Vaš brskalnik ne omogoča JavaScript!
JavaScript je nujen za pravilno delovanje teh spletnih strani. Omogočite JavaScript ali pa uporabite sodobnejši brskalnik.
Nacionalni portal odprte znanosti
Odprta znanost
DiKUL
slv
|
eng
Iskanje
Brskanje
Novo v RUL
Kaj je RUL
V številkah
Pomoč
Prijava
Development of a real-time motor-imagery-based EEG brain-machine interface
ID
Gorjup, Gal
(
Avtor
),
ID
Vrabič, Rok
(
Avtor
),
ID
Petrov Stoyanov, Stoyan
(
Avtor
),
ID
Østergaard Andersen, Morten
(
Avtor
),
ID
Manoonpong, Poramate
(
Avtor
)
PDF - Predstavitvena datoteka,
prenos
(10,69 MB)
MD5: 34AE8ED7EC7469EFE5BD21B73A1EDB8A
URL - Izvorni URL, za dostop obiščite
https://link.springer.com/chapter/10.1007%2F978-3-030-04239-4_55
Galerija slik
Izvleček
EEG-based brain-machine interfaces offer an alternative means of interaction with the environment relying solely on interpreting brain activity. They can not only significantly improve the life quality of people with neuromuscular disabilities, but also present a wide range of opportunities for industrial and commercial applications. This work focuses on the development of a real-time brain-machine interface based on processing and classification of motor imagery EEG signals. The goal was to develop a fast and reliable system that can function in everyday noisy environments. To achieve this, various filtering, feature extraction, and classification methods were tested on three data sets, two of which were recorded in a noisy public setting. Results suggested that the tested linear classifier, paired with band power features, offers higher robustness and similar prediction accuracy, compared to a non-linear classifier based on recurrent neural networks. The final configuration was also successfully tested on a real-time system.
Jezik:
Angleški jezik
Ključne besede:
electroencephalography
,
brain-machine interface
,
brain-computer interface
,
motor imagery
,
digital filtering
,
feature extraction
,
classification
Vrsta gradiva:
Članek v reviji
Tipologija:
1.08 - Objavljeni znanstveni prispevek na konferenci
Organizacija:
FS - Fakulteta za strojništvo
Status publikacije:
Objavljeno
Različica publikacije:
Recenzirani rokopis
Leto izida:
2018
Št. strani:
f. 610-622
Številčenje:
Vol. 11307
PID:
20.500.12556/RUL-106471
UDK:
681.5(045)
ISSN pri članku:
1611-3349
DOI:
10.1007/978-3-030-04239-4_55
COBISS.SI-ID:
16494107
Datum objave v RUL:
26.02.2019
Število ogledov:
1681
Število prenosov:
938
Metapodatki:
Citiraj gradivo
Navadno besedilo
BibTeX
EndNote XML
EndNote/Refer
RIS
ABNT
ACM Ref
AMA
APA
Chicago 17th Author-Date
Harvard
IEEE
ISO 690
MLA
Vancouver
:
Kopiraj citat
Objavi na:
Gradivo je del zbornika
Naslov:
Neural information processing
COBISS.SI-ID:
16493851
Gradivo je del revije
Naslov:
Lecture notes in computer science
Skrajšan naslov:
Lect. notes comput. sci.
Založnik:
Springer
ISSN:
1611-3349
COBISS.SI-ID:
29024005
Sekundarni jezik
Jezik:
Slovenski jezik
Ključne besede:
elektroencefalografija
,
vmesnik možgani-stroj
,
vmesnik možgani-računalnik
,
digitalno filtriranje
,
ekstrakcija značilk
,
klasifikacija
Projekti
Financer:
EC - European Commission
Program financ.:
H2020
Številka projekta:
7332266
Naslov:
FET Proactive: emerging themes and communities
Akronim:
Plan4Act
Podobna dela
Podobna dela v RUL:
Podobna dela v drugih slovenskih zbirkah:
Nazaj