Experimental Philosophy and Cognitive Science in the Context of Comprehending Hybrid Intelligence: Philosophical and Anthropological Aspect by German E. Bokov, Helen V. Chapny

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A portable EEG signal acquisition system and a limited-electrode channel classification network for SSVEP by Yunxiao Ma, Jinming Huang, Chuan Liu, Meiyu Shi

Subjects: “…Brain-Computer Interfaces (BCIs)…”
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Individualized prediction of multi-domain intelligence quotient in bipolar disorder patients using resting-state functional connectivity by Xiaoyu Li, Wei Wei, Linze Qian, Xiaojing Li, Mingli Li, Ioannis Kakkos, Qiang Wang, Hua Yu, Wanjun Guo, Xiaohong Ma, George K. Matsopoulos, Liansheng Zhao, Wei Deng, Yu Sun, Tao Li

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A composite improved attention convolutional network for motor imagery EEG classification by Wenzhe Liao, Zipeng Miao, Shuaibo Liang, Linyan Zhang, Chen Li

“…IntroductionA brain-computer interface (BCI) is an emerging technology that aims to establish a direct communication pathway between the human brain and external devices. …”
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Oligodendrocytes drive neuroinflammation and neurodegeneration in Parkinson’s disease via the prosaposin-GPR37-IL-6 axis by Qiang Ma, Jin-Lan Tian, Yao Lou, Ran Guo, Xiao-Ru Ma, Jian-Bin Wu, Jing Yang, Bing-Jie Tang, Shun Li, Mengsheng Qiu, Shumin Duan, Jing-Wei Zhao, Jing Zhang, Zhen-Zhong Xu

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Neurofilament light chain levels in neuronal surface antibody-associated autoimmune encephalitis: a systematic review and meta-analysis by Qi-Lun Lai, Meng-Ting Cai, Er-Chuang Li, Gao-Li Fang, Chun-Hong Shen, Yong-Feng Xu, Song Qiao, Jia-Jia Wang, Qin-Jie Weng, Yin-Xi Zhang

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Application of "Hand-Brain Perception and Hand-Brain Movement" Theory in Upper Limb Rehabilitation after Stroke by JIA Jie

“…Guided by the theory of "hand-brain perception and hand-brain movement", our research team developed an effective five-step method of hand-brain perception training (sensory assessment, education, training, task-oriented training and cognition), the brain-computer interface hand-brain perception paradigm, and the mirror therapy hand-brain perception paradigm. …”
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Research on EEG signal classification of motor imagery based on AE and Transformer by Rui JIANG, Liuting SUN, Xiaoming WANG, Dapeng LI, Youyun XU

“…The motor imagery brain-computer interface has always been the focus of scholars.But traditional system cannot accurately extract significant signals and has low classification accuracy.To overcome such difficulty, a new Transformer model was proposed based on the auto-encoder (AE).The filter bank common spatial pattern (FBCSP) was used to extract the features of multiple frequency bands, and the AE was exploited to obtain the dimensionality-reduced feature matrix.Finally, it considered the influence of the global signal features by the position encoding of the Transformer model and considered the internal correlation of the feature matrix by using the multi-head self-attention mechanism.By comparison with the traditional K-nearest neighbors (KNN) system based on linear discriminant analysis (LDA), the experimental results validates that the classification effect of AE+Transformer model is better than that of LDA+KNN system.It shows that the improved algorithm is suitable for the binary classification of motor imagery.…”
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Comparing P300 flashing paradigms in online typing with language models. by Nand Chandravadia, Shrita Pendekanti, Dustin Roberts, Robert Tran, Saarang Panchavati, Corey Arnold, Nader Pouratian, William Speier

“…The P300 Speller is a brain-computer interface system that allows victims of motor neuron diseases to regain the ability to communicate by typing characters into a computer by thought. …”
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Teleoperation Robot Control of a Hybrid EEG-Based BCI Arm Manipulator Using ROS by Vidya Nandikolla, Daniel A. Medina Portilla

“…To create the environment and user interface, a robot operating system (ROS) is used. Live brain computer interface (BCI) commands from a trained user are successfully harvested and used as an input signal to pick a goal point from 3D point cloud data and calculate the goal position of the robots’ mobile base, placing the goal point in the robot arms workspace. …”
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Research on How Human Intelligence, Consciousness, and Cognitive Computing Affect the Development of Artificial Intelligence by Yanyan Dong, Jie Hou, Ning Zhang, Maocong Zhang

“…In the future, the research and development of cutting-edge technologies such as brain-computer interface (BCI) together with the development of the human brain will eventually usher in a strong AI era, when AI can simulate and replace human’s imagination, emotion, intuition, potential, tacit knowledge, and other kinds of personalized intelligence. …”
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Real-Time Classification of Deep and Non-Deep Sleep With Comparative Intervention Experiments by Mo Xia, Hongxi Xue, Boning Li, Jianting Cao

“…This paper presents a system that utilizes a Brain-Computer Interface and a Deep Learning Network for the real-time classification of non-deep sleep and deep sleep. …”
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A hybrid CNN model for classification of motor tasks obtained from hybrid BCI system by R. Shelishiyah, Deepa Beeta Thiyam, M. Jehosheba Margaret, N. M. Masoodhu Banu

“…Abstract The Hybrid-Brain Computer Interface (BCI) has shown improved performance, especially in classifying multi-class data. …”
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Performance Improvement with Reduced Number of Channels in Motor Imagery BCI System by Ali Özkahraman, Tamer Ölmez, Zümray Dokur

“…Classifying Motor Imaging (MI) Electroencephalogram (EEG) signals is of vital importance for Brain–Computer Interface (BCI) systems, but challenges remain. …”
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Sistema domótico controlado a través de una interfaz cerebro-ordenador by Francisco Velasco-Álvarez, Álvaro Fernández-Rodríguez, Ricardo Ron-Angevin

“…Las interfaces cerebro-ordenador (BCI, de brain-computer interface) permiten utilizar la actividad cerebral de un usuario como canal de comunicación para interactuar con determinados dispositivos. …”
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Robust Spike Sorting Using Dual Tree Complex Wavelet Transform: Overcoming Traditional Limitations by Gorkem Serbes

“…Moreover, the DT-CWT’s computational efficiency and suitability for real-time, on-chip implementations in next-generation wireless brain computer interface devices highlight its practical advantages. …”
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Electroencephalography Signal Grouping and Feature Classification Using Harmony Search for BCI by Tae-Ju Lee, Seung-Min Park, Kwee-Bo Sim

“…This paper presents a heuristic method for electroencephalography (EEG) grouping and feature classification using harmony search (HS) for improving the accuracy of the brain-computer interface (BCI) system. EEG, a noninvasive BCI method, uses many electrodes on the scalp, and a large number of electrodes make the resulting analysis difficult. …”
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Research on High-Frequency Combination Coding-Based SSVEP-BCIs and Its Signal Processing Algorithms by Feng Zhang, Chengcheng Han, Lili Li, Xin Zhang, Jun Xie, Yeping Li

“…This study presents a new steady-state visual evoked potential (SSVEP) paradigm for brain computer interface (BCI) systems. The new paradigm is High-Frequency Combination Coding-Based SSVEP (HFCC-SSVEP). …”
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EEG-RegNet: Regressive Emotion Recognition in Continuous VAD Space Using EEG Signals by Hyo Jin Jon, Longbin Jin, Hyuntaek Jung, Hyunseo Kim, Eun Yi Kim

“…Electroencephalogram (EEG)-based emotion recognition has garnered significant attention in brain–computer interface research and healthcare applications. …”
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A method of EEG signal feature extraction based on hybrid DWT and EMD by Xiaozhong Geng, Linen Wang, Ping Yu, Weixin Hu, Qipeng Liang, Xintong Zhang, Cheng Chen, Xi Zhang

“…The processing and recognition of electroencephalogram (EEG) signal is the most important part of brain-computer interface (BCI) system, and the quality of signal processing and recognition is directly related to the effectiveness of BCI system. …”
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