RESUMO
This paper describes a data-driven Decision Support System for Electroencephalography (EEG) signals acquisition, and parallel elaboration based on the integration of an Ambient Intelligent (AmI) [1] platform and a GRID enabled Infrastructure. The paper explores the analysis and design of the environment, the real-time data acquisition, the integration of the acquired data in dedicated EHR, and the EEG processing through parallel analysis algorithm available on the GRID infrastructure. After an overview of background concepts, the paper presents a brief description of the environment architecture, and a detailed analysis of the EEG algorithm. The challenge of the work presented is to effectively show how medical data can be shared and processed by exploiting the resources and capabilities of both the AmI platform and the GRID infrastructure. This particular Decision Support System, shows how it is possible to improve patient safety, quality of care, and efficiency in healthcare delivery.
Assuntos
Algoritmos , Tomada de Decisões Assistida por Computador , Eletroencefalografia/instrumentação , Eletroencefalografia/métodos , Processamento de Sinais Assistido por Computador/instrumentação , HumanosRESUMO
A trend in modern medicine is towards individualization of healthcare and, potentially, grid computing can play an important role in this by allowing sharing of resources and expertise to improve the quality of care. In this paper, we present a new test bed, the BIOPATTERN Grid, which aims to fulfil this role in the long term. The main objectives in this paper are 1) to report the development of the BIOPATTERN Grid, for biopattern analysis and bioprofiling in support of individualization of healthcare. The BIOPATTERN Grid is designed to facilitate secure and seamless sharing of geographically distributed bioprofile databases and to support the analysis of bioprofiles to combat major diseases such as brain diseases and cancer within a major EU project, BIOPATTERN (www.biopattern.org); 2) to illustrate how the BIOPATTERN Grid could be used for biopattern analysis and bioprofiling for early detection of dementia and for brain injury assessment on an individual basis. We highlight important issues that would arise from the mobility of citizens in the EU, such as those associated with access to medical data, ethical and security; and 3) to describe two grid services which aim to integrate BIOPATTERN Grid with existing grid projects on crawling service and remote data acquisition which is necessary to underpin the use of the test bed for biopattern analysis and bioprofiling.