A Multi-Agent Care System to Support Independent Living

Kaluža, Boštjan; Cvetković, Božidara; Dovgan, Erik; Gjoreski, Hristijan; Gams, Matjaž; Luštrek, Mitja; Mirchevska, Violeta

doi:10.1142/s0218213014400016

Cited by 23 publications

(8 citation statements)

References 30 publications

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“…The agent paradigm has been successfully employed in healthcare in various cases [37], with applications spanning from decision support systems [69], disease monitoring [70], telehealth services [71], ambient intelligence and independent living [72], integration of heterogeneous biomedical systems [73], cross-organisational workflow management [74], planning and resource allocation [75], to evaluation of medical systems [76]. Via this work, we illustrate a new application domain of agent technologies in life sciences, i.e.…”

Section: Related Workmentioning

confidence: 99%

A Multiagent System for Integrated Detection of Pharmacovigilance Signals

Koutkias

Jaulent

2015

J Med Syst

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Pharmacovigilance is the scientific discipline that copes with the continuous assessment of the safety profile of marketed drugs. This assessment relies on diverse data sources, which are routinely analysed to identify the so-called "signals", i.e. potential associations between drugs and adverse effects, that are unknown or incompletely documented. Various computational methods have been proposed to support domain experts in signal detection. However, recent comparative studies illustrated that current methods exhibit high false-positive rates, significantly variable performance across different datasets used for analysis and events of interest, but also complementarity in their outcomes. In this regard, in order to reinforce accurate and timely signal detection, we elaborated through an agent-based approach towards systematic, joint exploitation of multiple heterogeneous signal detection methods, data sources and other drug-related resources under a common, integrated framework. The approach relies on a multiagent system operating based on a collaborative agent interaction protocol, aiming to implement a comprehensive workflow that comprises of method selection and execution, as well as outcomes' aggregation, filtering, ranking and annotation. This paper presents the design of the proposed multiagent system, discusses implementation issues and demonstrates the applicability of the proposed solution in an example signal detection scenario. This work constitutes a step towards large-scale, integrated and knowledge-intensive computational signal detection.

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Section: Related Workmentioning

confidence: 99%

A Multiagent System for Integrated Detection of Pharmacovigilance Signals

Koutkias

Jaulent

2015

J Med Syst

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“…Kim [ 32 ] proposes a methodology for the design and implementation of convergence mobile agents to develop ubiquitous healthcare (u-healthcare) systems. Kaluža [ 33 ] reveals an MAS that aids elderly people, preventing falls and pointing out health problems through an intelligent environment enriched by sensors.…”

Section: Related Workmentioning

confidence: 99%

The Next Generation of Interoperability Agents in Healthcare

Cardoso

Marins

Portela

et al. 2014

IJERPH

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Interoperability in health information systems is increasingly a requirement rather than an option. Standards and technologies, such as multi-agent systems, have proven to be powerful tools in interoperability issues. In the last few years, the authors have worked on developing the Agency for Integration, Diffusion and Archive of Medical Information (AIDA), which is an intelligent, agent-based platform to ensure interoperability in healthcare units. It is increasingly important to ensure the high availability and reliability of systems. The functions provided by the systems that treat interoperability cannot fail. This paper shows the importance of monitoring and controlling intelligent agents as a tool to anticipate problems in health information systems. The interaction between humans and agents through an interface that allows the user to create new agents easily and to monitor their activities in real time is also an important feature, as health systems evolve by adopting more features and solving new problems. A module was installed in Centro Hospitalar do Porto, increasing the functionality and the overall usability of AIDA.

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“…The percentage of persons aged 65 or over in developed countries is projected to rise from 7.5% in 2009 to 16% in 2050 [1]. This is driving the development of innovative ambient assisted living (AAL) technologies to help the elderly live independently for longer and with minimal support from the working-age population [2,3,4]. To provide timely and proper assistance, AAL systems must understand the user's situation and context, making activity recognition (AR) an essential component [5,6,7].…”

Section: Introductionmentioning

confidence: 99%

Telehealth using ECG sensor and accelerometer

Gjoreski

Rashkovska

Kozina

et al. 2014

2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)

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-The increasing size of the elderly population is driving the development of ambient assisted living systems and telehealth. The recognition of the user's everyday activities and detection of alarming situations are important components of such systems. Moreover, the monitoring of vital signs, like the ECG, has a key role in telecare and telemonitoring systems. Therefore, in this paper we propose a system that monitors the user by combining an ECG sensor and two accelerometers. Our system recognizes the user's activities and detects falls using the accelerometer data. The ECG data is analyzed in order to extract relevant physiological signals: heart rate, respiration rate, etc. In order to improve the reliability and robustness of the system, the measured accelerometer signals can be combined with the ECG signal in order to detect anomalies in the user's behavior and heart-related problems. The proposed proof-of-concept system could contribute significantly to the quality, unobtrusiveness and robustness of the health care and patient safety.

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A Multi-Agent Care System to Support Independent Living

Cited by 23 publications

References 30 publications

A Multiagent System for Integrated Detection of Pharmacovigilance Signals

A Multiagent System for Integrated Detection of Pharmacovigilance Signals

The Next Generation of Interoperability Agents in Healthcare

Telehealth using ECG sensor and accelerometer

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