Ontology-based healthcare context information model to implement ubiquitous environment

To establish real u-healthcare environments, it is necessary to receive the context information obtained from various platforms at the proper time in portable devices which operate using both wired and wireless communication. Moreover, a knowledge model is required that reflects the information and characteristics needed for such services while remaining appropriate for medical reference. This paper develops an ontology-based healthcare context information model to implement a ubiquitous environment. Contextual information will be extracted and classified to implement the healthcare services using the context information model. The healthcare context information model can be defined using the ontology, and a common healthcare model will be developed by considering medical references and service environments. Application and healthcare service developers can use the sensed information in various environments by authoring device- and space-specific ontologies based on this common ontology. In addition, this paper designs a personalized u-healthcare service system. The validity of the model used in this study is evaluated for the food and exercise recommendation in u-healthcare services.     

Smart health: Big data enabled health paradigm within smart cities

In the era of “big data”, recent developments in the area of information and communication technologies (ICT) are facilitating organizations to innovate and grow. These technological developments and wide adaptation of ubiquitous computing enable numerous opportunities for government and companies to reconsider healthcare prospects. Therefore, big data and smart healthcare systems are independently attracting extensive attention from both academia and industry. The combination of both big data and smart systems can expedite the prospects of the healthcare industry. However, a thorough study of big data and smart systems together in the healthcare context is still absent from the existing literature. The key contributions of this article include an organized evaluation of various big data and smart system technologies and a critical analysis of the state-of-the-art advanced healthcare systems. We describe the three-dimensional structure of a paradigm shift. We also extract three broad technical branches (3T) contributing to the promotion of healthcare systems. More specifically, we propose a big data enabled smart healthcare system framework (BSHSF) that offers theoretical representations of an intra and inter organizational business model in the healthcare context. We also mention some examples reported in the literature, and then we contribute to pinpointing the potential opportunities and challenges of applying BSHSF to healthcare business environments. We also make five recommendations for effectively applying `BSHSF to the healthcare industry. To the best of our knowledge, this is the first in-depth study about state-of-the-art big data and smart healthcare systems in parallel. The managerial implication of this article is that organizations can use the findings of our critical analysis to reinforce their strategic arrangement of smart systems and big data in the healthcare context, and hence better leverage them for sustainable organizational invention.     

Exploring context-awareness for ubiquitous computing in the healthcare domain

Ubiquitous technologies have potentials to play major roles in different real world organizational settings. One of the areas where applying ubiquitous technologies has been given a lot of attention is in the healthcare domain. Here, users are frequently on the move while at the same time relying increasingly on centralized computerized information. In this paper, we explore ubiquitous technologies in the real world through two studies in the healthcare domain. First, we look at the use and usability of a ubiquitous electronic patient record (EPR) system distributed on desktop and laptop computers throughout a large hospital. Secondly, we present an extension to this ubiquitous computing environment in the form of a context-aware mobile computer terminal prototype. The usability of the mobile EPR prototype was evaluated in both laboratory and field settings. Our results indicate that the usefulness of a ubiquitous computing environment supporting work activities in healthcare can benefit from context-aware mobile information access. However, interaction design for such systems must be carefully thought out and thoroughly evaluated. Also, while the use of mobile and stationary computers complement each other very well, we found that the usefulness of ubiquitous computing environments in healthcare may benefit from additional elements such as situated displays at key locations and on key objects, and from seamless integration between the different devices comprising the system as a whole.     

Interactive middleware architecture for lifelog based context awareness

Due to the development of IT convergence, a wide variety of information is being produced and distributed rapidly in digital form. Lifelog based context awareness is a technology that provides a service automatically based on perceived situational information in ubiquitous environments. To offer customized services to users, the technology of acquiring lifelog based context information in real time is the most important consideration. We propose the interactive middleware architecture for lifelog based context awareness in distributed and ubiquitous environments. Conventional middleware to support ubiquitous environments stores and manages the situational information and service content acquired by centralized storage or a DBMS. Centralized situational information and service content management may impede the autonomy of mobile nodes and the interoperation between different middle software. The proposed method designs a system that can distribute and manage situational information in mobile nodes using mobile devices in distributed and ubiquitous environments and share the service content between interactive middleware through publication. The application system designed in this study was used in a scenario providing situational perception based mobile service and proved to be useful.     

普适计算环境下基于构件化中间件的上下文管理技术研究

上下文相关技术已经成为普适计算环境中用于应用服务的不可或缺的核心技术之一。对于基于构件的中间件来说,对高性能的上下文管理的需求更是必不可少,因为它构成了普适计算环境中构件适配和部署的重要基础。因此,在已有构件中间件的基础上,我们针对普适计算环境的特点提出了一种整体的上下文管理方法,将上下文管理集成在已有的构件化中间件中。应用表明,该方法能够更好地支持普适计算环境下上下文相关的构件化应用开发。     

基于上下文感知的普适服务框架

为了更好地适应用户的个性化需求和普适计算环境的特征,提出一种基于上下文感知的普适服务框架。该框架包括服务呈现层、服务管理层、服务提供层和上下文感知层。通过基于社区的服务管理方式来屏蔽普适计算环境中服务的异构性、分布性,动态地感知与当前计算环境和用户活动相关的上下文信息,采用基于上下文的服务推荐机制为用户提供个性化的服务,从而更好地适应人的意图和环境 因素。     

Accurate monitoring of human physical activity levels for medical diagnosis and monitoring using off-the-shelf cellular handsets

Numerous laboratory-based studies have been reported on the use of accelerometry for gait and activity analysis particularly among cohorts of elderly subjects. A drawback of such studies is the use of custom hardware platforms worn by subjects. This paper introduces a system solely utilizing accelerometers embedded in off-the-shelf cellular handsets that allow medical professionals and caregivers to remotely monitor the activity characteristics of elderly patients in the home or in the community. The use of ubiquitous cellular handsets makes the system far more acceptable to patients and enables the use of the system to be extended beyond healthcare facilities into the home environment. Mobile handset power consumption issues and other relevant handset and mobile handset application characteristics have been investigated in the context of the deployment of the proposed system.     

普适计算中动态和语义的安全策略管理

普适计算环境是信息空间与物理空间的融合,存在着既要实现信息高度共享和协作,又要保证安全隐私之间的矛盾。该文提出普适计算环境中动态的、语义的安全策略管理机制。引入统一的本体知识库,根据上下文的变化,通过本体服务动态调整策略服务和事件服务,实现策略的动态执行。描述该机制的策略管理框架、策略动态执行和策略规范。通过普适计算的典型应用场景,分析和说明如何应用该机制。     

Comparative study of three training methods for enhancing process control performance: Emphasis shift training,situation awareness training,and drill and practice

Three training methods to improve attention management skills in process control were compared. Forty students from technical disciplines participated in a five-hour module of emphasis shift training (EST), EST combined with situation awareness training (EST/SA), and drill and practice (D&P) on a simulated process control task. Participants were then tested three times for 45 min each (immediately after training, two weeks after training, and six weeks after training) for system control performance and diagnostic performance on familiar and nonfamiliar fault states. D&P led to superior diagnostic performance on familiar system faults. EST/SA training supported the diagnosis of novel system faults. EST was less effective than expected for system control performance. Implications for training design in process control are discussed.     

The effects of ubiquitous healthcare service on the south Korean Economy: using input–output analysis

Due to the rapid market penetration of smartphones and the development of context-aware ubiquitous healthcare services, the demand for ubiquitous healthcare service—to monitor patients’ longitudinal health data continuously and cope with emergency situations—has rapidly increased. Recent developments have suggested that researchers need to provide policy-makers with accessible and reliable information regarding the role of ubiquitous healthcare services. The objective of this study is to investigate the impact of ubiquitous healthcare services on the South Korean economy, using a static input–output approach. We address topics relating to the input–output model, such as the demand-driven model and inter-linkage effects, and the components inherent in an unconventional input–output model, such as the supply-driven model and the Leontief price model. The results indicate that the ubiquitous healthcare industry as a final primary production sector has strong production-inducing effects, weak price ripple effects, and marginal backward and forward linkage effects. It is also found that the industry is closely related to the electric and electronic device sector and the precision machinery sector. This is largely attributable to the convergence characteristics of industries that use wireless telecommunications, as well as those of the medical and measurement device and medical service sectors.     

Building ubiquitous QoC-aware applications through model-driven software engineering

As every-day mobile devices can easily be equipped with multiple sensing capabilities, ubiquitous applications are expected to exploit the richness of the context information that can be collected by these devices in order to provide the service that is the most appropriate to the situation of the user. However, the design and implementation of such context-aware ubiquitous appplications remain challenging as there exist very few models and tools to guide application designers and developers in mastering the complexity of context information. This becomes even more crucial as context is by nature imperfect. One way to address this issue is to associate to context information meta-data representing its quality. We propose a generic and extensible design process for context-aware applications taking into account the quality of context (QoC). We demonstrate its use on a prototype application for sending flash sale offers to mobile users. We present extensive performance results in terms of memory and processing time of both elementary context management operations and the whole context policy implementing the Flash sale application. The cost of adding QoC management is also measured and appears to be limited to a few milliseconds. We show that a context policy with 120 QoC-aware nodes can be processed in less than 100 ms on a mobile phone. Moreover, a policy of almost 3000 nodes can be instantiated before exhausting the resources of the phone. This enables very rich application scenarios enhancing the user experience and will favor the development of new ubiquitous applications.     

Modelling alarm management workflow in healthcare according to IHE framework by coloured Petri Nets

Ensuring patient safety in medical device networks by managing alarms and related clinical data is a life-critical issue. The Integrating the Healthcare Enterprise (IHE) initiative emerged to discuss and solve the interoperability and integration problems among medical information systems, vendors and users in order to improve patient care and healthcare system dependability. This paper models and analyzes the IHE Alarm Communication Management by using the Unified Modelling Language and Coloured Timed Petri nets. Aiming at generality, the model does not refer to a specific healthcare context but it is based on a general scheme where the message transactions are integrated with the nurse responses. In order to show the potentialities of the model, a real case study is simulated and different scenarios with different levels of workload are analyzed. The results illustrate that the model is able to provide support for structured and comprehensive analysis of the healthcare system management.     

Hefestos: an intelligent system applied to ubiquitous accessibility

This article proposes Hefestos, an intelligent system applied to ubiquitous accessibility. This model uses ubiquitous computing concepts to manage accessibility resources for people with disabilities. Among the concepts employed, context awareness, user profiles and trails management can be highlighted. The paper proposes an ontology for accessibility and delineates scenarios of its application in everyday life of people with disabilities. Moreover, the implementation of a smart wheelchair prototype and its application in a practical experiment is described. Ten users with a range of disability degrees tried the system and filled out a survey based on the technology acceptance model. This experiment demonstrated the main functionalities and the acceptance of the system. The results showed 96 % of acceptance regarding perceived easy of use and 98 % in perceived usefulness. These results were encouraging and show the potential for implementing Hefestos in real life situations.     

基于贝叶斯网络的多Agent服务推荐机制研究

普适计算环境中的服务推荐需要满足系统异构性和移动性的要求。提出了一种基于贝叶斯网络的多Agent服务推荐机制并进行实现,将贝叶斯网络和聚类方法应用于服务推荐中,并设计了推荐模型自学习机制,充分考虑了上下文对服务推荐的影响及改进。实现系统由完成历史上下文汇集、知识训练、决策推荐和自学习功能的多个Agent构成,通过Agent之间的通信内容设计,在Agent之间建立流程控制和数据共享通道。     

A Usability Management Framework for Securing Healthcare Information System

Transformation from conventional business management systems to smart digital systems is a recurrent trend in the current era. This has led to digital revolution, and in this context, the hardwired technologies in the software industry play a significant role However, from the beginning, software security remains a serious issue for all levels of stakeholders. Software vulnerabilities lead to intrusions that cause data breaches and result in disclosure of sensitive data, compromising the organizations’ reputation that translates into, financial losses and compromising software usability as well. Most of the data breaches are financially motivated, especially in the healthcare sector. The cyber invaders continuously penetrate the E- Health data because of the high cost of the data on the dark web. Therefore, security assessment of healthcare web-based applications demands immediate intervention mechanisms to weed out the threats of cyber-attacks for the sake of software usability. The proposed disclosure is a unique process of three phases that are combined by researchers in order to produce and manage usability management framework for healthcare information system. In this most threatened time of digital era where, Healthcare data industry has borne the brunt of the highest number of data breach episodes in the last few years. The key reason for this is attributed to the sensitivity of healthcare data and the high costs entailed in trading the data over the dark web. Hence, usability management of healthcare information systems is the need of hour as to identify the vulnerabilities and provide preventive measures as a shield against the breaches. The proposed unique developed model of usability management workflow is prepared by associating steps like learn; analyze and manage. All these steps gives an all in one package for the healthcare information management industry because there is no systematic model available which associate identification to implementation steps with different evaluation steps.     

A comprehensive health assessment framework to facilitate IoT-assisted smart workouts: A predictive healthcare perspective

Enormous potential of Internet of Things (IoT) Technology has made it feasible to perceive and analyze real time health conditions in ubiquitous manner. Moreover, incorporation of IoT in healthcare industry has led researchers around the world to develop smart applications like mobile healthcare, health-aware recommendations, and intelligent healthcare systems. Inspired from these aspects, this research presents an intelligent healthcare framework based on IoT Technology to provide ubiquitous healthcare to person during his/her workout sessions. The intelligence of the presented framework lies with its ability to analyze real time health conditions during workouts and predict probabilistic health state vulnerability. For predictive purpose, the proposed framework indulges the utilization of Artificial Neural Network (ANN) model, which is comprised of three phases namely, monitor, learn, and predict. In addition to this, the presented framework is supported by a mathematical foundation to predict probabilistic vulnerability, in terms of Probabilistic State of Vulnerability (PSoV). In order to determine the validity and applicability of the proposed framework, experiments were performed where 5 people with different attributes are monitored for 14 days using numerous smart sensors. Results, upon comparison with various state-of-the-art techniques, depict that the proposed system is superior in performance and is highly effective in delivering healthcare services during workouts.     

Patient flow modelling and performance analysis of healthcare delivery processes in hospitals: A review and reflections

Analysis of hospital processes is essential for development of improved methods, policies and decision tools for overall performance improvement of the hospital system. Amidst the current scenario of continuously increasing healthcare costs and scarcity of resources, optimal utilization of resources without hampering the quality of care has gained importance in any country. Modelling, analysis and management of patient flows, in this context, plays a key role in performance analysis and improvement of hospital processes as appropriate modelling of patient flows may help healthcare managers make decisions related to capacity planning, resource allocation and scheduling, appointment scheduling and for making necessary changes in the process of care. The concept of patient flow and its modelling has gained much attention in healthcare management literature over past few decades. In this paper, the existing approaches pertaining to modelling of patient flows in hospital systems have been classified and critically appraised focussing on the recent advancements in order to identify future research avenues. A generic framework for patient flow modelling and performance analysis of hospital systems that may serve as a guide for the practitioners dealing with similar kinds of problems to improve healthcare delivery has also been provided.     

基于Android 和二维码的实训室管理系统的设计 与开发——以广州民航职业技术学院为例

为了方便实训室的管理,文章探讨了一种基于Android 和二维码的实训室管理系统的设计方法。该管理系统 包括手机端和PC端程序,其中手机端是基于Android 平台实现的,功能包括实训室使用情况、设备维护、安全检查和调课信息 等;PC端采用Delphi 语言实现设备维护、设备录入、数据管理和统计报表等功能。该系统在Windows XP和Android 手机上经 过测试,结果表明能有效提升实训室管理的工作效率,值得推广。     

Hybrid approach for context-aware service discovery in healthcare domain

Context-awareness computing is a research field which often refers to healthcare as an interesting and rich area of application. Context aware computing attains environments monitoring by means of sensors to provide relevant information or services according to the identified context. In particular, wireless ad hoc sensor networks for medical purposes are playing an increasing role within healthcare. Body Sensor Networks (BSN) are being designed for prophylactic and follow-up monitoring of patients in e.g. their homes, during hospitalization, and in emergencies. This work presents an integrated environment aimed at providing personalized healthcare services which appropriately meet the user?s context. Deploying the semantics embedded in web services and context models is a mandatory step in the automation of service discovery, invocation and composition. Nevertheless, in a context aware domain purely logic-based reasoning on respectively context and services may not be enough. The main idea of this work is related to enrich with qualitative representation of context underling data by means of Fuzzy Logic in order to automatically recognize the context and to consequently find the right set of healthcare services among the available ones. Semantic formalisms (e.g., OWL, OWL-S, etc.) enable the context and services modeling in terms of domain ontology concepts. On the other hand, soft computing techniques support activity of unsupervised context analysis and healthcare semantic service discovery. Goal is to define context-aware system whose quality of retrieved services relies on the acquisition of user context by means of a robust theoretical approach. Moreover, this work defines hybrid architecture which attains a synergy between the agent-based paradigm and the fuzzy modeling. Specifically, the system exploits some task oriented agents in order to achieve context recognition, services matchmaking and brokerage activities.     

Hybrid classification engine for cardiac arrhythmia cloud service in elderly healthcare management

The self-regulation ability of the elderly is largely degenerated with the age increases, and the elderly often expose to great potential hazards of heart disorders. In practice, the electrocardiography (ECG) is one of the well-known non-invasive procedures used as records of heart rhythms and diagnosis of unusual heart diseases. In this paper, we propose a healthcare management system, named CardiaGuard, which is specialized in monitoring and analysis the heart disorder events for the elderly. The CardiaGuard cloud service is an expert system designed based on the hybrid classifier implemented using support vector machine (SVM) and random tree (RT) classification algorithm. We conduct a comprehensive performance evaluation which shows the proposed hybrid classification engine are able to detect six types of cardiac disorders with higher accuracy rate than the SVM-based classifier alone. CardiaGuard poses a great solution to enhance the quality of good clinical practice on the healthcare management for the elderly in cardiology.