ERMHAN: A Context-Aware Service Platform to Support Continuous Care Networks for Home-Based Assistance

Abstract

Continuous care models for chronic diseases pose several technology-oriented challenges for home-based continuous care, where assistance services rely on a close collaboration among different stakeholders such as health operators, patient relatives, and social community members. Here we describe Emilia Romagna Mobile Health Assistance Network (ERMHAN) a multichannel context-aware service platform designed to support care networks in cooperating and sharing information with the goal of improving patient quality of life. In order to meet extensibility and flexibility requirements, this platform has been developed through ontology-based context-aware computing and a service oriented approach. We also provide some preliminary results of performance analysis and user survey activity.

BDCaM: Big Data for Context-Aware Monitoring—A Personalized Knowledge Discovery Framework for Assisted Healthcare

“…Traditional context-aware systems process the low level data and perform the computation in a local server or mobile device and then forward the high level context data to the cloud [24]. But the lack of storage and power in wearable sensors and mobile devices limit them to process large volume of sensor data using decent computational methods.…”

P2Care: A dynamic peer-to-peer network for collaboration in personalized healthcare service delivery

“…Innovations in ICT technologies imposed significant changes into the healthcare domain with the development of centralized computing systems. Many research projects such as SAPHIRE [8], ERMHAN [9], CAALYX [10], CHRONIOUS [11], have proposed and implemented various telemedicine and tele-monitoring systems for managing remotely patients suffering from a single disease. With the evolution in distributed collaborative systems, various platforms were established for supporting collaboration among primary and secondary care.…”

“…The health status is correlated with the level of risk which corresponds to a set of events either notification and alarms to specific healthcare professionals or a collaborative scheme with the appropriate entities for implementing the treatment plan. There is a variety of commercial solutions and research efforts related to home monitoring, management and assistance of patients suffering from chronic diseases [2,3,9,11,40,41]. The output of the decision-making framework of the IT Healthcare Service Provider triggers the P2Care for finding and binding the appropriate available medical and paramedical professionals according to the collaborative scheme.…”

A Telemedicine System for Hostile Environments

“…habitat ontology, person and medical history ontology, equipment ontology, behavior ontology and decision ontology) are employed to initialize Bayesian networks used for recognizing which activity is most likely to be performed by the patient at a given time and in a given place. In addition, an ontology-based model has been proposed for monitoring and assisting patient at home (Paganelli et al, 2008). The proposed model consists of several ontologies describing patient domain, home domain, alarm management and the social context ontology.…”