Skip to Main Content (Press Enter)

Logo UNIRC
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Professioni
  • Persone
  • Pubblicazioni
  • Strutture
  • Attività
  • Competenze

UNI-FIND
Logo UNIRC

|

UNI-FIND

unirc.it
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Professioni
  • Persone
  • Pubblicazioni
  • Strutture
  • Attività
  • Competenze
  1. Pubblicazioni

Findings about loreta applied to high-density EEG—a review

Articolo
Data di Pubblicazione:
2020
Citazione:
Findings about loreta applied to high-density EEG—a review / Dattola, S., Morabito, F.C., Mammone, N., La Foresta, F.. - In: ELECTRONICS. - ISSN 2079-9292. - 9:4(2020), p. 660. [10.3390/electronics9040660]
Abstract:
Electroencephalography (EEG) is a non-invasive diagnostic technique for recording brain electric activity. The EEG source localization has been an area of research widely explored during the last decades because it provides helpful information about brain physiology and abnormalities. Source localization consists in solving the so-called EEG inverse problem. Over the years, one of the most employed method for solving it has been LORETA (Low Resolution Electromagnetic Tomography). In particular, in this review, we focused on the findings about the LORETA family algorithms applied to high-density EEGs (HD-EEGs), used for improving the low spatial resolution deriving from the traditional EEG systems. The results were classified according to their clinical application and some aspects arisen from the analyzed papers were discussed. Finally, suggestions were provided for future improvement. In this way, the combination of LORETA with HD-EEGs could become an even more valuable tool for noninvasive clinical evaluation in the field of applied neuroscience.
Tipologia CRIS:
1.1 Articolo in rivista
Elenco autori:
Dattola, S.; Morabito, F. C.; Mammone, Nadia; La Foresta, F.
Autori di Ateneo:
LA FORESTA Fabio
MORABITO Francesco Carlo
Mammone Nadia
Link alla scheda completa:
https://iris.unirc.it/handle/20.500.12318/58964
Link al Full Text:
https://iris.unirc.it//retrieve/handle/20.500.12318/58964/68683/2020%20Electronics%20MDPI%20-%20Findings%20about%20LORETA.pdf
Pubblicato in:
ELECTRONICS
Journal
  • Dati Generali

Dati Generali

URL

https://www.mdpi.com/2079-9292/9/4/660
  • Utilizzo dei cookie

Realizzato con VIVO | Designed by Cineca | 26.6.0.0