Pervasive Digital Monitoring and Transmission of Pre-Care Patient Biostatics with an OSGi, MOM and SOA Based Remote Health Care System

Chen, Ing-Yi; Tsai, Chen-Hsin

doi:10.1109/percom.2008.93

Cited by 12 publications

(11 citation statements)

References 13 publications

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“…Each labeled vital sign and ECG data pass [3]to prognosis algorithm which checks different cases of medical domain to find diseases , abnormalities , prediction of heart stroke risk [2] etc. Each vital sign pass through different cases of prognosis [20] , where they are checked under medical domain for different prognosis results [13] as shown in Fig.1.Cases are predefined as age and genders.…”

Section: Metabolic Syndromementioning

confidence: 99%

Health Track

Aghav¹,

Sonawane²,

Bhambhlani³

2014

2014 International Conference on Advances in Engineering &Amp; Technology Research (ICAETR - 2014)

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The latest generation of smartphones are increasingly viewed as handheld computers rather than as phones, due to their powerful on-board computing capability, capacious memories, large screens and open operating systems that encourage application development. This paper provides a brief state-of-the-art overview of 'Health Track' smartphone app which is used with wearable biosensors for health monitoring and prognosis. In this paper, we present a system using an Android smartphone that collects, displays sensor data on the screen and streams to the central server simultaneously. Our system has Doctor, Nurse, Caretaker, User and Administrator as actors who are completely connected to each other via our Health Track modules. Raw sensor data collected from body area network are interpreted to either graphical or text notations to be presented on the smartphone and the central server. Furthermore, a PHP-based central server application is used to demonstrate communication with the Android system for data storage and analysis. Analysis section includes our prognosis algorithm, which helps to detect medical condition of user. Prognosis algorithm works on vital sign classification. Our system has classification which is based on context based health monitoring, trigger based and past records. Emergency conditions are handled by evaluating prognosis report. System provides location based emergency services.

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Section: Metabolic Syndromementioning

confidence: 99%

Health Track

Aghav¹,

Sonawane²,

Bhambhlani³

2014

2014 International Conference on Advances in Engineering &Amp; Technology Research (ICAETR - 2014)

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“…As widely described in the literature [17][18][19], telemedicine applications have to evolve dynamically in order to fulfill new requirements such as adding new health care services, updating the existing one in order to support improvements in wireless and mobile technologies, etc. This adaptability is essential to ensure that these applications remain within the functional requirements defined by application designers, as well as maintain their performance, security and safety properties.…”

Section: Case Studymentioning

confidence: 99%

“…In the literature, we have found some research works that use the Open Service Gateway initiative (OSGi) platform 3 to implement such case study [17,21]. We follow the same technology choice due its dynamism (a powerful Framework to create highly dynamic applications).…”

Section: Implementation Of Trmcs Case Studymentioning

confidence: 99%

Towards a TTCN-3 Test System for Runtime Testing of Adaptable and Distributed Systems

Lahami

Fakhfakh

Krichen

et al. 2012

Testing Software and Systems

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Abstract. Today, adaptable and distributed component based systems need to be checked and validated in order to ensure their correctness and trustworthiness when dynamic changes occur. Traditional testing techniques can not be used since they are applied during the development phase. Therefore, runtime testing is emerging as a novel solution for the validation of highly dynamic systems at runtime. In this paper, we illustrate how a platform independent test system based on the TTCN-3 standard can be used to execute runtime tests. The proposed test system is called TT4RT: TTCN-3 test system for Runtime Testing. A case study in the telemedicine field is used as an illustration to show the relevance of the proposed test system.

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“…Later on, mobile networks based on GPRS [4] [14] [15] and internet portals [16] [17] were used as new paradigms of the application of ICT in diabetes management. More recently comparative frameworks [18] have described the benefits of using mobile technologies in the management of chronic conditions and other authors have suggested the implementation of new communication architectures based on services (SOA) [19].…”

Section: Introductionmentioning

confidence: 99%