e-Prevention

Advanced Support System for Treatment Monitoring and Relapse Prevention in Patients with Psychotic Disorders using Long Term Recording and Analysis of Biometric Indexes

Project Details

Co‐financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code:T1EDK-02890).

About the Project

The goal of the e-Prevention project is to develop innovative and advanced remote electronic services for medical support that will facilitate effective treatment monitoring and relapse prevention in patients with psychotic disorders (i.e., bipolar disorder and schizophrenia).

Overall architecture of the e-Prevention system.

e-Prevention will develop a novel intelligent system which will offer the possibility for timely diagnosis of psychotic symptom’s relapses and adverse medicine side effects by combining:

  1. long-term continuous recordings of biometric indexes through simple wearable sensors (i.e., smartwatches),
  2. a portable device (tablet) that is used to record short-term audio-visual videos of the patient while communicating with the clinical personnel on weekly basis,
  3. parallel studies, medical diagnosis and decisions taken by the psychiatric research group, and
  4. development of an intelligent data processing and recognition system, which will be based on Cloud computing and processing of large-scale (big) data, providing statistical measurements, detections and estimates of changes and patterns that will facilitate the prediction of clinical symptoms and side effects of the patient’s medication.

Visualization of biometric indexes: user movement and heart rate data, i.e., acceleration data, gyroscope data for all three axis (x, y, z-axis) and data collected by the heart rate monitor (i.e., heart rate and RR-interval data).
Example of acceleration signal.
Examples of extracted features for a single user and one day – gray area denotes sleep (first two columns). Last column: sleep-wake ratio and number of steps per day for two weeks of a user. Missing values show periods of time during which HR could not be detected.
Example of the walking diary of user #A – shown are the steps per day, as well as the effort during walking.
Example of the sleeping diary of user #A – the hours per day spent awake and asleep.
Boxplots for features of controls and patients while awake (top row) and asleep (bottom-row). The bold line represents the median, the boxes extend between the 1st and 3rd quartile, whiskers extend to the lowest and highest datum within 1.5 times the inter-quartile range (IQR) of the 1st and 3rd quartile respectively, and outliers are shown as diamonds.

Differences in steps-per-day and sleep-wake ratio for controls, and patients with psychosis.
Work Plan
  • WP1: Data collection from healthy volunteers and patients. Patient Monitoring-Treatment. Model Evaluation
  • WP2: Monitoring sensors and cloud computing infrastructure
  • WP3: Multimodal data processing for recognition of changes and trends
  • WP4: Development of the integrated e-Prevention System
  • WP5: Commercial exploitation of results

Areas / Keywords

Psychotic relapse, prevention of psychotic episode, antipsychotic medication, mood stabilized induced tremor, schizophrenia, bipolar disorder.

Signal processing, pattern recognition and machine learning, computer vision and image processing, multimodal human-computer interaction, multi-sensory processing, parallel and distributed processing, cloud systems/computer architecture, biomedical information systems.

  • National Technical University of Athens Logo
    National Technical University of Athens School of Electrical and Computer Engineering, Intelligent Robotics and Automation Laboratory (IRAL) P.I. & Scientific Director: Prof. Petros Maragos (NTUA)

    Team Prof. Panagiotis Tsanakas Prof. Ilias Maglogiannis (Dept. of Digital Systems, Univ. of Piraeus) Assoc. Prof Gerasimos Potamianos (Dept. of ECE, Univ. of Thessaly) Dr. Athanasia Zlatintsi Dr. Georgios Retsinas Dr. Andreas Menychtas Dr. Dimitra Georgiou Niki Efthymiou Panagiotis-Paraskevas Filntisis Dionisis Papadimatos Melina Tziomaka Dr. Vrettos Moulos
  • National Technical University of Athens Logo
    National Technical University of Athens Neuroscience and Medical Accuracy Mental Health Research Institute P. I.: Prof Nikolaos Smyrnis (School of Medicine, National Kapodistrian Univ. Athens)

    Team Dr. Thomas Karantinos Vasia Garyfalli, MD Manolis Kalisperakis, MD Makis Mantas, MD Marina Lazaridi
  • Blockachain Logo
    Blockachain Blockachain, a custom software engineering company, operating as a full-service software development company. Blockachain exploits modern design principles, along with the latest blockchain, cloud, mobile and desktop technologies to deliver software of best-in-class performance at affordable prices. P. I.: Thomas Sounapoglou

    Team Athanasios Gkoumas Evaggelia Mpogiatzi Gianna Papaplioura Kostas Romanidis
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