Zobrazeno 1 - 10
of 132
pro vyhledávání: '"speech imagery"'
Autor:
Meenakshi Bisla, Radhey Shyam Anand
Publikováno v:
IEEE Access, Vol 12, Pp 108399-108413 (2024)
We propose a Transfer learning-enabled electroencephalography-based intuitive brain-computer interface system by utilizing phase-based brain functional connectivity methods such as phase lag index (PLI) and Intersite phase clustering (ISPC) along wit
Externí odkaz:
https://doaj.org/article/53f36fac6f6a497d95e532d78e296aeb
Autor:
Zengzhi Guo, Fei Chen
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 506-518 (2023)
Brain computer interface (BCI) based on speech imagery can help people with motor disorders communicate their thoughts to the outside world in a natural way. Due to being portable, non-invasive, and safe, functional near-infrared spectroscopy (fNIRS)
Externí odkaz:
https://doaj.org/article/308fc2fd920e48af90a34f4f47010ee7
Publikováno v:
Brain Sciences, Vol 14, Iss 3, p 196 (2024)
Brain-Computer Interfaces (BCIs) aim to establish a pathway between the brain and an external device without the involvement of the motor system, relying exclusively on neural signals. Such systems have the potential to provide a means of communicati
Externí odkaz:
https://doaj.org/article/dc8288f2aefd4e5aae454cfb47465f4b
Autor:
Tsuneo Nitta, Junsei Horikawa, Yurie Iribe, Ryo Taguchi, Kouichi Katsurada, Shuji Shinohara, Goh Kawai
Publikováno v:
Frontiers in Human Neuroscience, Vol 17 (2023)
Speech imagery recognition from electroencephalograms (EEGs) could potentially become a strong contender among non-invasive brain-computer interfaces (BCIs). In this report, first we extract language representations as the difference of line-spectra
Externí odkaz:
https://doaj.org/article/d0328e4000364426bff3325543327992
Autor:
Ahmad Naebi, Zuren Feng
Publikováno v:
Applied Sciences, Vol 13, Iss 21, p 11787 (2023)
Many current brain–computer interface (BCI) applications depend on the quick processing of brain signals. Most researchers strive to create new methods for future implementation and enhance existing models to discover an optimal feature set that ca
Externí odkaz:
https://doaj.org/article/5afdb06c49e947969bd435b48c77f545
Autor:
Pongsakorn Sommit
Publikováno v:
Journal of Humanities and Social Sciences Mahasarakham University, Vol 40, Iss 6, Pp 119-128 (2021)
The objectives of this study were (1) to compare the speech abilities of students with proficiency in speaking before and after using the imagery to speaking and (2) to evaluate satisfaction of students with an impromptu speaking talent regarding ima
Externí odkaz:
https://doaj.org/article/0a392a85d2434b68858ea8846eebc7f1
Publikováno v:
IEEE Access, Vol 9, Pp 135371-135383 (2021)
We present a transfer learning-based approach for decoding imagined speech from electroencephalogram (EEG). Features are extracted simultaneously from multiple EEG channels, rather than separately from individual channels. This helps in capturing the
Externí odkaz:
https://doaj.org/article/40ec06f8977c48d9a54d0b649c0701d7
Akademický článek
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Publikováno v:
Frontiers in Neuroscience, Vol 15 (2021)
Over the past decade, many researchers have come up with different implementations of systems for decoding covert or imagined speech from EEG (electroencephalogram). They differ from each other in several aspects, from data acquisition to machine lea
Externí odkaz:
https://doaj.org/article/77c58b1880384f3daf3a40c544ffb153
Akademický článek
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