Project description
Personal Health Systems (PHS)
ARMOR is a flexible, holistic and economical monitoring tool of the brain. It diagnozes and manages epileptic seizures efficiently including possibilities for detecting premonitory signs and feedback to the patient. The tool is optimized for each patient and is tested in several case studies which evaluated it as a wide use ambulatory monitoring tool.
To develop the ARMOR tool, the projects experts managed and analysed a large number of already acquired and new multimodal and advanced technology data from brain and body activities of epileptic patients and controls (MEG, multichannel EEG, video, ECG, GSR, EMG, etc).
Novel approaches for large scale analysis (both real-time and offline) of multi-parametric streaming and archived data were being introduced to discover patterns and associations between external indicators and mental states, detect correlations among parallel observations, and identify vital signs changing significantly. Moreover methods for automatically summarizing results and efficiently managing medical data were developed in the framework of the project.
The EU funded ARMOR project will be completed in October 2014. Eight organizations of five European countries (Greece, Spain, Cyprus, Germany and UK) are involved.
Epilepsy, the propensity for recurrent, unprovoked epileptic seizures, is the most common serious neurological disorder, affecting over 50 million people worldwide. Epileptic seizures manifest with a wide variety of motor, cognitive, affective, and autonomic symptoms and signs and associated changes in the electrical activities of the brain (EEG), heart (ECG), muscles (EMG), skin (GSR), as well as changes in other important measurable biological parameters, such as respiration and blood pressure. Their recognition and full understanding is the basis for their optimal management and treatment, but presently is unsatisfactory in many respects. Epileptic seizures occur unpredictably and typically outside hospital and are often misdiagnosed as other episodic disturbances such as syncope, psychogenic and sleep disorders, with which they may co-exist, blurring the clinical presentation; on the other hand, costs of hospital evaluation are substantial, frequently without the desirable results, due to suboptimal monitoring capabilities.Reliable diagnosis requires state of the art monitoring and communication technologies providing real-time, accurate and continuous brain and body multi-parametric data measurements, suited to the patient's medical condition and normal environment and facing issues of patient and data security, integrity and privacy.In this project we will manage and analyse a large number of already acquired and new multimodal and advanced technology data from brain and body activities of epileptic patients and controls (MEG, multichannel EEG, video, ECG, GSR, EMG, etc) aiming to design ARMOR, a more holistic, personalized, medically efficient and economical monitoring system.New methods and tools will be developed for multimodal data pre-processing and fusion of information from various sources. Novel approaches for large scale analysis (both real-time and offline) of multi-parametric streaming and archived data will be introduced to discover patterns and associations between external indicators and mental states, detect correlations among parallel observations, and identify vital signs changing significantly. Moreover methods for automatically summarizing results and efficiently managing medical data will be developed. ARMOR will incorporate models derived from data analysis based on already existing communication platform solutions emphasising on security and ethical issues and performing required adaptations to meet specifications. Special effort will be devoted in areas such as data anonymization and provision of required service.ARMOR will provide flexible monitoring optimized for each patient and will be tested in several case studies and evaluated as a wide use ambulatory monitoring tool for seizures efficient diagnosis and management including possibilities for detecting premonitory signs and feedback to the patient.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciences computer and information sciences data science
- medical and health sciences basic medicine neurology epilepsy
- natural sciences computer and information sciences computer security data protection
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Programme(s)
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
FP7-ICT-2011-7
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Funding Scheme
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Coordinator
08700 IGUALADA
Spain
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.