Support for context-aware monitoring in home healthcare

Mileo, Alessandra; Merico, Davide; Bisiani, Roberto

doi:10.3233/ais-2010-0052

Cited by 39 publications

(15 citation statements)

References 36 publications

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“…In order to achieve a pervasive healthcare system for independent living [57], a context-aware monitoring system should be able to observe, interpret and reason regarding the subject's conditions including behavioural, physiological, and environmental information. In a smart home environment, the system should be able to perform actions and provide feedback to the subject according to the results of its reasoning process.…”

Section: The Architecture Of Context-aware Health Systemsmentioning

confidence: 99%

A survey on health monitoring systems for health smart homes

Mshali

Lemlouma

Moloney

et al. 2018

International Journal of Industrial Ergonomics

185

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Aging population ratios are rising significantly. Health monitoring systems (HMS) in smart environments have evolved rapidly to become a viable alternative to traditional healthcare solutions. The aim of HMS is to not only reduce costs but to also provide timely e-health services to individuals wishing to maintain their independence. In this way, elderly people can avoid, for as long as possible, any interaction with healthcare institutions (e.g. nursing homes and hospitals), which in turn reduces pressure on the health system. To fully realise this vision of seamless e-health services supporting people in need of them, a number of challenges that need further investigation still exist. To this end, we provide an overview of the current state of the art for smart health monitoring systems. We review HMS in smart environments from a general perspective and with a particular focus on systems for the elderly and dependent people. We look at the challenges for these systems from the perspective of developing the technology itself, system requirements, system design and modelling. We present a consolidated picture of the most important functions and services offered by HMS for monitoring and detecting human behaviour including its concepts, approaches, and processing techniques. Moreover, we provide an extensive, in-depth analysis and evaluation of the existing research findings in the area of e-health systems. Finally, we present challenges and open issues facing the smart HMS field and we make recommendations on how to improve future systems.

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Section: The Architecture Of Context-aware Health Systemsmentioning

confidence: 99%

A survey on health monitoring systems for health smart homes

Mshali

Lemlouma

Moloney

et al. 2018

International Journal of Industrial Ergonomics

185

View full text Add to dashboard Cite

show abstract

“…CAMAR makes use of unified user context information and allows users to view and tailor augmented information to share them with other end users [18]. Mileo et al present a context model that makes use of information from pervasive sensors placed in the environment and patient explanatory feedback as well to interpret complex collected data and reason about available knowledge using logic programming language in order to support patient well-being [19]. Byun et al employed context history beside user modeling and machine learning algorithms to provide adaptation.…”

Section: Related Workmentioning

confidence: 99%

A novel context-aware augmented reality framework for maintenance systems

Akbarinasaji

Homayounvala

2017

AIS

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Augmented Reality (AR) bridges the gap between real and virtual world by bringing virtual information to real environment as seamlessly as possible. The need for better perception of knowledge-intensive complex maintenance tasks and access to large amounts of documents and data makes the use of AR technology promising in a maintenance domain. Context-awareness enhances the usability of such AR applications, i.e. the output and behavior of the system will be adapted according to different contexts such as user location, preferences, devices, etc. to afford higher level of personalization. The adaptation needs to be efficient in terms of performance and speed. This paper presents an optimized framework which combines context-awareness and AR for training and assisting technicians in maintaining equipment in an industrial context to improve field workers effectiveness. Ontology is used to model a maintenance context and Semantic Web Rule Language (SWRL) provides logical reasoning. This optimized framework utilizes a behavior network to select suitable actions collection based on ongoing task current step and apply context-based inferred information from ontology to each member of this collection. Evaluation results comparing the performance of the proposed framework with conventional ontology alone in a maintenance domain confirmed that the proposed framework in this research provides the same results as ontology in terms of content, but it runs much faster in terms of run-time and performance. The proposed contextaware framework is quite valuable especially in case of response time and performance of maintenance systems with large number of maintenance activities.

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“…He believes that through primary context we can obtain other context information which is called "secondary context" [28]. Context in the healthcare sector can be any kind of information about different entities such as patients, caregivers, medical places, homes and others that are considered relevant to the system [29]. Different projects have used various context types in healthcare systems which can be categorized as follows (see Table 4).…”

Section: Context Typementioning

confidence: 99%

An Introduction to Cloud-Based Pervasive Healthcare Systems

Poorejbari¹,

Vahdat-Nejad²

2015

Proceedings of the 3rd International Conference on Context-Aware Systems and Applications

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The healthcare system is important due to its focus on human care and its interference with human lives. In recent years, we have witnessed a rapid rise in e-healthcare technologies such as Electronic Health Records (EHRs) and the importance of emergency detection and response. Cloud computing is one of the new approaches that can handle some of the challenges of smart healthcare in terms of security, sharing, integration and management. In this study, we review the significance and opportunities of using cloud computing in pervasive healthcare, and then look at the current as well as the future challenges it faces.

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Support for context-aware monitoring in home healthcare

Cited by 39 publications

References 36 publications

A survey on health monitoring systems for health smart homes

A survey on health monitoring systems for health smart homes

A novel context-aware augmented reality framework for maintenance systems

An Introduction to Cloud-Based Pervasive Healthcare Systems

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