2023 - Research.com Neuroscience in Italy Leader Award
Donatella Mattia mostly deals with Electroencephalography, Brain–computer interface, Neuroscience, Human–computer interaction and Artificial intelligence. Her research on Electroencephalography focuses in particular on Brain activity and meditation. Donatella Mattia interconnects Neuroplasticity, Motor recovery and Physical medicine and rehabilitation in the investigation of issues within Brain–computer interface.
Her Neuroscience study frequently links to related topics such as GABAA receptor. Her work carried out in the field of Human–computer interaction brings together such families of science as Field, Software, The Internet and State. Coherence, Multivariate statistics, Autoregressive model and Image resolution is closely connected to Pattern recognition in her research, which is encompassed under the umbrella topic of Artificial intelligence.
Her primary areas of investigation include Electroencephalography, Brain–computer interface, Artificial intelligence, Neuroscience and Neurophysiology. The concepts of her Electroencephalography study are interwoven with issues in Cognition, Brain mapping and Audiology. Her Brain–computer interface study combines topics from a wide range of disciplines, such as Speech recognition, Physical medicine and rehabilitation and Human–computer interaction.
Donatella Mattia has included themes like Software and Simulation in her Human–computer interaction study. Her Artificial intelligence research is multidisciplinary, incorporating perspectives in Autoregressive model, Machine learning, Computer vision and Pattern recognition. Her Pattern recognition research incorporates elements of Estimator and Coherence.
Donatella Mattia mainly focuses on Brain–computer interface, Electroencephalography, Physical medicine and rehabilitation, Artificial intelligence and Rehabilitation. Her Brain–computer interface research includes elements of Speech recognition and User-centered design, Usability, Human–computer interaction. Neuroscience covers Donatella Mattia research in Electroencephalography.
Her work deals with themes such as Stroke, Neurorehabilitation, Neurofeedback, Physical therapy and Motor imagery, which intersect with Physical medicine and rehabilitation. The study incorporates disciplines such as Machine learning, Coherence and Pattern recognition in addition to Artificial intelligence. Her study in Rehabilitation is interdisciplinary in nature, drawing from both Ankle, Biofeedback, Selection and Spasticity.
Her primary scientific interests are in Brain–computer interface, Electroencephalography, Physical medicine and rehabilitation, Cognition and Interface. Donatella Mattia has researched Brain–computer interface in several fields, including State and Human–computer interaction. The study incorporates disciplines such as Neurophysiology, Stroke, Cerebellar stroke, Neural correlates of consciousness and Topology in addition to Electroencephalography.
Her studies in Physical medicine and rehabilitation integrate themes in fields like Rehabilitation, Physical therapy and User-centered design. Her Physical therapy study incorporates themes from Workload, Motor imagery and Usability. In her study, which falls under the umbrella issue of Cognition, Event-related potential, Audiology and Oddball paradigm is strongly linked to Minimally conscious state.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness.
Gianluca Borghini;Laura Astolfi;Giovanni Vecchiato;Donatella Mattia.
Neuroscience & Biobehavioral Reviews (2014)
Combining Brain-Computer Interfaces and Assistive Technologies: State-of-the-Art and Challenges.
José del R. Millán;Rüdiger Rupp;Gernot Müller-Putz;Rod Murray-Smith.
Frontiers in Neuroscience (2010)
Estimation of the cortical functional connectivity with the multimodal integration of high-resolution EEG and fMRI data by directed transfer function.
Fabio Babiloni;Febo Cincotti;Claudio Babiloni;Filippo Carducci.
Brain–computer interface boosts motor imagery practice during stroke recovery
Floriana Pichiorri;Giovanni Morone;Manuela Petti;Jlenia Toppi.
Annals of Neurology (2015)
Comparison of different cortical connectivity estimators for high-resolution EEG recordings.
Laura Astolfi;Febo Cincotti;Donatella Mattia;M. Grazia Marciani.
Human Brain Mapping (2007)
Non-invasive brain-computer interface system: towards its application as assistive technology
Febo Cincotti;Donatella Mattia;Fabio Aloise;Simona Bufalari.
Brain Research Bulletin (2008)
Thromboembolic Events in Beta Thalassemia Major: An Italian Multicenter Study
C. Borgna Pignatti;V. Carnelli;V. Caruso;F. Dore.
Acta Haematologica (1998)
Spectral EEG frontal asymmetries correlate with the experienced pleasantness of TV commercial advertisements.
Giovanni Vecchiato;Jlenia Toppi;Laura Astolfi;Fabrizio De Vico Fallani.
Medical & Biological Engineering & Computing (2011)
Using brain–computer interfaces to induce neural plasticity and restore function
Moritz Grosse-Wentrup;Donatella Mattia;Karim Oweiss.
Journal of Neural Engineering (2011)
Changes in Brain Activity During the Observation of TV Commercials by Using EEG, GSR and HR Measurements
Giovanni Vecchiato;Laura Astolfi;Fabrizio De Vico Fallani;Febo Cincotti.
Brain Topography (2010)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: