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Prof. Vasileios Megalooikonomou University of Patras , Greece

A dvanced multi- pa R ametric M onitoring and analysis for diagnosis and O ptimal management of epilepsy and R elated brain disorders. Prof. Vasileios Megalooikonomou University of Patras , Greece. Clustering Workshop: eHealth and the Brain – ICT for Neuropsychiatric Health

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Prof. Vasileios Megalooikonomou University of Patras , Greece

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  1. Advanced multi-paRametricMonitoring and analysis for diagnosis and Optimal management of epilepsy and Related brain disorders Prof. Vasileios Megalooikonomou University of Patras, Greece Clustering Workshop: eHealth and the Brain – ICT for Neuropsychiatric Health Brussels, November 5th 2013 http://www.armor-project.eu

  2. Epilepsy • a common, devastating and still incurable disorder • treatment needs continuous adjustment and change to retain its efficacy • multifactorial causes and paroxysmal nature • needs multi-parametric monitoring for: • accurate diagnosis, prediction, alerting and prevention, treatment follow-up and presurgicalevaluation http://www.armor-project.eu

  3. ARMOR’s Main Objective To 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 (multichannel EEG, ECG, GSR, EMG, respiration, acceleration, and assisting modalities such as MEG) aiming to design a more holistic, personalized, medically efficient and economical monitoring system. Flexible monitoring optimized for each patient Tested in several case-studies Ambulatory monitoring tool Possibilities for detecting premonito-ry signs Feedback to the patient http://www.armor-project.eu

  4. Scenarios http://www.armor-project.eu

  5. ARMOR General View: ICT Components Local Site / Home Gateway • Possible: • Preprocessing • Feature Extraction • Storage Possible: Occasionally retrieve raw data • Real Time: • Monitoring • Decision Support • Personalized Analysis Online Analysis DSMS Events, Alerts Mobiserv SHACU Aggregator Raw Data Local Storage Sensors Features/ Reduced Data Online Analysis results Raw Data/ Preprocessed Data Adjust Model Parameters Offline Data Processing and Management Center User Interfaces • Storage: • Sensor Data • MRI, fMRI • Patient’s Profile • Analysis Results Application Server Information Server • Offline: • Analysis • Fusion • Data Mining EHR Offline Analysis Server Local copies of data Legacy Datasets

  6. ARMOR Middleware Architecture http://www.armor-project.eu

  7. Multi-parametric Data Processing & Analysis Offline Data Processing & Analysis Analysis Pre-Processing Creation of models of different types of epilepsy Correlation Analysis Filtering Pattern Discovery • Outlier Detection Support on Decision Making Detection of Epileptic Seizures Data Transformation Detection of Events of Interest Personalized Patient Health Profiles (PHPs) Summarization/ Feature Extraction Data Fusion http://www.armor-project.eu

  8. Multi-parametric Data Processing & Analysis Online Data Processing & Analysis • Online Processing involves tasks such as: • Preprocessing • Data Fusion • Decision making • performed with respect to processing time, memory and communication constraints. • Online Analysis incorporates all necessary processing techniques adopted to the streaming nature of the data, in order to perform real-time : • Detection of Seizures • Detection of (patient-specific) abnormal values (e.g., excessive techycardia, oxygen level excursions) from several modalities • Detection of other possible emergency situations Online analysis involves results from offline analysis in order to adjust parameters according to each patient’s personal profile. Minimal Data Requirements (e.g. number of sensors) is incorporated with respect to the medical expectations and the desired levels of accuracy http://www.armor-project.eu

  9. Objectives and Achievements • Clinical/Medical • Facilitate and increase the yield of diagnostic, treatment and follow-up practice • Support health care professionals in their decision making • Reduce epilepsy related management costs; • Increase understanding of epileptic seizure, epilepsy, and other non-epileptic paroxysmal events (NEPE) • Advance the technology of Personal Health Systems (PHS) suitable for chronic diseases of multifactorial causes and unpredictable expression of their symptoms • Information and Communication Technologies • Develop novel multi-parametric data processing, management and analysis tools, both real time and off-line • Design and develop adequate measuring/monitoring methodologies and systems • Adopt and adapt prominent coordination/communication platforms providing robust and flexible end-to-end communication and assure security and privacy on sensitive medical data http://www.armor-project.eu

  10. Consortium Karlsruher Institut fuer Technologie GERMANY Sensing & Control Systems S.L SPAIN Technological Educational Institute of Western Greece GREECE University of Patras GREECE AAI Scientific Cultural Services Ltd CYPRUS King’s College London UK INTRACOM S.A. Telecom Solutions GREECE SYSTEMA Technologies S.A. GREECE http://www.armor-project.eu

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