Liu et al., 2009 - Google Patents

Dynamic difficulty adjustment in computer games through real-time anxiety-based affective feedback

Liu et al., 2009

Document ID
84482398623502156
Author
Liu C
Agrawal P
Sarkar N
Chen S
Publication year
Publication venue
International Journal of Human-Computer Interaction

External Links

Snippet

A number of studies in recent years have investigated the dynamic difficulty adjustment (DDA) mechanism in computer games to automatically tailor gaming experience to individual player's characteristics. Although most of these existing works focus on game …
Continue reading at www.tandfonline.com (other versions)

Classifications

    • 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F3/00Input 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
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/011Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
    • G06F3/015Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0476Electroencephalography
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/48Other medical applications
    • 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
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/74Details of notification to user or communication with user or patient ; user input means
    • 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

Similar Documents

Publication Publication Date Title
Liu et al. Dynamic difficulty adjustment in computer games through real-time anxiety-based affective feedback
Vasiljevic et al. Brain–computer interface games based on consumer-grade EEG Devices: A systematic literature review
Mandryk et al. The potential of game-based digital biomarkers for modeling mental health
Blankertz et al. The Berlin brain–computer interface: non-medical uses of BCI technology
Liu et al. Physiology-based affect recognition for computer-assisted intervention of children with Autism Spectrum Disorder
Lottridge et al. Affective interaction: understanding, evaluating, and designing for human emotion
Rani et al. Maintaining optimal challenge in computer games through real-time physiological feedback
Nacke Affective ludology: Scientific measurement of user experience in interactive entertainment
Moschovitis et al. Keep calm and aim for the head: Biofeedback-controlled dynamic difficulty adjustment in a horror game
CN114007705A (en) Brain-computer interface for computing systems
Darzi et al. Automated affect classification and task difficulty adaptation in a competitive scenario based on physiological linkage: An exploratory study
Bontchev et al. Affect-based adaptation of an applied video game for educational purposes
Ye et al. Flow experience detection and analysis for game users by wearable-devices-based physiological responses capture
Clerico et al. Biometrics and classifier fusion to predict the fun-factor in video gaming
Bekele et al. Psychophysiological feedback for adaptive human–robot interaction (HRI)
Yang et al. Designing mobile eeg neurofeedback games for children with autism
Foglia et al. Towards relating physiological signals to usability metrics: a case study with a web avatar
Rashed et al. A review of player engagement estimation in video games: Challenges and opportunities
Aloisio et al. Serious Games for ADHD: a narrative review.
Bilius et al. The age-reward perspective: a systematic review of reward mechanisms in serious games for older people
Mandryk Modeling user emotion in interactive play environments: A fuzzy physiological approach
Beaudoin-Gagnon et al. The funii database: A physiological, behavioral, demographic and subjective video game database for affective gaming and player experience research
Becker et al. Physiologically interactive gaming with the 3D agent Max
Liu et al. Affective state recognition and adaptation in human-robot interaction: A design approach
Agrawal et al. Interaction between human and robot: An affect-inspired approach