[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Yousefi et al., 2023 - Google Patents

Enhancing the accuracy of electroencephalogram-based emotion recognition through Long Short-Term Memory recurrent deep neural networks

Yousefi et al., 2023

View HTML
Document ID
6171116763866974188
Author
Yousefi M
Dehghani A
Taghaavifar H
Publication year
Publication venue
Frontiers in Human Neuroscience

External Links

Snippet

Introduction Emotions play a critical role in human communication, exerting a significant influence on brain function and behavior. One effective method of observing and analyzing these emotions is through electroencephalography (EEG) signals. Although numerous …
Continue reading at www.frontiersin.org (HTML) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/345Medical expert systems, neural networks or other automated diagnosis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/3487Medical report generation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/32Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/02Knowledge representation
    • G06N5/022Knowledge engineering, knowledge acquisition
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00Digital computers in general; Data processing equipment in general
    • G06F15/18Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/7264Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/16Devices for psychotechnics; Testing reaction times; Devices for evaluating the psychological state
    • A61B5/165Evaluating the state of mind, e.g. depression, anxiety

Similar Documents

Publication Publication Date Title
Xu et al. A one-dimensional CNN-LSTM model for epileptic seizure recognition using EEG signal analysis
Chakravarthi et al. EEG-based emotion recognition using hybrid CNN and LSTM classification
Özerdem et al. Emotion recognition based on EEG features in movie clips with channel selection
Khanam et al. Electroencephalogram-based cognitive load level classification using wavelet decomposition and support vector machine
Dastgoshadeh et al. Detection of epileptic seizures through EEG signals using entropy features and ensemble learning
Rahul et al. A systematic review of EEG based automated schizophrenia classification through machine learning and deep learning
Gao et al. EEG driving fatigue detection based on log-Mel spectrogram and convolutional recurrent neural networks
Yousefi et al. Enhancing the accuracy of electroencephalogram-based emotion recognition through Long Short-Term Memory recurrent deep neural networks
Mahato et al. Analysis of region of interest (RoI) of brain for detection of depression using EEG signal
Al-hajjar et al. Epileptic seizure detection using feature importance and ML classifiers
Li et al. An innovative EEG-based emotion recognition using a single channel-specific feature from the brain rhythm code method
Jehosheba Margaret et al. Performance analysis of EEG based emotion recognition using deep learning models
Li et al. Diagnosis of Alzheimer's disease by feature weighted-LSTM: a preliminary study of temporal features in brain resting-state fMRI
Radhakrishnan et al. A hybrid model for the classification of Autism Spectrum Disorder using Mu rhythm in EEG
Kumar et al. Early detection of depression through facial expression recognition and electroencephalogram-based artificial intelligence-assisted graphical user interface
Woodward et al. Combining deep learning with signal-image encoding for multi-modal mental wellbeing classification
Mohammad et al. Tri-model classifiers for EEG based mental task classification: Hybrid optimization assisted framework
Wang et al. Cognitive Workload Estimation in Conditionally Automated Vehicles Using Transformer Networks Based on Physiological Signals
Priyadarshani et al. Human brain waves study using EEG and deep learning for emotion recognition
Zhang et al. Positional multi-length and mutual-attention network for epileptic seizure classification
Mishra et al. Realization of EEG based multi-label classification with convolutional neural networks
Najmusseher et al. Impact of feature selection techniques for EEG-based seizure classification
Malathi et al. Parkinson disease prediction using improved crayfish optimization based hybrid deep learning
Chahar et al. An Efficient K NN Algorithm for the Mental Health Performance Assessment Using K-means Clustering
Wang et al. Retracted: Self‐attention Bi‐RNN for developer emotion recognition based on EEG