one where there are less requests for clean. ...
Background: Restroom cleanliness is an important factor in hospital quality. Due to its dynamic process, it can be difficult to detect the presence of dirty restrooms that need to be cleaned. Using an Internet of Things (IoT) button can permit users to designate restrooms that need cleaning and in turn, allow prompt response from housekeeping to maintain real-time restroom cleanliness.
... Restrooms in places with higher traffic such as those in the main hospital received higher requests for cleaning in comparison with restrooms on an inpatient ward. These findings suggest that the IoT button system can enable contextual awareness of restroom cleanliness to enable real-time housekeeping staffing levels based on requests for cleaning [14]. For example, during times of high public traffic, if there is a real-time increase in requests for clean in one part of the hospital, this could be an indication to housekeeping leadership to move a housekeeper to that area from one where there are less requests for clean. ...
Background and Objective
With the recent advances in the Internet of Things (IoT), the field has become more and more developed in healthcare. The Internet of things will help physicians and hospital staff perform their duties comfortably and intelligently. With the latest advanced technologies, most of the challenges of using IoT have been resolved, and this technology can be a great revolution and has many benefits in the future of digital. Healthcare is one of the most useful areas for IoT use. The most important application of IoT is to monitor and make quick decisions in critical situations. Thanks to this technology-based treatment approach, there is an unprecedented opportunity to better the quality and productivity of treatments and better the patient's well-being and better government funding.
Methods
In this paper, we provide a comprehensive overview of the primary uses of IoT in healthcare. We used the Systematic Literature Review (SLR) method to analyze and comparison articles published in this field between 2015 and March 2020.
Results
A comprehensive taxonomy is presented based on the contents of the articles under study. In this article, a brief overview of selected articles based on research questions is given and highlights the most critical challenges and case studies for the future use of IoT in healthcare.
Conclusions
According to a detailed study of the 89 articles and a glimpse into about 208 articles, challenges and future trends in healthcare have been identified.
The emergence of the Internet of Things involves new services in healthcare while existing systems will have to interact with the IoT framework in order to integrate in the established ecosystem and use its infrastructure and services. It will be important to design appropriate interfaces for those systems that will take into consideration the unique characteristics of healthcare. We propose an interface design that allows users to efficiently interact with smart objects of a healthcare platform. The notion of a wearable cloud is introduced which connects all sensors of a Body Area Network into a unified interface, managed by a single device, while context aware computing methods personalize the system behavior and natural interaction methods are integrated.
The Internet of Things (IoT) makes smart objects the ultimate building blocks in the development of cyber-physical smart pervasive frameworks. The IoT has a variety of application domains, including health care. The IoT revolution is redesigning modern health care with promising technological, economic, and social prospects. This paper surveys advances in IoT-based health care technologies and reviews the state-of-the-art network architectures/platforms, applications, and industrial trends in IoT-based health care solutions. In addition, this paper analyzes distinct IoT security and privacy features, including security requirements, threat models, and attack taxonomies from the health care perspective. Further, this paper proposes an intelligent collaborative security model to minimize security risk; discusses how different innovations such as big data, ambient intelligence, and wearables can be leveraged in a health care context; addresses various IoT and eHealth policies and regulations across the world to determine how they can facilitate economies and societies in terms of sustainable development; and provides some avenues for future research on IoT-based health care based on a set of open issues and challenges.
There's a widely known need to revise current forms of healthcare provision. Of particular interest are sensing systems in the home, which have been central to several studies. This article presents an overview of this rapidly growing body of work, as well as the implications for machine learning, with an aim of uncovering the gap between the state of the art and the broad needs of healthcare services in ambient assisted living. Most approaches address specific healthcare concerns, which typically result in solutions that aren't able to support full-scale sensing and data analysis for a more generic healthcare service, but the approach in this article differs from seamlessly linking multimodel data-collecting infrastructure and data analytics together in an AAL platform. This article also outlines a multimodality sensor platform with heterogeneous network connectivity, which is under development in the sensor platform for healthcare in a residential environment (SPHERE) Interdisciplinary Research Collaboration (IRC).
Despite the proliferation of Internet-of-Things (IoT) platforms for building and deploying IoT applications in the cloud, there is still no easy way to integrate heterogeneous geographically and administratively dispersed sensors and IoT services in a semantically interoperable fashion. In this paper we provide an overview of the OpenIoT project, which has developed and provided a first-of-kind open source IoT platform enabling the semantic interoperability of IoT services in the cloud. At the heart of OpenIoT lies the W3C Semantic Sensor Networks (SSN) ontology, which provides a common standards-based model for representing physical and virtual sensors. OpenIoT includes also sensor middleware that eases the collection of data from virtually any sensor, while at the same time ensuring their proper semantic annotation. Furthermore, it offers a wide range of visual tools that enable the development and deployment of IoT applications with almost zero programming. Another key feature of OpenIoT is its ability to handle mobile sensors, thereby enabling the emerging wave of mobile crowd sensing applications. OpenIoT is currently supported by an active community of IoT researchers, while being extensively used for the development of IoT applications in areas where semantic interoperability is a major concern.
The new era of mobile health ushered in by the wide adoption of ubiquitous computing and mobile communications has brought opportunities for governments and companies to rethink their concept of healthcare. Simultaneously, the worldwide urbanization process represents a formidable challenge and attracts attention toward cities that are expected to gather higher populations and provide citizens with services in an efficient and human manner. These two trends have led to the appearance of mobile health and smart cities. In this article we introduce the new concept of smart health, which is the context-aware complement of mobile health within smart cities. We provide an overview of the main fields of knowledge that are involved in the process of building this new concept. Additionally, we discuss the main challenges and opportunities that s-Health would imply and provide a common ground for further research.
Pervasive healthcare applications utilizing body sensor networks generate a vast amount of data that need to be managed and stored for processing and future usage. Cloud computing among with the Internet of Things (IoT) concept is a new trend for efficient managing and processing of sensor data online. This paper presents a platform based on Cloud Computing for management of mobile and wearable healthcare sensors, demonstrating this way the IoT paradigm applied on pervasive healthcare.
This paper proposes the Internet of Things communication framework as the main enabler for distributed worldwide health care applications. Starting from the recent availability of wireless medical sensor prototypes and the growing diffusion of electronic health care record databases, we analyze the requirements of a unified communication framework. Our investigation takes the move by decomposing the storyline of a day in Robert's life, our unlucky character in the not so far future, into simple processes and their interactions. Subsequently, we devise the main communication requirements for those processes and for their integration in the Internet as web services. Finally, we present the Internet of Things protocol stack and the advantages it brings to health care scenarios in terms of the identified requirements.
A new paradigm for ubiquitous healthcare characterized by pervasive continuous vital sign data collection, real-time processing of monitored data to derive meaningful physiological parameters, and context-aware data- and patient-centric decision making, is central to deliver personalized healthcare solutions to the elderly and the physically challenged. However, this new paradigm requires real-time processing of wirelessly collected vital signs using inherently complex physiological models and analysis of the processed information under context (e.g., location, ambient conditions, current physical activity) to extract knowledge about the health condition of patients. As the computational capabilities of biomedical sensor nodes are insufficient to run these models, this article presents an innovative resource provisioning framework that organizes and harnesses the computing capabilities of under-utilized electronic devices in the vicinity (e.g., laptops, tablets, PDAs, DVRs, medical terminals) in home and hospital settings. Novel wireless communication solutions for reliable vital sign transmission and algorithms for acquiring context awareness to support this framework are also discussed.
As we are moving towards the Internet of Things (IoT), the number of sensors
deployed around the world is growing at a rapid pace. Market research has shown
a significant growth of sensor deployments over the past decade and has
predicted a significant increment of the growth rate in the future. These
sensors continuously generate enormous amounts of data. However, in order to
add value to raw sensor data we need to understand it. Collection, modelling,
reasoning, and distribution of context in relation to sensor data plays
critical role in this challenge. Context-aware computing has proven to be
successful in understanding sensor data. In this paper, we survey context
awareness from an IoT perspective. We present the necessary background by
introducing the IoT paradigm and context-aware fundamentals at the beginning.
Then we provide an in-depth analysis of context life cycle. We evaluate a
subset of projects (50) which represent the majority of research and commercial
solutions proposed in the field of context-aware computing conducted over the
last decade (2001-2011) based on our own taxonomy. Finally, based on our
evaluation, we highlight the lessons to be learnt from the past and some
possible directions for future research. The survey addresses a broad range of
techniques, methods, models, functionalities, systems, applications, and
middleware solutions related to context awareness and IoT. Our goal is not only
to analyse, compare and consolidate past research work but also to appreciate
their findings and discuss their applicability towards the IoT.
In this paper we present a fall detection system for el-derly people. The core of the system is an intelligent sensor consisting of three accelerometers and a pro-cessor capable of analysing incoming data in real time and classifying motions events such as falls or other normal and abnormal events. The sensor is able to communicate these findings to nearby camera phones or PCs through Bluetooth for further processing. We have used the system to collect data of falls and non-falls which we have used to evaluate different algo-rithms.
The design and development of wearable biosensor systems for health monitoring has garnered lots of attention in the scientific community and the industry during the last years. Mainly motivated by increasing healthcare costs and propelled by recent technological advances in miniature biosensing devices, smart textiles, microelectronics, and wireless communications, the continuous advance of wearable sensor-based systems will potentially transform the future of healthcare by enabling proactive personal health management and ubiquitous monitoring of a patient's health condition. These systems can comprise various types of small physiological sensors, transmission modules and processing capabilities, and can thus facilitate low-cost wearable unobtrusive solutions for continuous all-day and any-place health, mental and activity status monitoring. This paper attempts to comprehensively review the current research and development on wearable biosensor systems for health monitoring. A variety of system implementations are compared in an approach to identify the technological shortcomings of the current state-of-the-art in wearable biosensor solutions. An emphasis is given to multiparameter physiological sensing system designs, providing reliable vital signs measurements and incorporating real-time decision support for early detection of symptoms or context awareness. In order to evaluate the maturity level of the top current achievements in wearable health-monitoring systems, a set of significant features, that best describe the functionality and the characteristics of the systems, has been selected to derive a thorough study. The aim of this survey is not to criticize, but to serve as a reference for researchers and developers in this scientific area and to provide direction for future research improvements.
This paper presents a robust location-aware activity recognition approach for establishing ambient intelligence applications in a smart home. With observations from a variety of multimodal and unobtrusive wireless sensors seamlessly integrated into ambient-intelligence compliant objects (AICOs), the approach infers a single resident's interleaved activities by utilizing a generalized and enhanced Bayesian Network fusion engine with inputs from a set of the most informative features. These features are collected by ranking their usefulness in estimating activities of interest. Additionally, each feature reckons its corresponding reliability to control its contribution in cases of possible device failure, therefore making the system more tolerant to inevitable device failure or interference commonly encountered in a wireless sensor network, and thus improving overall robustness. This work is part of an interdisciplinary Attentive Home pilot project with the goal of fulfilling real human needs by utilizing context-aware attentive services. We have also created a novel application called ldquoActivity Maprdquo to graphically display ambient-intelligence-related contextual information gathered from both humans and the environment in a more convenient and user-accessible way. All experiments were conducted in an instrumented living lab and their results demonstrate the effectiveness of the system.
Wireless sensor networks are going to allow for ubiquitous health monitoring, improving users' well-being, the healthcare system, and helping to quickly react on emergency situations. Meeting the strict security needs of these ubiquitous medical applications is a big challenge, since safety and privacy of medical data has to be guaranteed all the way from the sensor nodes to the back-end services, the system has to fulfill latency needs, and lots of mobility is expected. In this paper, we introduce a deployment model for wireless sensor networks for pervasive healthcare based on the concepts of patient area networks and medical sensor networks, and propose a complete and efficient security framework for them. Our security framework is organized into three layers, addressing the operational requirements and security needs at the patient area network, medical sensor network and back-end levels. We specify how these layers are interconnected with each other as well as the needed security mechanisms that allow for the efficient and practical deployment of secure pervasive healthcare systems based on wireless sensor networks.
New care models have been defined in order to manage the increasing impact of chronic conditions. These models pose several technology-oriented challenges for home-based continuous care, requiring assistance services based on collaboration among different stakeholders: health operators, patient relatives, as well as social community members. This work describes an ontology-based context model and a related context management middleware providing a reusable and extensible application framework for monitoring and assisting patients at home. It provides flexible instruments for patient health status and social context representation, as well as reasoning mechanisms for alarm situation handling.
Remote ambulatory monitoring is widely seen as playing a key part in addressing the impending crisis in health care provision. We describe two mobile health solutions, one developed in the Netherlands and one in Australia. In both cases a patient’s biosignals are measured by means of a body sensor network which communicate wirelessly with a handheld device. Alarms and biosignals can be transmitted over wireless communication links to a remote location, and a remote health professional can view the biosignal data via a web portal. Both systems are undergoing commercialisation. The clinical purposes are similar, however the technological approaches differ in some respects. We compare the two approaches, present a generic architecture for healthcare sensor network systems and discuss the experience gained working with a number of different patient groups and clinical specialties during patient trials in Europe and Australia.
Continuous care models for chronic diseases pose several technology-oriented challenges for home-based continuous care, where assistance services rely on a close collaboration among different stakeholders such as health operators, patient relatives, and social community members. Here we describe Emilia Romagna Mobile Health Assistance Network (ERMHAN) a multichannel context-aware service platform designed to support care networks in cooperating and sharing information with the goal of improving patient quality of life. In order to meet extensibility and flexibility requirements, this platform has been developed through ontology-based context-aware computing and a service oriented approach. We also provide some preliminary results of performance analysis and user survey activity.
Over the last few years, the convincing forward steps in the development of Internet of Things (IoT)-enabling solutions are spurring the advent of novel and fascinating applications. Among others, mainly radio frequency identification (RFID), wireless sensor network (WSN), and smart mobile technologies are leading this evolutionary trend. In the wake of this tendency, this paper proposes a novel, IoT-aware, smart architecture for automatic monitoring and tracking of patients, personnel, and biomedical devices within hospitals and nursing institutes. Staying true to the IoT vision, we propose a smart hospital system (SHS), which relies on different, yet complementary, technologies, specifically RFID, WSN, and smart mobile, interoperating with each other through a Constrained Application Protocol (CoAP)/IPv6 over low-power wireless personal area network (6LoWPAN)/representational state transfer (REST) network infrastructure. The SHS is able to collect, in real time, both environmental conditions and patients' physiological parameters via an ultra-low-power hybrid sensing network (HSN) composed of 6LoWPAN nodes integrating UHF RFID functionalities. Sensed data are delivered to a control center where an advanced monitoring application (MA) makes them easily accessible by both local and remote users via a REST web service. The simple proof of concept implemented to validate the proposed SHS has highlighted a number of key capabilities and aspects of novelty, which represent a significant step forward compared to the actual state of the art.
Recent vehicular networking activities include public vehicle to vehicle/infrastructure (V2X) large scale deployment, machine-to-machine (M2M) integration scenarios and more automotive applications. eHealth is about the use of the Internet to disseminate health related information, and is one of the promising Internet of Things (IoT) applications. Combining vehicular networking and eHealth to record and transmit a patient's vital signs is a special telemedicine application that helps hospital resident health professionals to optimally prepare the patient's admittance. From the automotive perspective, this is a typical Vehicle-to-Infrastructure (V2I) communication scenario. This proposal provides an IPv6 vehicular platform which integrates eHealth devices and allows sending captured health-related data to a Personal Health Record (PHR) application server in the IPv6 Internet. The collected data is viewed remotely by a doctor and supports a diagnostic decision. This paper introduces the integration of vehicular and eHealth testbeds, describes related work and presents a lightweight auto-configuration method based on a DHCPv6 extension to provide IPv6 connectivity for resource constrained devices.
This works describes the system LAURA which provides patient localization, tracking and monitoring services within nursing institutes through a wireless sensor network. The system is composed of three functional blocks: a localization and tracking engine which performs localization out of samples of the received signal strength and tracking through a particle filter; a personal monitoring module based on bi-axial accelerometers which classifies the movements of the patients eventually detecting hazardous situations, and a wireless communication infrastructure to deliver the information remotely. The paper comments on the design and dimensioning of the building blocks. Two approaches are proposed to the implementation of the localization and tracking engine: a centralized implementation where localization is executed centrally out of information collected locally, and a distributed solution where the localization is performed at the mobile nodes and the outcome is delivered to the central controller. Strengths and weaknesses of the two solutions are highlighted from a system’s perspective in terms of localization accuracy, energy efficiency and traffic loads. LAURA modules are finally tested in a real environment using commercial hardware. The main outcomes are an average localization error lower than 2 m in 80% of the cases and a movements classification accuracy as high as 90%.
The term “Internet-of-Things” is used as an umbrella keyword for covering various aspects related to the extension of the Internet and the Web into the physical realm, by means of the widespread deployment of spatially distributed devices with embedded identification, sensing and/or actuation capabilities. Internet-of-Things envisions a future in which digital and physical entities can be linked, by means of appropriate information and communication technologies, to enable a whole new class of applications and services. In this article, we present a survey of technologies, applications and research challenges for Internet-of-Things.
Becoming mature enough to be used for improving the quality of life, wireless sensor network technologies are considered as one of the key research areas in computer science and healthcare application industries. The pervasive healthcare systems provide rich contextual information and alerting mechanisms against odd conditions with continuous monitoring. This minimizes the need for caregivers and helps the chronically ill and elderly to survive an independent life, besides provides quality care for the babies and little children whose both parents have to work. Although having significant benefits, the area has still major challenges which are investigated in this paper. We provide several state of the art examples together with the design considerations like unobtrusiveness, scalability, energy efficiency, security and also provide a comprehensive analysis of the benefits and challenges of these systems.
The Body Area Network (BAN) concept enables wireless communication between several miniaturized, intelligent Body Sensor (or actor) Units (BSU) and a single Body Central Unit (BCU) worn at the human body. A separate wireless transmission link from the BCU to a network access point--using different technology--provides for online access to BAN data via usual network infrastructure. BAN is expected to become a basic infrastructure element for service-based electronic health assistance: By integrating patient-attached sensors and control of mobile dedicated actor units, the range of medical workflow can be extended by wireless patient monitoring and therapy support. Beyond clinical use, professional disease management environments, and private personal health assistance scenarios (without financial reimbursement by health agencies/insurance companies), BAN enables a wide range of health care applications and related services.
Health care systems will integrate new computing paradigms in the coming years. Context-awareness computing is a research field which often refers to health care as an interesting and rich area of application.
Through a survey of the research literature, we intended to derive an objective view of the actual dynamism of context awareness in health care, and to identify strengths and weaknesses in this field.
After discussing definitions of context, we proposed a simple framework to analyse and characterize the use of context through three main axes. We then focused on context-awareness computing and reported on the main teams working in this area. We described some of the context-awareness projects in health care. A deeper analysis of the hospital-based projects demonstrated the gap between recommendations expressed for modelling context awareness and the actual use in a prototype. Finally, we identified pitfalls encountered in this area of research.
A number of opportunities remain for this evolving field of research. We found relatively few groups with such a specific focus. As yet there is no consensus as to the most appropriate models or attributes to include in context awareness. We conclude that a greater understanding of which aspects of context are important in a health care setting is required; the inherent sociotechnical nature of context-aware applications in health care; and the need to draw on a number of disciplines to conduct this research.
Context reasoning refers to the process of giving high-level context deduction from a set of low-level contexts. It plays an indispensable role in ubiquitous computing. Most existing reasoning methods are proposed with the assumption that the knowledge of low-level context which is relevant to the given high- level context reasoning is available. When this information is lack, the existing methods blindly select some possible low-level contexts for reasoning, so that useless context might be included. These useless contexts have no or little favorable effect for reasoning and increase computation burden as well as repository burden. To deal with this problem, we use information gain-based method for context selection in our work. Only selected contexts are used for reasoning. Experimental results show that our proposed approach is promising.
. The proliferation ofcomputing into the physical world promises more than the ubiquitous availability of computing infrastructure; it suggests new paradigms of interaction inspired by constant access to information and computational capabilities. For the past decade, applicationdriven research in ubicomp has pushed three interaction themes: natural interfaces, context-aware applications, and automated capture and access. To chart a course for future research in ubiquitous computing, we review the accomplishments of these efforts and point to remaining research challenges. Research in ubiquitous computing implicitly requires addressing some notion of scale; whether in the number and type of devices, the physical space of distributed computing or the number of people using a system. We posit a new area of applications research, everyday computing, focussed on scaling interaction with respect to time. Just as pushing the availability of computing away from the traditional desktop fun...
A Framework for Context-Aware Pervasive Computing Applications Computer Science, School of Information Technology and Electrical Engineering, The University of Queensland
- K Henricksen