The design and implementation of multi-character classification scheme based on EEG signals of visual imagery

Alom KM, Islam S (2020) Classification for the P300-based brain computer interface (BCI). In: 2020 2nd international conference on advanced information and communication technology (ICAICT), pp. 387–391

Altan A, Karasu S (2020) Recognition of COVID-19 disease from X-ray images by hybrid model consisting of 2D curvelet transform, chaotic salp swarm algorithm and deep learning technique. Chaos Solit Fract 140:110071

Article MathSciNet Google Scholar

Babo RM, Buot A, Tallon BC (2019) Neural responses to heartbeats distinguish self from other during imagination. NeuroImage 191:10–20

Article Google Scholar

Bang JS, Jeong JH, Won DO (2021) Classification of visual perception and imagery based EEG signals using convolutional neural networks. In: 2021 9th international winter conference on brain-computer interface (BCI), pp. 1–6

Boashash B (2015) Time-frequency signal analysis and processing: a comprehensive reference

Christa N, Scherer R, Reiner M, Gert P (2005) Imagery of motor actions: differential effects of kinesthetic and visual-motor mode of imagery in single-trial EEG. Brain Res Cogn Brain Res 25(3):668–677

Article Google Scholar

Daniel B, Beata J, Nicolas MY, Sergey SD (2015) Neural point-and-click communication by a person with incomplete locked-in syndrome. Neurorehabil Neural Rep 29(5):462–471

Article Google Scholar

Dijkstra N, Mostert P, Lange FPd, Bosch S, Gerven MA (2018) Differential temporal dynamics during visual imagery and perception. Elife 7:33904

Article Google Scholar

Ehsan ET (2012) Classification of primitive shapes using brain computer interfaces. Comput Aided Des 44(10):1011–1019

Article Google Scholar

Esposito DM, Detre JA, Aguirre GK, Stallcup M, Alsop DC (1997) A functional MRI study of mental image generation. Neuropsychologia 35(5):725–30

Article PubMed Google Scholar

Fabio LR, Gustavo P, Jose AM (2020) Convolutional neural networks and genetic algorithm for visual imagery classification. Austral Phys Eng Sci Med 43(3):973–983

Article Google Scholar

Filip S, Tom C (2020) Non-specific visuospatial imagery as a novel mental task for online EEG-based BCI control. Int J Neural Syst 30(6):2050026

Article Google Scholar

Fu Y, Li Z, Gong A, Qian Q, Su L, Zhao L (2021) Identification of visual imagery by electroencephalography based on empirical mode decomposition and an auto-regressive model. Comput Intell Neuro Sci 30:203

Jelena M, Jeremy F, Smeety P, Jeremie M, Fabien L (2021) Towards identifying optimal biased feedback for various user states and traits in motor imagery BCI. IEEE Trans Biomed Eng 69(23):1101–1110

Juneja K (2019) Individual and mutual feature processed ELM model for EEG signal based brain activity classification. Wirel Pers Commun Int J 108(2):659

Article Google Scholar

Kano N (2019) Communication of ALS patients with totally locked-in syndrome. J Nurs Sci Eng 6(2):63–69

Ko W, Jeon E, Jeong S, Suk H-I (2021) Multi-scale neural network for EEG representation learning in BCI. IEEE Computat Intell Magaz 16(2):31–45

Article Google Scholar

Koizumi K, Ueda K, Nakao M (2018) Development of a cognitive brain-machine interface based on a visual imagery method. Annu Int Conf IEEE Eng Med Biol Soc 18:1062–1065

Kumar P, Saini R, Roy PP, Sahu PK, Dogra DP (2018) Envisioned speech recognition using EEG sensors. Pers Ubiquit Comput 22:185–199

Article Google Scholar

Kwon BH, Lee BH, Cho JH, Jeong JH (2022) Decoding visual imagery from EEG signals using visual perception guided network training method. In: 2022 10th international winter conference on brain-computer interface (BCI), pp. 1–5

Laurens VDM, Hinton G (2008) Visualizing data using t-SNE. J Mach Learn Res 9(86):2579–2605

Lee S, Jang S, Jun SC (2022) Exploring the ability to classify visual perception and visual imagery EEG data: toward an intuitive BCI system. Electronics 11(17):2706

Article Google Scholar

Lee S, Lee M, Lee S (2020) Neural decoding of imagined speech and visual imagery as intuitive paradigms for BCI communication. IEEE Trans Neural Syst Rehabilit Eng 28(12):2647–2659

Article Google Scholar

Li Y, Ning F, Jiang X, Yi Y (2022) Feature extraction of ship radiation signals based on wavelet packet decomposition and energy entropy. Math Probl Eng 2022:1–12

Article Google Scholar

Li M, Wang R, Xu D (2020) An improved composite multiscale fuzzy entropy for feature extraction of MI-EEG. Entropy (Basel) 22(12):1356

Article ADS PubMed Google Scholar

Llorella FR, AzorÃn JM, Patow G (2023) Black hole algorithm with convolutional neural networks for the creation of brain-computer interface based in visual perception and visual imagery. Neural Comput Appl 35(8):5631–5641

Article Google Scholar

Lu H, Konstantinos PN, Anastasios VN (2009) Uncorrelated multilinear discriminant analysis with regularization and aggregation for tensor object recognition. IEEE Trans Neural Netw 20(1):103–23

Article PubMed Google Scholar

Lu H, Konstantinos PN, Anastasios VN (2009) Uncorrelated multilinear principal component analysis for unsupervised multilinear subspace learning. IEEE Trans Neural Netw 20(11):1820–1836

Article CAS PubMed Google Scholar

Markus K, Jan K, Thomas M, Mark G (2000) Cortical activation evoked by visual mental imagery as measured by fMRI. Neuro Rep 11:3957–3962

Min B, Kim J, Park H-j, Lee B, et al. (2016) Vowel imagery decoding toward silent speech BCI using extreme learning machine with electroencephalogram. BioMed Res Int 2016

Nataliya K, Lindgren JT, Anatole L (2018) Attending to visual stimuli versus performing visual imagery as a control strategy for EEG-based brain-computer interfaces. Sci Rep 8(1):13222

Article Google Scholar

Pan H, Li Z, Tian C, Wang L, Fu Y, Qin X, Liu F (2022) The light GBM-based classification algorithm for Chinese characters speech development imagery BCI system. Cognit Neurodyn 17(2):373–384

Article Google Scholar

Sousa T, Amaral C, Andrade J, Pires G, Nunes UJ, Castelo-Branco M (2017) Pure visual imagery as a potential approach to achieve three classes of control for implementation of BCI in non-motor disorders. J Neural Eng 14(4):1–11

Article Google Scholar

Srivastava G, Crottaz-Herbette S, Lau KM, Glover GH, Menon V (2005) ICA-based procedures for removing ballistocardiogram artifacts from EEG data acquired in the MRI scanner. Neuroimage 24(1):50–60

Article CAS PubMed Google Scholar

Sun G, Song Z, Liu J, Zhu S, He Y (2017) Feature selection method based on maximum information coefficient and approximate markov blanket. Acta Automat Sin 43(5):795–805

Tang J, Xu M, Han J, Liu M, Dai T, Chen S, Ming D (2020) Optimizing SSVEP-based BCI system towards practical high-speed spelling. Sensors 20(15):4186

Article ADS PubMed PubMed Central Google Scholar

Vinay C, Ankur V, Anand N, Eklas H (2020) Brain-computer interface-based humanoid control: a review. Sensors (Basel) 20(13):3620

Article Google Scholar

Williams AH, Ben P, Maheswaranathan N, Dhawale AK (2020) Discovering precise temporal patterns in large-scale neural recordings through robust and interpretable time warping. Neuron 105(2):246–259

Article CAS PubMed Google Scholar

Winlove C, Milton F, Ranson J, Fulford J, Mackisack M, Macpherson F, Zeman A (2018) The neural correlates of visual imagery: a co-ordinate-based meta-analysis. Cortex 105:4–25

Article PubMed Google Scholar

YaÄŸ I, Altan A (2022) Artificial intelligence-based robust hybrid algorithm design and implementation for real-time detection of plant diseases in agricultural environments. Biology 11(12):1732

Article Google Scholar

Zhang Z, Sun J, Chen T (2022) A new dynamically convergent differential neural network for brain signal recognition. Biomed Sig Process Control 71(3):103130

Article Google Scholar

Zhang L, Wen D, Li C, Zhu R (2020) Ensemble classifier based on optimized extreme learning machine for motor imagery classification. J Neural Eng 17(2):1–12

Article Google Scholar

View original article

COGNITIVE NEURODYNAMICS

0 0 0 0 0 0 0

Comments (0)