Zobrazeno 1 - 10
of 9 211
pro vyhledávání: '"Common spatial pattern"'
Autor:
Xiaozhong Geng, Xi Zhang, Mengzhe Yue, Weixin Hu, Linen Wang, Xintong Zhang, Ping Yu, Duo Long, Hui Yan
Publikováno v:
Alexandria Engineering Journal, Vol 101, Iss , Pp 38-51 (2024)
Feature extraction and classification is a difficult area in motor imagery electroencephalogram (EEG) signal processing. In order to improve the classification accuracy of EEG signals, both a feature extraction method based on the combination of LMD-
Externí odkaz:
https://doaj.org/article/c3a8be73d1964d269c5146b2e3f7c350
Publikováno v:
IEEE Access, Vol 12, Pp 52978-52989 (2024)
This study addresses the challenge faced by individuals with upper-limb prostheses in regulating grip force and adapting movements to different object weights. Despite limited exploration, this research pioneers the use of EEG to estimate object weig
Externí odkaz:
https://doaj.org/article/13824c1615504bb18f6486f4dc3e2196
Publikováno v:
Frontiers in Robotics and AI, Vol 11 (2024)
We introduce a novel approach to training data augmentation in brain–computer interfaces (BCIs) using neural field theory (NFT) applied to EEG data from motor imagery tasks. BCIs often suffer from limited accuracy due to a limited amount of trainin
Externí odkaz:
https://doaj.org/article/a611c5f185da4ef8bf12cbcc2c704c3a
Akademický článek
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Publikováno v:
Sensors, Vol 24, Iss 12, p 3755 (2024)
A motor imagery brain–computer interface connects the human brain and computers via electroencephalography (EEG). However, individual differences in the frequency ranges of brain activity during motor imagery tasks pose a challenge, limiting the ma
Externí odkaz:
https://doaj.org/article/5a72c3fce1a947e9beb000a7436f7bee
Publikováno v:
Frontiers in Neuroscience, Vol 17 (2023)
BackgroundAs a typical self-paced brain–computer interface (BCI) system, the motor imagery (MI) BCI has been widely applied in fields such as robot control, stroke rehabilitation, and assistance for patients with stroke or spinal cord injury. Many
Externí odkaz:
https://doaj.org/article/2696306560d74e118aee02fc5890915e
Publikováno v:
Frontiers in Human Neuroscience, Vol 17 (2023)
BackgroundBrain-computer interface (BCI) systems based on motor imagery (MI) have been widely used in neurorehabilitation. Feature extraction applied by the common spatial pattern (CSP) is very popular in MI classification. The effectiveness of CSP i
Externí odkaz:
https://doaj.org/article/6bf125aaae0b487684c9210611d48daa
Publikováno v:
Frontiers in Human Neuroscience, Vol 17 (2023)
IntroductionThe common spatial patterns (CSP) algorithm is the most popular technique for extracting electroencephalogram (EEG) features in motor imagery based brain-computer interface (BCI) systems. CSP algorithm embeds the dimensionality of multich
Externí odkaz:
https://doaj.org/article/3c4b21886c774e54a73001e085e28f95
Akademický článek
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Publikováno v:
IEEE Access, Vol 11, Pp 139457-139465 (2023)
Several motor imagery classification methods have been developed and achieve higher accuracy. Machine learning (ML) based algorithms utilizing manually designed features often encounter robustness issues, leading to diminished accuracy. While deep le
Externí odkaz:
https://doaj.org/article/b5aea993e0cd44db99f8ebdc75c91411