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).

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:
- long-term continuous recordings of biometric indexes through simple wearable sensors (i.e., smartwatches),
- 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,
- parallel studies, medical diagnosis and decisions taken by the psychiatric research group, and
- 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.






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
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
Melina Tziomaka
Dr. Vrettos Moulos -
University Mental Health, Neurosciences and Precision Medicine Research
Institute “COSTAS STEFANIS”
Laboratory of Cognitive Neuroscience and Sensoriomotor Control
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
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
Publications
- Person Identification Using Deep Convolutional Neural Networks On Short-term Signals From Wearable Sensors, ICASSP-2020
- An intelligent cloud-based platform for effective monitoring of patients with psychotic disorders, AIAI-2020
- Wearable-based Long-term Digital Phenotyping and Relevant Markers Identification in Patients with Mental Disorders, JBHI-2021 (Under review)
- Physical activity and autonomic function patterns between psychotic patients and controls over longitudinal wearable sensors recording, ICHI-2021 (Submitted)
- Advances in Morphological Neural Networks: Training, Pruning and Enforcing Shape Constraints, ICASSP-2021
- Sparsity in Max-Plus Algebra and Applications in Multivariate Convex, ICASSP 2021
- Tropical Modeling Of Weighted Transducer Algorithms On Graphs, ICASSP-2019
- Evaluating mental patients utilizing video analysis of facial expressions, AIAI-2021
- An Unsupervised Learning Approach for Detecting Relapses from Spontaneous Speech in Patients with Psychosis, BHI-2021