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Development of a real-time motor-imagery-based EEG brain-machine interface
Gorjup, Gal (Avtor), Vrabič, Rok (Avtor), Petrov Stoyanov, Stoyan (Avtor), Østergaard Andersen, Morten (Avtor), Manoonpong, Poramate (Avtor)

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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 (dk_c)
Tipologija:1.08 - Objavljeni znanstveni prispevek na konferenci
Organizacija:FS - Fakulteta za strojništvo
Leto izida:2018
Št. strani:f. 610-622
Številčenje:Vol. 11307
UDK:681.5(045)
ISSN pri članku:1611-3349
DOI:10.1007/978-3-030-04239-4_55 Povezava se odpre v novem oknu
COBISS.SI-ID:16494107 Povezava se odpre v novem oknu
Število ogledov:596
Število prenosov:564
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
 
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Gradivo je del zbornika

Naslov:Neural information processing
COBISS.SI-ID:16493851 Povezava se odpre v novem oknu

Gradivo je del revije

Naslov:Lecture notes in computer science
Založnik:Springer
ISSN:1611-3349
COBISS.SI-ID:29024005 Povezava se odpre v novem oknu

Gradivo je financirano iz projekta

Financer:EC - European Commission
Program financ.:H2020
Številka projekta:7332266
Naslov:FET Proactive: emerging themes and communities
Akronim:Plan4Act

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:elektroencefalografija, vmesnik možgani-stroj, vmesnik možgani-računalnik, digitalno filtriranje, ekstrakcija značilk, klasifikacija

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