[go: up one dir, main page]

Bourbakis et al., 2022 - Google Patents

A new multi-resolution approach to EEG brain modeling using local-global graphs and stochastic petri-nets

Bourbakis et al., 2022

Document ID
5113883855902394737
Author
Bourbakis N
Michalopoulos K
Antonakakis M
Zervakis M
Publication year
Publication venue
International Journal of Neural Systems

External Links

Snippet

Recent modeling of brain activities encompasses the fusion of different modalities. However, fusing brain modalities requires not only the efficient and compatible representation of the signals but also the benefits associated with it. For instance, the combination of the …
Continue reading at www.worldscientific.com (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34—Computer-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
    • G06F19/345—Medical expert systems, neural networks or other automated diagnosis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • G06K9/00268—Feature extraction; Face representation
    • G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0476—Electroencephalography
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00496—Recognising patterns in signals and combinations thereof
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0402—Electrocardiography, i.e. ECG
    • A61B5/0452—Detecting specific parameters of the electrocardiograph cycle
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions

Similar Documents

Publication Publication Date Title
Ramos-Aguilar et al. Feature extraction from EEG spectrograms for epileptic seizure detection
Zhao et al. Deep learning in the EEG diagnosis of Alzheimer’s disease
Herrera et al. Combination of heterogeneous EEG feature extraction methods and stacked sequential learning for sleep stage classification
JP2020537583A (en) Methods of determining the subject's visual attention focus from brainwave signals, computer programs, computer systems and systems that determine the subject's visual attention focus from brainwave signals
CN118737477B (en) Method, device, equipment and medium for constructing digital twin brain mechanism model
CN116189881A (en) A method and system for formulating an individualized control strategy for task-state functional magnetic resonance
CN115813409A (en) Ultra-low-delay moving image electroencephalogram decoding method
CN118013340A (en) EEG recognition method and system based on temporal self-attention and dynamic graph convolution
Gagliardi et al. Improving emotion recognition systems by exploiting the spatial information of EEG sensors
Varghese et al. Transformer-based temporal sequence learners for arrhythmia classification
Bunterngchit et al. Simultaneous EEG-fNIRS data classification through selective channel representation and spectrogram imaging
CN120340784A (en) A medical image automatic diagnosis method and system based on deep learning
CN119324057B (en) Construction method and system for nerve rehabilitation evaluation model
Bourbakis et al. A new multi-resolution approach to EEG brain modeling using local-global graphs and stochastic petri-nets
Gao et al. Graph convolutional neural network based emotion recognition with brain functional connectivity network
Santos et al. Efficient classification of depression using eeg through spectral graph analysis
Lv et al. A novel recognition and classification approach for motor imagery based on spatio-temporal features
Dehgan et al. Artificial Neural Networks for Magnetoencephalography: A review of an emerging field
Abdulrahman et al. Human identification based on electroencephalography signals using sample entropy and horizontal visibility graphs
Li CNN-based image analysis for EEG signal characterization
Sharmila et al. Integrative Approach for Epileptic Seizure Detection: A Comparative Analysis
Ke et al. Exploring smri biomarkers for diagnosis of autism spectrum disorders based on multi class activation mapping models
Rajinikanth et al. Biomedical Signal and Image Examination with Entropy-Based Techniques
CN119649158B (en) Image feature selection method for Spark model of schizophrenia medical records
Gao frontiers| Frontiers in Neuroscience