.

Dr Lucia Quitadamo

Marie Curie Research Fellow

School of Life & Health Sciences
Aston University
Birmingham
B4 7ET
UK

email: l.quitadamo@aston.ac.uk

Dr Lucia Quitadamo

I graduated in 2006 in Biomedical Engineering at the University of Tor Vergata, Rome Italy, with a thesis dealing in Brain-Computer Interface (BCI) systems. In 2011 I obtained my PhD in “Space Systems and Technologies” with a thesis about the modelling and standardization of BCI systems. During my PhD studies I independently designed and realized: a) a common model for the description of BCI components; b) a common file format for storing information and data; c) a common metric for the evaluation of the performances of BCI systems and tools and methodologies for their optimization.  I also developed extensive experience in the main processing and classification techniques of physiological signals (mainly EEG and MEG). In particular, I studied the properties of pre-processing techniques, spatial filtering, and linear and non-linear classification methods to improve the efficiency of BCI systems.

From 2009 to 2013 I worked as a research scientist at the Neuroelectrical Imaging and BCI laboratory, Fondazione Santa Lucia, IRCCS, Rome, Italy. I was part of the TOBI- “Tools for Brain-Computer Interaction” (European ICT Programme Project FP7-224631) project and the DECODER- "Deployment of Brain-Computer Interfaces for the Detection of Consciousness in Non-Responsive Patients" (European ICT Programme Project FP7-247919, 2010-2013) project. In the former, my contribution was devoted to the standardization aspects of the BCI; in the latter, my research aimed to develop techniques for the detection of mental states in non-responsive patients (vegetative, minimally conscious, locked-in states) by means of BCI technologies. From 2013 to 2015 I was a post-doctoral researcher at the Department of Electronic Engineering, University of Tor Vergata, Rome Italy. I was involved in the implementation of signal processing techniques and strategies for the analysis and the classification of gestures and postures for surgical application and prosthesis/device control.

In October 2015 I joined Aston University, Birmingham, UK, as a Marie Curie post-doctoral researcher. My project, called EPINET (Epileptic Networks), aims at developing and validating innovative methods to localise and characterize non-invasively functional properties of the epileptogenic zone. Once validated, the analyses methods will add value to the existing analysis platforms and the development of a database of intra and extra-cranial data will facilitate the circulation of knowledge in the European epilepsy research community.

G. Saggio, F. Riillo, L. Sbernini, L.R. Quitadamo, “Resistive flex sensors: a survey”, Smart Materials and Structures, 2015, 25(1):1-30.
 

F. Cavrini, L. Bianchi, L.R. Quitadamo, G. Saggio, " A Fuzzy Integral Ensemble Method in Visual P300 Brain-Computer Interface", Computational Intelligence and Neuroscience, 2016,9845980, 2016.

F. Riillo, L.R. Quitadamo, F. Cavrini, E. Gruppioni, C. A. Pinto, N. Cosimo Pastò, L. Sbernini, L. Albero, G. Saggio, “Optimization of EMG-based hand gesture recognition: supervised vs. unsupervised data preprocessing on healthy subjects and transradial amputees”, Biomedical Signal Porcessing and Control, 2014, 14:117-125.

G. Saggio, L.R. Quitadamo and L. Albero, “Development and Evaluation of a Novel Low-Cost Sensor-based Knee Flexion Angle Measurement System”. The Knee, 2014, 21(5):896-901.

D.E. Thompson, L.R. Quitadamo, L. Mainardi, K. R. Laghari, S. Gao, P. Kindermans, J.D. Simeral, R. Fazel-Rezai, M. Matteucci, T.H. Falk, L. Bianchi, C.A. Chestek, J. E. Huggins “Performance Measurement for Brain-Computer or Brain-Machine Interfaces: A Tutorial”. Journal of Neural Engineering, 2014, 11(3):035001.

J. Toppi, M. Risetti, L.R. Quitadamo, M. Petti, L. Bianchi, S. Salinari, F. Babiloni, F. Cincotti, D. Mattia and L. Astolfi. “Investigating the effects of a sensorimotor rhythm-based BCI training on the cortical activity elicited by mental imagery”, Journal of Neural Engineering, 2014, 11(3):035010.

M. Risetti, R. Formisano, J. Toppi, L. R. Quitadamo, L. Bianchi, L. Astolfi, F. Cincotti and D. Mattia. “On ERPs detection in disorders of consciousness rehabilitation”. Frontiers in Human Neuroscience, 2013, 7(775):1-10.

L. R. Quitadamo, M. Abbafati, G. C. Cardarilli, D. Mattia, F. Cincotti, F. Babiloni, L. Bianchi. “Evaluation of the performances of different P300 based brain–computer interfaces by means of the efficiency metric”. Journal of Neuroscience Methods, 2012, 203(2):361-8.

L. R. Quitadamo, D. Mattia, F. Cincotti, F. Babiloni, G. C. Cardarilli, M. G. Marciani and L. Bianchi. “Classification of complex tasks for Brain-Computer Interface”. International Journal of Bioelectromagnetism, 2011, vol. 8, pp. 136-138.

L. Bianchi, S. Sami, A. Hillebrand, I. P. Fawcett, L. R. Quitadamo and S. Seri, “Which Physiological Components are More Suitable for Visual ERP Based Brain-Computer Interface? A Preliminary MEG/EEG Study,” Brain Topography, 2010, 23(2):180-5.

L. R. Quitadamo, M. G. Marciani, G. C. Cardarilli and L. Bianchi. “Describing different Brain-Computer Interface systems through a unique model: a UML implementation”, Neuroinformatics, 2008, 6(2):81-96.

L. Bianchi, L. R. Quitadamo, G. Garreffa, G. C. Cardarilli and M. G. Marciani, “Performances Evaluation and Optimization of Brain-Computer Interface Systems in a copy spelling task”, IEEE Transaction on Neural Systems and Rehabilitation Engineering, 2007, 15(2):207-16.

L. Bianchi, L. R. Quitadamo, M. G. Marciani, B. Maraviglia, M. Abbafati and G. Garreffa, “How the NPX data format handles EEG data acquired simultaneously with fMRI”, Magnetic Resonance Imaging, 2007, 25(6):1011-14.

L. R. Quitadamo, M. G. Marciani and L. Bianchi. “Optimization of Brain Computer Interface systems by means of XML and BF++ Toys”, International Journal of Bioelectromagnetism, 2007, 9(3):172-84.

Book chapters

C. Guger, B. Sorger, Q. Noirhomme, L. Naci, M.M. Monti, R. Real, C.Pokorny, S. Veser, Z. Lugo, L. Quitadamo, D. Lesenfants, M. Risetti, R. Formisano, J. Toppi, L. Astolfi, T. Emmerling, L. Heine, H. Erlbeck, P. Horki, B. Kotchoubey, L. Bianchi, D. Mattia, R. Goebel, A. M. Owen , F. Pellas, G. Müller-Putz, S. Laureys, A. Kübler (2013). “Brain-computer interfaces for assessment and communication in disorders of consciousness”, Emerging Theory and Practice in Neuroprosthetics, Publisher IGIGLOBAL.

L. R. Quitadamo, D. Mattia, F. Cincotti, F. Babiloni, G. C. Cardarilli, M. G. Marciani and L. Bianchi (2009). “Standard Model, File Formats and Methods in Brain-Computer Interface Research: Why?”, Biomedical Engineering, Carlos Alexandre Barros de Mello (Ed.), ISBN: 978-953-307-013-1, InTech.