Coupling Clinical Decision Support System with Computerized Prescriber Order Entry and their Dynamic Plugging in the Medical Workflow System

This work deals with coupling Clinical Decision Support System (CDSS) with Computerized Prescriber Order Entry (CPOE) and their dynamic plugging in the medical Workflow Management System (WfMS). First, in this paper we argue some existing CDSS representative of the state of the art in order to emphasize their inability to deal with coupling with CPOE and medical WfMS. The multi-agent technology is at the basis of our proposition since (i) it provides natural abstractions to deal with distribution, heterogeneity and autonomy which are inherent to the previous systems (CDSS, CPOE and medical WfMS), and (ii) it introduces powerful concepts such as organizations, goals and roles useful to describe in details the coordination of the different components involved in these systems. In this paper, we also propose a Multi-Agent System (MAS) to support the coupling CDSS with CPOE. Finally, we show how we integrate the proposed MAS in the medical workflow management system which is also based on collaborating agentsComment: International Conference on Information Technology and e-services, ICITeS'12, IEEE, March 24-26,Sousse-Tunisia, 201

Fuzzy adaptive cognitive stimulation therapy generation for Alzheimer’s sufferers: Towards a pervasive dementia care monitoring platform

In this paper, we present a novel system for cognitive stimulation therapy to progressively assess cognitive impairment and emotional well-being of dementia patients in social care settings. The system assesses patients interactions and computes performance scores for different areas of cognitive stimulation. Patient interactions are initially classified into predefined performance categories through clustering of a sampled population. New personalized stimulation plans tailored to match the patient’s changing level of impairment are generated automatically through a set of fuzzy rule based systems using quantitative attributes and the overall scores of patients interactions. Therapists can redefine, evaluate and adjust the rules governing difficulty and activity levels for different stimulation areas to fine tune generated activity plans. The system can also be combined with an Internet of Things (IoT) enabled patient dialogue system for determining the affective state of participants during therapy sessions that could be used as a pervasive condition monitoring platform. Experiments consisting of therapy sessions of patients interacting with the system were performed in which the activity plans were automatically generated. Initial results showed that the system outputs were in agreement with the therapists own assessment in most of the stimulation areas. Simulation experiments were also conducted to analyse the system performance over multiple sessions. The results suggest that the system is able to adapt therapy plans overtime in response to changing levels of impairment/performance while supporting therapists to tune and evaluate therapy plans more effectively

Extending External Agent Capabilities in Healthcare Social Networks

A social health care system, such as palliative care, can be viewed as a social network of interacting patients and care providers. Each patient in the network has a set of capabilities to perform his or her intended daily tasks. However, some patients may not have the required capabilities to carry out their desired tasks. Consequently, different groups of care providers - consist of doctors, volunteers, nurses, etc.- offer the patients support by providing them with a variety of needed services. Assuming there are a cost and resource limitations for providing care within the system, where each care provider can support a limited number of patients, the problem is to find a set of suitable care providers to match the needs of the maximum number of patients. In this dissertation, we propose a novel agent-based model to address this problem by extending the agent\u27s capabilities using the benefit of the social network. Our assumption is that each agent, or patient, can cover its disabilities and perform its desired tasks through collaboration with other agents, or care providers, in the network. The goal of this work is to improve the quality of services in the network at both individual and system levels. On the one hand, an individual patient wants to maximize the quality of his/her life, while at the system level we want to achieve quality care for as many patients as possible with minimum cost. The performance and functionality of this proposed model have been evaluated based on various synthetic networks. The results demonstrate a significant reduction in the operational costs and enhancement of the service quality

Fusion system based on multi-agent systems to merge data from WSN

This paper presents an intelligent multi-agent system that is aimed at improving healthcare and assistance to elderly and dependent people in geriatric residences and at their homes. The system is based on the PANGEA multi-agent architecture, which provides a high-level framework for intelligent information fusion and management. The system makes use of wireless sensor networks and a real-time locating system to obtain heterogeneous data, and is able to provide autonomous responses according to the environment status. The high-level development of the system that extracts and stores information plays an essential role to deal with the avalanche of context data. In our case, the multi-agent system approach results satisfactorily because each agent that represents an autonomous entity with different capabilities and offers different services works collaboratively with each other. Several tests have been performed on this platform to evaluate/demonstrate its validity

Multi-Agent Information Fusion System to manage data from a WSN in a residential home

With the increase of intelligent systems based on Multi-Agent Systems (MAS) and the use of Wireless Sensor Networks (WSN) in context-aware scenarios, information fusion has become an essential part of this kind of systems where the information is distributed among nodes or agents. This paper presents a new MAS specially designed to manage data from WSNs, which was tested in a residential home for the elderly. The proposed MAS architecture is based on virtual organizations, and incorporates social behaviors to improve the information fusion processes. The data that the system manages and analyzes correspond to the actual data of the activities of a resident. Data is collected as the information event counts detected by the sensors in a specific time interval, typically one day. We have designed a system that improves the quality of life of dependant people, especially elderly, by fusioning data obtained by multiple sensors and information of their daily activities. The high development of systems that extract and store information make essential to improve the mechanisms to deal with the avalanche of context data. In our case, the MAS approach results appropriated because each agent can represent an autonomous entity with different capabilities and offering different services but collaborating among them. Several tests have been performed to evaluate this platform and preliminary results and the conclusions are presented in this paper