Developing Brain-Based Bare-Handed Human-Machine Interaction via On-Skin Input

Authors: Kim, M., Shin, H., Cho, J., Lee, S.

Source: IEEE Transactions on Cybernetics IEEE Trans. Cybern. Cybernetics, IEEE Transactions on. 55(4):1554-1567 Apr, 2025

A Deep Learning Approach for Early Detection of Epileptic Seizures

Authors: Anitha L, Adersh Mohan Puthiyedath, Alind Wilson, Ansil T.A, Devanarayanan Anil

Subject Terms: Real-time epileptic seizure detection, hybrid deep learning models, EEG Signal analysis, patient-specific epilepsy management

Neurophysiologically Meaningful Motor Imagery EEG Simulation With Applications to Data Augmentation

Authors: Catalina María Galván, Rubén D. Spies, Diego H. Milone, Victoria Peterson

Source: IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 2346-2355 (2024)

Subject Terms: Brain modeling, Artificial intelligence, Data augmentation, Decoding, Cognitive Neuroscience, RM1-950, EEG Analysis, motor imagery, Deep Learning, Motor imagery, Cognitive psychology, Medical technology, Humans, Psychology, Computer Simulation, Deep Learning for EEG, R855-855.5, Data models, deep learning, Life Sciences, Electroencephalography, Brain-Computer Interfaces in Neuroscience and Medicine, Computer science, EEG simulation, FOS: Psychology, Brain–computer interface, surface EEG, Neural Ensemble Physiology, Brain-Computer Interfaces, Imagination, Therapeutics. Pharmacology, Motor Imagery, Brain-computer interfaces, Algorithms, data augmentation, Neuroscience

File Description: application/pdf

Access URL: https://pubmed.ncbi.nlm.nih.gov/38900612
https://doaj.org/article/d9067cc0dfc844de88495be9afb91f75
http://hdl.handle.net/11336/254693

EMG gesture signal analysis towards diagnosis of upper limb using dual-pathway convolutional neural network

Authors: Hafiz Ghulam Murtza Qamar, Muhammad Farrukh Qureshi, Zohaib Mushtaq, Zubariah Zubariah, Muhammad Zia ur Rehman, Nagwan Abdel Samee, Noha F. Mahmoud, Yeong Hyeon Gu, Mohammed A. Al‐masni

Source: Mathematical Biosciences and Engineering, Vol 21, Iss 4, Pp 5712-5734 (2024)
Qamar, H G M, Qureshi, M F, Mushtaq, Z, Zubariah, Z, Rehman, M Z U, Samee, N A, Mahmoud, N F, Gu, Y H & Al-Masni, M A 2024, 'EMG gesture signal analysis towards diagnosis of upper limb using dual-pathway convolutional neural network', Mathematical Biosciences and Engineering, vol. 21, no. 4, pp. 5712-5734. https://doi.org/10.3934/mbe.2024252

Subject Terms: Male, electromyography, Artificial intelligence, log mel spectrogram, convolutional neural network, 02 engineering and technology, Surface EMG, Pattern recognition (psychology), Epilepsy Detection, EEG Analysis, 0302 clinical medicine, Engineering, Cognitive psychology, 0202 electrical engineering, electronic engineering, information engineering, Psychology, Gestures, Life Sciences, Signal Processing, Computer-Assisted, Neural Interface Technology, Middle Aged, Brain-Computer Interfaces in Neuroscience and Medicine, FOS: Psychology, Analysis of Electromyography Signal Processing, Physical Sciences, nina pro, Medicine, Female, Algorithms, Biotechnology, Adult, Cognitive Neuroscience, Biomedical Engineering, Convolutional neural network, upper limb, Speech recognition, FOS: Medical engineering, Upper Extremity, Young Adult, 03 medical and health sciences, Cellular and Molecular Neuroscience, Amputees, QA1-939, Humans, Deep Learning for EEG, gesture recognition, Electromyography, Reproducibility of Results, Computer science, Musculoskeletal Modeling, Physical medicine and rehabilitation, Recall, Neural Networks, Computer, TP248.13-248.65, Mathematics, Neuroscience

File Description: application/pdf

Access URL: https://pubmed.ncbi.nlm.nih.gov/38872555
https://doaj.org/article/9d76c19912c04629a23aa47278da8f07
https://vbn.aau.dk/ws/files/708673610/10.3934_mbe.2024252.pdf
http://www.scopus.com/inward/record.url?scp=85191355753&partnerID=8YFLogxK
https://vbn.aau.dk/da/publications/55d5565c-7538-426b-9b88-92f480607225
https://doi.org/10.3934/mbe.2024252

NeuroWave-Net: Enhancing epileptic seizure detection from EEG brain signals via advanced convolutional and long short-term memory networks

Authors: Md. Mehedi Hassan, R. Haque, Sheikh Mohammed Shariful Islam, Hossam Meshref, Roobaea Alroobaea, Mehedi Masud, Anupam Kumar Bairagi

Source: AIMS Bioengineering, Vol 11, Iss 1, Pp 85-109 (2024)

Subject Terms: Artificial intelligence, Feature (linguistics), Classification of Brain Tumor Type and Grade, 02 engineering and technology, Pattern recognition (psychology), 01 natural sciences, Epilepsy Detection, EEG Analysis, Computer security, convolutional neural networks, Psychology, Life Sciences, Electroencephalography, Brain-Computer Interfaces in Neuroscience and Medicine, Long short term memory, FOS: Philosophy, ethics and religion, FOS: Psychology, epileptic seizure detection, Neurology, Physical Sciences, TP155-156, Deep Learning in Computer Vision and Image Recognition, Computer Vision and Pattern Recognition, eeg, long short-term memory, 0210 nano-technology, Biotechnology, Artificial neural network, Cognitive Neuroscience, Recurrent neural network, Convolutional neural network, neurowave-net, Chemical engineering, brain signal preprocessing, Machine learning, Medical technology, Neural Network Architectures, Deep Learning for EEG, R855-855.5, Key (lock), Deep learning, Linguistics, Computer science, 0104 chemical sciences, Philosophy, Neural Ensemble Physiology, Categorization, Computer Science, Epileptic seizure, FOS: Languages and literature, lstm-cnn, TP248.13-248.65, Neuroscience

Access URL: https://doaj.org/article/88d3b5b205a044a1ae1b51c2b1109f9e

ADHD/CD-NET: automated EEG-based characterization of ADHD and CD using explainable deep neural network technique

Authors: Hui Wen Loh, Chui Ping Ooi, Shu Lih Oh, Prabal Datta Barua, Yi Ren Tan, U. Rajendra Acharya, Daniel Fung

Source: Cogn Neurodyn

Subject Terms: Artificial intelligence, Cognitive Neuroscience, Clinical psychology, Geometry, Convolutional neural network, Comorbidity, Analysis of Brain Functional Connectivity Networks, Pattern recognition (psychology), Conduct disorder, Attention deficit hyperactivity disorder, 03 medical and health sciences, EEG Analysis, 0302 clinical medicine, Health Sciences, Machine learning, FOS: Mathematics, ADHD, Psychology, EEG, Deep Learning for EEG, Attention-Deficit/Hyperactivity Disorder, Grad-CAM, Psychiatry, Explainable artificial intelligence (XAI), Life Sciences, Deep learning, Electroencephalography, Brain-Computer Interfaces in Neuroscience and Medicine, Computer science, Correlation, 3. Good health, FOS: Psychology, Psychiatry and Mental health, Brain Network Development, Medicine, Conduct disorde, CNN, Mathematics, Research Article, Neuroscience

File Description: application/pdf

Access URL: https://pubmed.ncbi.nlm.nih.gov/39104684

Different Methods of EEG Signal Analysis Using Power Spectral Density, ChronoNet and ResNest

Authors: Md. Mehedi Hasan, Senjuti Rahman, Ajay Krishno Sarkar, Fayez Khan, Ashek Seum

Source: European Journal of Electrical Engineering and Computer Science. 7:20-27

Subject Terms: Blind Source Separation and Independent Component Analysis, Artificial intelligence, Support vector machine, Cognitive Neuroscience, Memristive Devices for Neuromorphic Computing, 02 engineering and technology, Pattern recognition (psychology), Bayesian probability, Epilepsy Detection, EEG Analysis, Bayes' theorem, 03 medical and health sciences, Engineering, Spectral density, 0302 clinical medicine, Machine learning, FOS: Electrical engineering, electronic engineering, information engineering, Decision tree, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Psychology, Deep Learning for EEG, Electrical and Electronic Engineering, Epilepsy, Naive Bayes classifier, 4. Education, Life Sciences, Electroencephalography, Brain-Computer Interfaces in Neuroscience and Medicine, 16. Peace & justice, Computer science, 3. Good health, FOS: Psychology, Neural Ensemble Physiology, Combinatorics, Physical Sciences, Signal Processing, Computer Science, Kernel (algebra), Telecommunications, Feature extraction, Mathematics, Neuroscience, Random forest

Assessing the Potential of Data Augmentation in EEG Functional Connectivity for Early Detection of Alzheimer’s Disease

Authors: Jialei Hao, Zihao Huang, César F. Caiafa, Feng Duan, Zhang Yu, Zhe Sun, Jordi Solé‐Casals

Contributors: Apollo - University of Cambridge Repository

Source: CONICET Digital (CONICET)
Consejo Nacional de Investigaciones Científicas y Técnicas

Subject Terms: Artificial neural network, Aging, Artificial intelligence, Data augmentation, Neuroimaging Data Analysis, Cognitive Neuroscience, Bioengineering, Set (abstract data type), Neurodegenerative, Analysis of Brain Functional Connectivity Networks, Alzheimer's Disease, Pattern recognition (psychology), Epilepsy Detection, Cellular and Molecular Neuroscience, EEG Analysis, 46 Information and Computing Sciences, 4611 Machine Learning, Machine learning, Acquired Cognitive Impairment, Machine Learning and Artificial Intelligence, Psychology, EEG, Deep Learning for EEG, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Life Sciences, Electroencephalography, Neural Interface Technology, Brain-Computer Interfaces in Neuroscience and Medicine, Computer science, Brain Disorders, Programming language, 3. Good health, FOS: Psychology, Networking and Information Technology R&D (NITRD), Neurological, Brain Network Development, Dementia, Alzheimer disease, Neuroscience

File Description: application/pdf; text/xml

Access URL: http://hdl.handle.net/11336/221800
https://www.repository.cam.ac.uk/handle/1810/363423
https://doi.org/10.1007/s12559-023-10188-7

Extraction of Fetal Electrocardiogram by Combining Deep Learning and SVD-ICA-NMF Methods

Authors: Said Ziani, Yousef Farhaoui, Mohammed Moutaib

Source: Big Data Mining and Analytics, Vol 6, Iss 3, Pp 301-310 (2023)

Subject Terms: Blind Source Separation and Independent Component Analysis, Artificial intelligence, Cognitive Neuroscience, Convolutional neural network, Independent component analysis, Speech recognition, Pattern recognition (psychology), Quantum mechanics, convolutional neural network (cnn), Epilepsy Detection, Matrix decomposition, deep learning (dl), Health Sciences, Arrhythmia Detection, FOS: Mathematics, Deep Learning for EEG, Eigenvalues and eigenvectors, fetal electrocardiogram, feature extraction, Physics, Singular value decomposition, Pure mathematics, Life Sciences, Non-negative matrix factorization, QA75.5-76.95, Analysis of Electrocardiogram Signals, Brain-Computer Interfaces in Neuroscience and Medicine, ECG Signal, Independent Component Analysis, Computer science, Dimensionality reduction, Dimension (graph theory), Electronic computers. Computer science, Signal Processing, Computer Science, Physical Sciences, Medicine, Feature extraction, Cardiology and Cardiovascular Medicine, Mathematics, Neuroscience

Access URL: https://doaj.org/article/4d9db15e4968489f808cf92c27a8ccc4

A ROBUST FRAMEWORK FOR DRIVER FATIGUE DETECTION FROM EEG SIGNALS USING ENHANCEMENT OF MODIFIED Z-SCORE AND MULTIPLE MACHINE LEARNING ARCHITECTURES

Authors: Rafiuddin Abdubrani, Mahfuzah Mustafa, Zarith Liyana Zahari

Source: International Islamic University Malaysia Engineering Journal, Vol 24, Iss 2 (2023)

Subject Terms: Artificial neural network, z-score, Artificial intelligence, Support vector machine, Cognitive Neuroscience, Social Sciences, Experimental and Cognitive Psychology, Convolutional neural network, 02 engineering and technology, Speech recognition, Pattern recognition (psychology), Epilepsy Detection, EEG Analysis, 0502 economics and business, Health Sciences, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Psychology, Driver Fatigue, Deep Learning for EEG, Psychiatry, 05 social sciences, deep learning, Life Sciences, Electroencephalography, electroencephalogram, Brain-Computer Interfaces in Neuroscience and Medicine, Engineering (General). Civil engineering (General), 16. Peace & justice, Computer science, Programming language, 3. Good health, Effects of Sleep Deprivation and Fatigue on Performance, FOS: Psychology, Driver fatigue, Neural Ensemble Physiology, Analysis and Applications of Heart Rate Variability, Medicine, Feature extraction, TA1-2040, Software portability, Cardiology and Cardiovascular Medicine, Neuroscience

Access URL: https://doaj.org/article/c3adfee6a0654c048c757540dc262698

Spectral features of resting-state EEG in Parkinson's Disease: A multicenter study using functional data analysis

Authors: Alberto Jaramillo‐Jimenez, Diego Alejandro Tovar‐Rios, Johann Alexis Ospina, Yorguin-Jose Mantilla-Ramos, Daniel Loaiza-López, Verónica Henao Isaza, Luisa María Zapata Saldarriaga, Valeria Cadavid Castro, Jazmín Ximena Suárez-Revelo, Yamile Bocanegra, Francisco Lopera, David Antonio Pineda-Salazar, Carlos Andrés Tobón Quintero, John Fredy Ochoa Gómez, Miguel Germán Borda, Dag Aarsland, Laura Bonanni, Kolbjørn Brønnick

Source: Clinical Neurophysiology

Subject Terms: MILD COGNITIVE IMPAIRMENT, PREDICTION, Parkinson's disease, Astronomy, Pattern recognition (psychology), Astrophysics, 09 Engineering, Epilepsy Detection, EEG Analysis, Cognitive psychology, Psychology, Disease, BODY, Neuronal Oscillations in Cortical Networks, Internal medicine, 11 Medical and Health Sciences, Spectroscopy, UTILITY, Parkinson's Disease, Construct validity, DEMENTIA, Physics, Statistics, Life Sciences, Parkinson Disease, Electroencephalography, Alpha rhythm, Neural Interface Technology, Audiology, Brain-Computer Interfaces in Neuroscience and Medicine, LEWY BODIES, 17 Psychology and Cognitive Sciences, FOS: Psychology, Medicine, Resting state fMRI, Life Sciences & Biomedicine, Psychometrics, DIAGNOSTIC-CRITERIA, Cognitive Neuroscience, POWER, Clinical Neurology, Spectral analysis, Alpha (finance), MOVEMENT, Cellular and Molecular Neuroscience, Spectral density, QUANTITATIVE EEG, Theta rhythm, FOS: Mathematics, Humans, VDP::Medisinske Fag: 700, Deep Learning for EEG, Science & Technology, Neurology & Neurosurgery, Neurosciences, Reproducibility of Results, Functional Data Analysis, Epoch (astronomy), Functional data analysis, Galaxy, Neural Ensemble Physiology, 3209 Neurosciences, Neurosciences & Neurology, Beta Rhythm, Mathematics, Neuroscience

File Description: application/pdf; 13 páginas

Access URL: https://pubmed.ncbi.nlm.nih.gov/37146531
https://www.sciencedirect.com/science/article/pii/S1388245723005989?via=ihub
https://hdl.handle.net/11564/809911
https://doi.org/10.1016/j.clinph.2023.03.363
https://lirias.kuleuven.be/handle/20.500.12942/765568
https://doi.org/10.1016/j.clinph.2023.03.363
https://hdl.handle.net/11250/3119190
https://hdl.handle.net/10614/15852
https://doi.org/10.1016/j.clinph.2023.03.363

A Systematic Review of Using Deep Learning Technology in the Steady-State Visually Evoked Potential-Based Brain-Computer Interface Applications: Current Trends and Future Trust Methodology

Authors: A. S. Albahri, Z.T. Al-qaysi, Laith H. Alzubaidi, Alhamzah Alnoor, O. S. Albahri, A. H. Alamoodi, Anizah Abu Bakar

Source: Int J Telemed Appl
International Journal of Telemedicine and Applications, Vol 2023 (2023)

Subject Terms: Artificial neural network, Parallel computing, Artificial intelligence, Interface (matter), Cognitive Neuroscience, Memristive Devices for Neuromorphic Computing, Convolutional neural network, Review Article, Operations research, Cellular and Molecular Neuroscience, Engineering, Machine learning, FOS: Electrical engineering, electronic engineering, information engineering, Deep Learning for EEG, Electrical and Electronic Engineering, Brain-inspired Computing, Biology, Bubble, Boltzmann machine, Life Sciences, Deep learning, Electroencephalography, Neural Interface Technology, Brain-Computer Interfaces in Neuroscience and Medicine, Computer science, Multiple-criteria decision analysis, Process (computing), Brain–computer interface, Operating system, Brain-Computer Interfaces, Physical Sciences, Medicine, Maximum bubble pressure method, Neuroscience

Access URL: https://pubmed.ncbi.nlm.nih.gov/37168809
https://doaj.org/article/c067b27d95044a77bb57284bc54673ff

Application of Signal Classifiers in Auditory Evoked Potentials for the Detection of Pathological Patients

Authors: Marco G. Baldiviezo, Juan Luis Barberia, Camila Bontempo, Yanina Corsaro, F. Fernandez Biancardi, Masia R. Hernando, Lorenzo Licata Caruso, Adrián E. Paglia, Matías Rodriguez, Walter Legnani

Source: Trends in Computational and Applied Mathematics, Vol 24, Iss 1 (2023)
Trends in Computational and Applied Mathematics, Volume: 24, Issue: 1, Pages: 63-81, Published: 27 MAR 2023

Subject Terms: fractal dimension, Blind Source Separation and Independent Component Analysis, Artificial intelligence, Cognitive Neuroscience, Receiver operating characteristic, Speech recognition, Pattern recognition (psychology), support vector machines, Epilepsy Detection, EEG Analysis, Artificial Intelligence, Machine learning, permutation entropy, QA1-939, Deep Learning for EEG, signal classification, Life Sciences, zero crossing rate, Neural Network Fundamentals and Applications, Brain-Computer Interfaces in Neuroscience and Medicine, Computer science, K-nearest neighbours, auditory evoked potentials, Computer Science, Physical Sciences, Signal Processing, Wavelet, random forest, Lyapunov exponent, Mathematics, Neuroscience

File Description: text/html

Access URL: https://doaj.org/article/e062e8e7750444f8b631d424745d869f
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2676-00292023000100063&lng=en&tlng=en

Dipper Throated Algorithm for Feature Selection and Classification in Electrocardiogram

Authors: Doaa Sami Khafaga, Amel Ali Alhussan, Abdelaziz A. Abdelhamid, Abdelhameed Ibrahim‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Mohamed Saber, El-Sayed M. El-kenawy

Source: Computer Systems Science and Engineering. 45:1469-1482

Subject Terms: Pulmonary and Respiratory Medicine, Artificial intelligence, Cognitive Neuroscience, Feature (linguistics), 02 engineering and technology, Heartbeat Classification, Pattern recognition (psychology), Cardiac arrhythmia, EEG Analysis, Electrocardiography, Analysis of Cardiac and Respiratory Sounds, Selection (genetic algorithm), Health Sciences, Machine learning, Arrhythmia Detection, 0202 electrical engineering, electronic engineering, information engineering, Deep Learning for EEG, Data mining, Internal medicine, 4. Education, Life Sciences, Statistical classification, Linguistics, Analysis of Electrocardiogram Signals, Brain-Computer Interfaces in Neuroscience and Medicine, Computer science, Atrial fibrillation, FOS: Philosophy, ethics and religion, 3. Good health, Philosophy, Categorization, Feature selection, FOS: Languages and literature, Medicine, Feature extraction, Cardiac Health Diagnosis, Classifier (UML), Cardiology and Cardiovascular Medicine, Neuroscience

Electroencephalography and mild cognitive impairment research: A scoping review and bibliometric analysis (ScoRBA)

Authors: Adi Wijaya, Noor Akhmad Setiawan, Asma Hayati Ahmad, Rahimah Zakaria, Zahiruddin Othman

Source: AIMS Neurosci
AIMS Neuroscience, Vol 10, Iss 2, Pp 154-171 (2023)

Subject Terms: scorba, FOS: Computer and information sciences, Mild Cognitive Impairment, Cognitive Neuroscience, Neurosciences. Biological psychiatry. Neuropsychiatry, Machine Learning (stat.ML), Neuroimaging, Review, Analysis of Brain Functional Connectivity Networks, Epilepsy Detection, 03 medical and health sciences, EEG Analysis, mild cognitive impairment, bibliometric analysis, 0302 clinical medicine, Cognition, Statistics - Machine Learning, Health Sciences, Psychology, Deep Learning for EEG, Life Sciences, Electroencephalography, Brain-Computer Interfaces in Neuroscience and Medicine, Diagnosis and Management of Alzheimer's Disease, Computer science, 3. Good health, FOS: Psychology, Psychiatry and Mental health, Cognitive impairment, Quantitative electroencephalography, Quantitative Biology - Neurons and Cognition, FOS: Biological sciences, Medicine, Neurons and Cognition (q-bio.NC), scoping review, electroencephalography, RC321-571, Neuroscience

Access URL: https://pubmed.ncbi.nlm.nih.gov/37426780
http://arxiv.org/abs/2211.00302
https://doaj.org/article/db50e682b1fd4ec6a61154e28c6fce7d

Design and Development of Low-cost Wearable Electroencephalograms (EEG) Headset

Authors: Muhammad Riaz, Ahmed Ali, M. Abid Anwar, Toufique Ahmed Soomro, Omar AlShorman, Adel Alshahrani, Mahmoud Masadeh, Ghulam Md Ashraf, Naif H. Ali, Muhammad Irfan, Athanasios Alexiou

Source: Intelligent Automation & Soft Computing. 35:2821-2835

Subject Terms: Artificial intelligence, Cognitive Neuroscience, Set (abstract data type), Noise (video), 02 engineering and technology, Headset, Pattern recognition (psychology), 7. Clean energy, Epilepsy Detection, Cellular and Molecular Neuroscience, EEG Analysis, Engineering, Image (mathematics), 0202 electrical engineering, electronic engineering, information engineering, Deep Learning for EEG, Embedded system, Neuronal Oscillations in Cortical Networks, Psychiatry, Radar, Life Sciences, Electroencephalography, Wearable computer, Waveform, Computer hardware, Neural Interface Technology, Brain-Computer Interfaces in Neuroscience and Medicine, 16. Peace & justice, Computer science, Programming language, SIGNAL (programming language), Electrical engineering, Telecommunications, Medicine, Wavelet, Headphones, Neuroscience

Voluntary Respiration Control: Signature Analysis by EEG

Authors: Yue Wang, Yan Zhang, Y.G. Zhang, Zongyu Wang, Weidong Guo, Yuru Zhang, Yuhui Wang, Qi Ge, Dangxiao Wang

Source: IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 4624-4634 (2023)

Subject Terms: Consciousness, Cognitive Neuroscience, Non-contact Physiological Monitoring Technology, Biomedical Engineering, sample entropy, RM1-950, FOS: Medical engineering, Pattern recognition (psychology), Pulse Oximetry, EEG Analysis, Engineering, Respiratory Rate, PLV, Cognitive psychology, Health Sciences, Medical technology, Humans, Psychology, EEG, Deep Learning for EEG, R855-855.5, Scalp, Respiration, Cortical Control, Brain, Life Sciences, Electroencephalography, Audiology, Brain-Computer Interfaces in Neuroscience and Medicine, FOS: Psychology, Sample entropy, Analysis and Applications of Heart Rate Variability, Physical Sciences, Emotion Regulation, Medicine, Therapeutics. Pharmacology, Anatomy, Cardiology and Cardiovascular Medicine, Neuroscience

Access URL: https://pubmed.ncbi.nlm.nih.gov/37955998
https://doaj.org/article/de27b0a240ca49a293b493321b13b93f

Automatic Detection of Outliers in Multi-Channel EMG Signals Using MFCC and SVM

Authors: Muhammad Irfan, Khalil Ullah, Fazal Muhammad, Salman A. Khan, Faisal Althobiani, Muhammad Usman, Mohammed Alshareef, Shadi Alghaffari, Saifur Rahman

Source: Intelligent Automation & Soft Computing. 36:169-181

Subject Terms: Artificial intelligence, Support vector machine, Linear discriminant analysis, Cognitive Neuroscience, Biomedical Engineering, Surface EMG, Noise (video), Speech recognition, FOS: Medical engineering, Pattern recognition (psychology), Epilepsy Detection, EEG Analysis, Engineering, Health Sciences, Arrhythmia Detection, Image (mathematics), Deep Learning for EEG, Computer network, 4. Education, Life Sciences, Analysis of Electrocardiogram Signals, Brain-Computer Interfaces in Neuroscience and Medicine, Computer science, Subspace topology, Analysis of Electromyography Signal Processing, Channel (broadcasting), Outlier, Physical Sciences, Medicine, Mel-frequency cepstrum, Feature extraction, Classifier (UML), Cardiology and Cardiovascular Medicine, Neuroscience

BiTCAN: An emotion recognition network based on saliency in brain cognition

Authors: Yanling An, Shaohai Hu, Shuaiqi Liu, Bing Li

Source: Mathematical Biosciences and Engineering, Vol 20, Iss 12, Pp 21537-21562 (2023)

Subject Terms: Artificial intelligence, Cognitive Neuroscience, Emotions, Social Sciences, Experimental and Cognitive Psychology, Lateralization of brain function, Convolutional neural network, bi-hemispheric discrepancy, Speech recognition, Pattern recognition (psychology), EEG Analysis, Cognition, Artificial Intelligence, Cognitive psychology, emotion recognition, spatial attention, QA1-939, Psychology, Eye Tracking in Human-Computer Interaction, Deep Learning for EEG, spatio-temporal features, Brain, Life Sciences, Electroencephalography, Brain-Computer Interfaces in Neuroscience and Medicine, Computer science, FOS: Psychology, Human-Computer Interaction, Head Gesture Recognition, Emotion Recognition, Computer Science, Physical Sciences, Affective Computing, Emotion recognition, eeg, Classifier (UML), attention mechanism, TP248.13-248.65, Mathematics, Algorithms, Biotechnology, Emotion Recognition and Analysis in Multimodal Data, Neuroscience

Access URL: https://pubmed.ncbi.nlm.nih.gov/38124609
https://doaj.org/article/35f52e5c3d4a4daab5ba9da096d97a60

A convolutional neural network-based decision support system for neonatal quiet sleep detection

Authors: Saadullah Farooq Abbasi, Qammer H. Abbasi, Faisal Saeed, Norah Saleh Alghamdi

Source: Mathematical Biosciences and Engineering, Vol 20, Iss 9, Pp 17018-17036 (2023)

Subject Terms: Pooling, China, Artificial intelligence, Cognitive Neuroscience, Polysomnography, convolutional neural network, Health Professions, Convolutional neural network, Pharmacy, Pattern recognition (psychology), Epilepsy Detection, polysomnography, biomedical engineering, Health Sciences, Machine learning, QA1-939, Humans, Psychology, Deep Learning for EEG, Sleep (system call), Child, Infant Crying and Colic Studies, Infant, Newborn, Life Sciences, Electroencephalography, Brain-Computer Interfaces in Neuroscience and Medicine, Neonatal Brain Injury and Developmental Consequences, Computer science, 3. Good health, FOS: Psychology, Operating system, neonatal sleep, Pediatrics, Perinatology and Child Health, Medicine, Computer vision, Neural Networks, Computer, Sleep Stages, Sleep, CAH11-01-01 - computer science, electroencephalography, TP248.13-248.65, Mathematics, Algorithms, Biotechnology, Neuroscience, Smoothing

File Description: text

Access URL: https://pubmed.ncbi.nlm.nih.gov/37920045
https://doaj.org/article/50876898aa1f483ca6af8fb1650fcde4