EEG analysis

Dream EEG database project

This ia a collaborative research project that we believe will be of high interest to scientific community. In brief, we will present a large number of data sets collected, or to be collected, by many different research teams of human sleep EEG and associated dream reports
on an open access platform; and we will also carry out a registered analysis of that collection. We intend for this to be a significant contribution to the fields of neuroscience, cognitive science and psychology—with potential reach to artificial intelligence, machine learning and mental health.

Informazioni

Struttura
Spin OFF
KET
Keywords
Progetti principali
Altre informazioni

Componenti del gruppo

Nome	E-mail

Collaboratori nazionali ed internazionali

Laboratori

Pubblicazioni

Brevetti

Progetti di ricerca

ERC

ERC	Descrizione

Infrastrutture

Leggi tutto su Dream EEG database project

Early diagnosis of Alzheimer's disease: the role of biomarkers including advanced EEG signal analysis. Report from the IFCN-sponsored panel of experts

Alzheimer's disease (AD) is the most common neurodegenerative disease among the elderly with a progressive decline in cognitive function significantly affecting quality of life. Both the prevalence and emotional and financial burdens of AD on patients, their families, and society are predicted to grow significantly in the near future, due to a prolongation of the lifespan.

A Patient-specific Approach for Short-term Epileptic Seizures Prediction through the Analysis of EEG synchronization

Epilepsy is a neurological disorder arising from anomalies of the electrical activity in the brain, affecting about 65 millions individuals worldwide. Objective: This work proposes a patient-specific approach for short-term prediction (i.e., within few minutes) of epileptic seizures. Methods: We use noninvasive EEG data, since the aim is exploring the possibility of developing a noninvasive monitoring/control device for the prediction of seizures. Our approach is based on finding synchronization patterns in the EEG that allow to distinguish in real time preictal from interictal states.