Search results for "Affective Computing"

showing 10 items of 22 documents

Détection automatique des repères visuels associés à la dépression

2018

Depression is the most prevalent mood disorder worldwide having a significant impact on well-being and functionality, and important personal, family and societal effects. The early and accurate detection of signs related to depression could have many benefits for both clinicians and affected individuals. The present work aimed at developing and clinically testing a methodology able to detect visual signs of depression and support clinician decisions.Several analysis pipelines were implemented, focusing on motion representation algorithms, including Local Curvelet Binary Patterns-Three Orthogonal Planes (LCBP-TOP), Local Curvelet Binary Patterns- Pairwise Orthogonal Planes (LCBP-POP), Landma…

DepressionReconnaissance de formesImage Processing[SDV.MHEP.PSM] Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Pattern RecognitionTraitement d'image[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]Informatique affective[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental healthAffective Computing[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM][INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
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Filtering of Spontaneous and Low Intensity Emotions in Educational Contexts

2015

Affect detection is a challenging problem, even more in educational contexts, where emotions are spontaneous and usually subtle. In this paper, we propose a two-stage detection approach based on an initial binary discretization followed by a specific emotion prediction stage. The binary classification method uses several distinct sources of information to detect and filter relevant time slots from an affective point of view. An accuracy close to 75% at detecting whether the learner has felt an educationally relevant emotion on 20 second time slots has been obtained. These slots can then be further analyzed by a second classifier, to determine the specific user emotion.

DiscretizationPoint (typography)Binary classificationComputer scienceSpeech recognitionClassifier (linguistics)Binary numberFilter (signal processing)Affective computingAffect (psychology)
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APIS to extract information in social channels in educational context

2018

In this days the world is involved in the research and development of new resources, and methods that allow the use of new technologies fulfilling a goal that is the learning of education through the Web, thus using resources such as different APIs for different purposes. Taking into account the functionalities provided by the APIs, the objective was to obtain information about the different educational resources in the social channels of the Universidad Tecnica Particular de Loja (UTPL). The study of pervious APIs is a part of the project Use of Cloud Computing tools, Bodies of Knowledge and affective computing in the process of developing technological skills focused on problem solving of…

Emerging technologiesComputer sciencebusiness.industry020207 software engineeringCloud computing02 engineering and technologyWorld Wide WebBody of knowledgeEngineering educationEducational resources0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingbusinessAffective computingCoding (social sciences)2018 13th Iberian Conference on Information Systems and Technologies (CISTI)
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Semantic Computing of Moods Based on Tags in Social Media of Music

2014

Social tags inherent in online music services such as Last.fm provide a rich source of information on musical moods. The abundance of social tags makes this data highly beneficial for developing techniques to manage and retrieve mood information, and enables study of the relationships between music content and mood representations with data substantially larger than that available for conventional emotion research. However, no systematic assessment has been done on the accuracy of social tags and derived semantic models at capturing mood information in music. We propose a novel technique called Affective Circumplex Transformation (ACT) for representing the moods of music tracks in an interp…

FOS: Computer and information sciencesVocabularyComputer scienceMusic information retrievalmedia_common.quotation_subjectSemantic analysis (machine learning)Moodscomputer.software_genreAffect (psychology)SemanticsComputer Science - Information RetrievalSemantic computingMusic information retrievalAffective computingmedia_commonSocial and Information Networks (cs.SI)ta113Probabilistic latent semantic analysisSocial tagsbusiness.industryComputer Science - Social and Information NetworksMultimedia (cs.MM)Semantic analysisComputer Science ApplicationsMoodComputational Theory and MathematicsWeb miningta6131Vector space modelArtificial intelligenceGenresbusinesscomputerComputer Science - MultimediaInformation Retrieval (cs.IR)MusicNatural language processingPrediction.Information SystemsIEEE Transactions on Knowledge and Data Engineering
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Video-based Pain Level Assessment: Feature Selection and Inter-Subject Variability Modeling

2018

Automatic pain level assessment, based on video features, may provide clinically-relevant, objective measures of pain intensity. In various clinical contexts accurate pain level estimation by health care personnel is challenging. This problem is compounded by considerable inter- and intra-individual variability of both perceived pain levels and of the associated facial expressions, especially at low pain levels. Thus, providing objective video-based indices for pain level assessment is a rather computationally challenging problem. In the present work both geometric and color-based features were extracted. The most informative features were identified with lasso regression, and subject varia…

Facial expressionbusiness.industryComputer scienceImage processingFeature selection02 engineering and technologyMachine learningcomputer.software_genre03 medical and health sciences0302 clinical medicine030225 pediatricsPain level0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligenceAffective computingbusinesscomputer2018 41st International Conference on Telecommunications and Signal Processing (TSP)
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Sonification of Emotion : Strategies for Continuous Display of Arousal and Valence

2013

Sonification is an interdisciplinary field of research broadly interested in the use of sound to convey information. A fundamental attribute of sound is its ability to evoke emotion, but the display of emotion as a continuous data type has not yet received adequate attention. This paper motivates the use of sonification for display of emotion in affective computing, and as a means of targeting mechanisms of emotion elicitation in music. Environmental sound and music are presented as two possible sources for non-verbal auditory emotion elicitation, each with specific determinants and available features. The review concludes that the auditory-cognitive mechanisms of brain-stem reflex and emot…

InformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g.HCI)sonificationpsychoacoustic cuesaffective computing
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An Intra-Subject Approach Based on the Application of HMM to Predict Concentration in Educational Contexts from Nonintrusive Physiological Signals in…

2021

Previous research has proven the strong influence of emotions on student engagement and motivation. Therefore, emotion recognition is becoming very relevant in educational scenarios, but there is no standard method for predicting students’ affects. However, physiological signals have been widely used in educational contexts. Some physiological signals have shown a high accuracy in detecting emotions because they reflect spontaneous affect-related information, which is fresh and does not require additional control or interpretation. Most proposed works use measuring equipment for which applicability in real-world scenarios is limited because of its high cost and intrusiveness. To tackle this…

IntrusivenessComputer scienceEmotionsControl (management)Student engagementContext (language use)02 engineering and technologyuser-centred systemsLearner modellinglcsh:Chemical technologyNonintrusiveMachine learningcomputer.software_genre01 natural sciencesBiochemistryArticleAnalytical ChemistryTask (project management)Heart RateUser-centred systems0202 electrical engineering electronic engineering information engineeringHumanslcsh:TP1-1185Electrical and Electronic EngineeringAffective computingHidden Markov modelaffective computingInstrumentationInformáticabusiness.industry010401 analytical chemistrynonintrusiveAffective computingComputer scienceAtomic and Molecular Physics and Opticsphysiological sensors0104 chemical scienceslearner modellingPhysiological sensors020201 artificial intelligence & image processingArtificial intelligenceState (computer science)Skin TemperaturebusinesscomputerSensors
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On the Convergence of Affective and Persuasive Technologies in Computer-Mediated Health-Care Systems

2015

This paper offers a portrayal of how affective computing and persuasive technologies can converge into an effective tool for interfacing biomedical engineering with behavioral sciences and medicine. We describe the characteristics, features, applications, present state of the art, perspectives, and trends of both streams of research. In particular, these streams are analyzed in light of the potential contribution of their convergence for improving computer-mediated health-care systems, by facilitating the modification of patients’ attitudes and behaviors, such as engagement and compliance. We propose a framework for future research in this emerging area, highlighting how key constructs and …

Knowledge managementSocial PsychologyBehavioural sciences02 engineering and technologyPersuasive technologyMultimodalityHealth care0202 electrical engineering electronic engineering information engineeringcomputer-mediated health careAffective computingaffective computingpersuasive technologylcsh:T58.5-58.64patient engagementbusiness.industrylcsh:Information technologyCommunication05 social sciences050301 education020207 software engineeringpatient motivationHuman-Computer InteractionCost reductionParadigm shiftConvergence (relationship)businessPsychology0503 education
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Automatic Assessment of Depression Based on Visual Cues: A Systematic Review

2019

International audience; Automatic depression assessment based on visual cues is a rapidly growing research domain. The present exhaustive review of existing approaches as reported in over sixty publications during the last ten years focuses on image processing and machine learning algorithms. Visual manifestations of depression, various procedures used for data collection, and existing datasets are summarized. The review outlines methods and algorithms for visual feature extraction, dimensionality reduction, decision methods for classification and regression approaches, as well as different fusion strategies. A quantitative meta-analysis of reported results, relying on performance metrics r…

MonitoringRating-ScaleRemissionComputer sciencePerformanceFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyAdolescentscomputer.software_genreToolsAttentional Bias[SPI]Engineering Sciences [physics]03 medical and health sciences0302 clinical medicineDynamic-AnalysisMoodDiagnosisDisorder[ SPI ] Engineering Sciences [physics]0202 electrical engineering electronic engineering information engineeringaffective computingAffective computingSensory cueComputingMilieux_MISCELLANEOUSVisualizationFacial expressionData collectionContextual image classificationbusiness.industryDimensionality reductionfacial image analysisReliabilityVisualizationEuropeFacial ExpressionHuman-Computer Interactionmachine learningDepression assessment020201 artificial intelligence & image processingArtificial intelligencebusinesscomputer030217 neurology & neurosurgerySoftwareNatural language processingIEEE Transactions on Affective Computing
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BIG-AFF

2017

Recent research has provided solid evidence that emotions strongly affect motivation and engagement, and hence play an important role in learning. In BIG-AFF project, we build on the hypothesis that ``it is possible to provide learners with a personalised support that enriches their learning process and experience by using low intrusive (and low cost) devices to capture affective multimodal data that include cognitive, behavioural and physiological information''. In order to deal with the affect management complete cycle, thus covering affect detection, modelling and feedback, there is lack of standards and consolidated methodologies. Being our goal to develop realistic affect-aware learnin…

Process (engineering)Computer scienceMultimodal data05 social sciences050301 educationCognition02 engineering and technologyAffect (psychology)Data scienceUser studiesWork (electrical)Human–computer interactionOrder (exchange)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingAffective computing0503 educationAdjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization
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