Nothing Special   »   [go: up one dir, main page]

Ahmed et al., 2023 - Google Patents

A systematic survey on multimodal emotion recognition using learning algorithms

Ahmed et al., 2023

View HTML
Document ID
3084503499614334252
Author
Ahmed N
Al Aghbari Z
Girija S
Publication year
Publication venue
Intelligent Systems with Applications

External Links

Snippet

Emotion recognition is the process to detect, evaluate, interpret, and respond to people's emotional states and emotions, ranging from happiness to fear to humiliation. The COVID-19 epidemic has provided new and essential impetus for emotion recognition research. The …
Continue reading at www.sciencedirect.com (HTML) (other versions)

Classifications

    • 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
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
    • G06F3/015—Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection
    • 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
    • G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/02—Knowledge representation
    • G06N5/022—Knowledge engineering, knowledge acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00—Digital computers in general; Data processing equipment in general
    • G06F15/18—Digital 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
    • 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
    • A61B5/16—Devices for psychotechnics; Testing reaction times; Devices for evaluating the psychological state
    • A61B5/165—Evaluating the state of mind, e.g. depression, anxiety
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/20—Education
    • 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
    • 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

Similar Documents

Publication Publication Date Title
Ahmed et al. A systematic survey on multimodal emotion recognition using learning algorithms
Dewan et al. Engagement detection in online learning: a review
Lim et al. Emotion recognition using eye-tracking: taxonomy, review and current challenges
Cavallo et al. Emotion modelling for social robotics applications: a review
Chen et al. Analyze spontaneous gestures for emotional stress state recognition: A micro-gesture dataset and analysis with deep learning
Kandemir et al. Multi-task and multi-view learning of user state
Saffaryazdi et al. Using facial micro-expressions in combination with EEG and physiological signals for emotion recognition
Guthier et al. Affective computing in games
Liu et al. Learning analytics based on wearable devices: A systematic literature review from 2011 to 2021
Liu et al. P300 event-related potential detection using one-dimensional convolutional capsule networks
Samal et al. Role of machine learning and deep learning techniques in EEG-based BCI emotion recognition system: a review
Kim et al. ALIS: Learning affective causality behind daily activities from a wearable life-log system
Sukumaran et al. A survey on automatic engagement recognition methods: online and traditional classroom
Ismail et al. A systematic review of emotion recognition using cardio-based signals
Blackmore et al. Integrating Biofeedback and Artificial Intelligence into eXtended Reality Training Scenarios: A Systematic Literature Review
Kannadasan et al. An EEG-Based Computational Model for Decoding Emotional Intelligence, Personality, and Emotions
Akhtar et al. Visual nonverbal behavior analysis: The path forward
Kumar et al. Measuring Non-Typical Emotions for Mental Health: A Survey of Computational Approaches
Gaudi et al. Affective computing: an introduction to the detection, measurement, and current applications
Adebiyi et al. Affective e-learning approaches, technology and implementation model: a systematic review.
Yang et al. Wearable Structured Mental-Sensing-Graph Measurement
Zhang et al. Multimodal Fast–Slow Neural Network for learning engagement evaluation
Perry Fordson et al. Hyper-Enhanced Feature Learning System for Emotion Recognition
Yates Affective intelligence in built environments
Verma Multimodal Affective Computing: Affective Information Representation, Modelling, and Analysis