PORTO @ 
Archivio Istituzionale della Ricerca
IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.
EnglishIn this paper, the accuracy in classifying Motor Imagery (MI) tasks for a Brain-Computer Interface (BCI) is analyzed. Electroencephalographic (EEG) signals were taken into account, notably by employing one channel per time. Four classes were to distinguish, i.e. imagining the movement of left hand, right hand, feet, or tongue. The dataset '2a' of BCI Competition IV (2008) was considered. Brain signals were processed by applying a short-time Fourier transform, a common spatial pattern filter for feature extraction, and a support vector machine for classification. With this work, the aim is to give a contribution to the development of wearable MI-based BCIs by relying on single channel EEG.
Metrological performance of a single-channel brain-computer interface based on motor imagery / Angrisani, L.; Arpaia, P.; Donnarumma, F.; Esposito, A.; Moccaldi, N.; Parvis, M.. - ELETTRONICO. - 2019-(2019), pp. 1-5. ((Intervento presentato al convegno 2019 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2019 tenutosi a Auckland, New Zeland nel 2019.
| Titolo: | Metrological performance of a single-channel brain-computer interface based on motor imagery |
| Autori: | |
| Data di pubblicazione: | 2019 |
| Abstract: | In this paper, the accuracy in classifying Motor Imagery (MI) tasks for a Brain-Computer Interfac...e (BCI) is analyzed. Electroencephalographic (EEG) signals were taken into account, notably by employing one channel per time. Four classes were to distinguish, i.e. imagining the movement of left hand, right hand, feet, or tongue. The dataset '2a' of BCI Competition IV (2008) was considered. Brain signals were processed by applying a short-time Fourier transform, a common spatial pattern filter for feature extraction, and a support vector machine for classification. With this work, the aim is to give a contribution to the development of wearable MI-based BCIs by relying on single channel EEG. |
| ISBN: | 9781538634608 |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| I2MTC_2019__Motor_Imagery_BCI.pdf | 2. Post-print / Author's Accepted Manuscript | PUBBLICO - Tutti i diritti riservati | Visibile a tuttiVisualizza/Apri | |
| Metrological performance of a single-channel Brain-Computer Interface based on Motor Imagery.pdf | 2a Post-print versione editoriale / Version of Record | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia |
http://hdl.handle.net/11583/2848086
Copyright © 2021