Coordinador
Research groups
- TICs and Emotions
- Applied Biomechanics
- Signal Interpretation
- Wireless Technologies, Security and e-Health
- Biomaterials
- Power Electronics
- Smart Environments
- Ergonomics
- Mechanobiology
- Tissue Microenvironment
- Laser Technologies
- Physiotherapy
The Biomedical Engineering Division is a clear example of the multidisciplinary approach of the I3A, bringing together specialists in Biology, Medicine, Physics, Mathematics and Engineering who cooperate to develop technological solutions that improve health and quality of life.
Today's technologies for diagnosis, monitoring, therapy, surgery and assistance to people with disabilities encompass almost all fields of engineering.
General research lines
- Biomaterials and tissue engineering
- Biological and biomechanical modelling
- Biomedical instrumentation and signal processing
- Prevention and care technologies
- Digital twins
- Personalised medicine
Keywords
Mechano-biology, biomaterials, tissue engineering, microfluidics, bioreactors, diagnostic devices, modelling of cell behaviour, microstructural behaviour of biomaterials, cardiac electrophysiology, telemedicine, automatic coding of biomedical signals, biomedical information transmission protocols, smart sensors, computer vision algorithms for human detection, activity tracking and recognition, prosthesis design, mesenchymal stem cells, neurodegenerative disease therapies, prion genomics and genetics, adapted human-machine interfaces, localisation and guidance in indoor and outdoor environments.
Projects
Translational cardioselective RNAi therapies and predictive heart-on-chip to tackle cardiac clinical challenges
In silico framework to improve the personalized prediction of progression and outcomes in thoracic and abdominal aortic aneurysms based on personalized clinical and mechanical biomarkers
To develop a computational-experimental framework to improve the prediction of the initiation, progression and final outcome of the pathology.
To validate technically and clinically novel methods to understand, and give support to tremor diagnosis.
By developing biological ventricular assist devices (BioVADs), BRAV3 will bring a quantum leap in regenerative medicine and its translation towards the clinic, as well as impact the development of novel medical technologies whilst greatly advancing our knowledge on human heart development.
Computational modeling of cell culture in dynamically adaptive multilayer microenvironment charged with drug-delivery microcapsules
Develop computational tools for the predictive analysis of key factors in the evolution of multiple myeloma and cartilage, and spinal cell growth and more...
The main objective is to develop a comprehensive methodology for the correction and treatment of mandibular asymmetries in children.
Customised DNA-based nanocarriers to boost heart healing
DNABEATS aims to bring advanced materials to regenerate injured myocardium.
Extracting the Human Motor Null Space from Muscles - A new framework to measure human neural activity
ECHOES will capitalize on recent breakthroughs in decoding the spinal outputs to muscles to develop a theoretical and experimental framework to unveil the 'motor null space' in human muscles.
, 
Predict and prevent foot pathologies related to hallux limitus and flat feet
Predict and prevent foot pathologies related to hallux limitus and flat feet
In vitro characterization and in vitro/in vivo simulation of the effect of hypoxia and drug dosis in glioblastoma growth
The in vitro and in silico study of glioblastoma multiforme (GBM) tumor is proposed.
Individual and Collective Migration of Immune Cellular Systems
ICoMICS aims to develop a novel virtual simulation platform to investigate how therapeutic immune cells (TICs) detect, move and interact with cancer cells and the tumour microenvironment.
, 
multI-discipliNary, multi-Sectoral and multi-national trainIng network on Digital biomarkErs for supraventricular arrHythmia charactErizAtion and Risk assessmenT
Establishing a multi-disciplinary network to tackle the design and the early-phase validation of digital biomarkers, specifically targeting the diagnosis of supraventricular arrhythmias (SVAs) and their associated potential for adverse risk assessment, via the joint combination of signal processing, artificial intelligence and non-clinical devices.
, 
In silico models for tendinomuscular injuries analysis using artificial intelligence techniques
To continue characterizing the in vitro mechanical properties of tissues present in the ankle joint of a mouse model and extend the study to those involved in the shoulder's rotator cuff. In the case of muscles, the active behavior will also be analyzed by inducing contraction through an external electrical signal.
Methods for Stroke Monitoring and Diagnosing based on BCG
To develop novel, non-invasive methods for detecting cardiac and non-cardiac disease in stroke patients using the ballistocardiogram (BCG) signal, allowing for patient monitoring without transfer to clinical settings
, 
COMPUTER-AIDED EFFECTIVE FRACTURE RISK STRATIFICATION OF PATIENTS WITH VERTEBRAL METASTASES FOR PERSONALISED TREATMENT THROUGH ROBUST COMPUTATIONAL MODELS VALIDATED IN CLINICAL SETTINGS
METASTRA will propose new guidelines for the stratification and management of metastatic patients. METASTRA approach is expected to cut the uncertain diagnoses from the current 60% down to 20% of cases. This will reduce patient suffering, and allow cutting expenditure by 2.4B€/year.
Mental Illness Detection and Clinical Assessment with Reliable Interpretability
This project aims to develop an open source AI based model, explainable and transparent, that can assess between many mental illnesses using voice recordings from a patient, contributing from the study, analysis and understanding of the problem, providing greater interpretability, security and extrapolation ability.
, 
To improve diagnosis and monitoring of sleep apnea-hypopnea syndrome (SAHS)
Optimisation of personalised treatments for femoral fractures using digital twins and machine learning
PELVIc Floor Evaluation live TRACKing – Real-time prediction of perineal trauma
To develop the first-ever solution to predict pelvic floor tearing
, 
Microelectronic control architectures for smart power electronic converters based on wide-gap semiconductors
Implementation and validation of a closed-loop neural interface to entrain brain rhythms and reduce motor symptoms in Parkinson's Disease
To develop a non-invasive neuromodulation platform to apply closed-loop stimulation protocols synchronized with brain oscillations decoded from the periphery with muscle recordings
, 
Translational Research and Training on Atrial Cardiomyopathy as a Key to Better Atrial Fibrillation Management
The project will train 15 researchers to address gaps in our understanding of AF, atrial cardiomyopathy (ACM) their management and consequences by integrating advanced data-driven and mechanistic computational modelling, clinical AI and wet-lab research with a focus on extended time scales of AF aetiology and progression.
Unlocking data content of Organ-On-Chips
To develop groundbreaking Organ-on-Chips (OOC) technologies to mitigate the challenges posed by use of animals in drug development and testing. Direct use of human cells is a real game changer, bridging the gender gap and allowing personalized medicine.
, 
Advanced image processing for early eye disease detection
The project will focus on extracting both macro- and microstructure biomarkers from clinical images of the retina, lens, and cornea to aid early disease detection and personalised management.
