Search results for: affective computing
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Affective computing and affective learning – methods, tools and prospects
PublicationEvery teacher knows that interest, active participation and motivation are important factors in the learning process. At the same time e-learning environments almost always address only the cognitive aspects of education. This paper provides a brief review of methods used for affect recognition, representation and processing as well as investigates how these methods may be used to address affective aspect of e-education. The paper...
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Investigation of educational processes with affective computing methods
PublicationThis paper concerns the monitoring of educational processes with the use of new technologies for the recognition of human emotions. This paper summarizes results from three experiments, aimed at the validation of applying emotion recognition to e-learning. An analysis of the experiments’ executions provides an evaluation of the emotion elicitation methods used to monitor learners. The comparison of affect recognition algorithms...
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A note on the affective computing systems and machines: a classification and appraisal
PublicationAffective computing (AfC) is a continuously growing multidisciplinary field, spanning areas from artificial intelligence, throughout engineering, psychology, education, cognitive science, to sociology. Therefore, many studies have been devoted to the aim of addressing numerous issues, regarding different facets of AfC solutions. However, there is a lack of classification of the AfC systems. This study aims to fill this gap by reviewing...
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IEEE Transactions on Affective Computing
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Affective Computing
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International Conference on Affective Computing and Intelligent
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Agnieszka Landowska dr hab. inż.
PeopleAgnieszka Landowska works for Gdansk University of Technology, FETI, Department of Software Engineering. Her research concentrates on usability, accessibility and technology adoption, as well as affective computing methods. She initiated Emotions in HCI Research Group and conducts resarch on User eXperiene evaluation of applications and other technologies.
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Affective Learning Manifesto – 10 Years Later
PublicationIn 2004 a group of affective computing researchers proclaimed a manifesto of affective learning that outlined the prospects and white spots of research at that time. Ten years passed by and affective computing developed many methods and tools for tracking human emotional states as well as models for affective systems construction. There are multiple examples of affective methods applications in Intelligent Tutoring Systems (ITS)....
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Michał Wróbel dr inż.
PeopleMichał Wróbel, Assistant Professor of Gdańsk University of Technology, computer scientist, a specialist in software engineering. I graduated from the Faculty of Electronics Technical University of Gdansk in 2002 with a degree in Computer Science, with specialization in Software Engineering and Databases. Until 2006 I worked as system administrator in several companies, including CI TASK. Since 2006 I have been working at the Faculty...
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Graph Representation Integrating Signals for Emotion Recognition and Analysis
PublicationData reusability is an important feature of current research, just in every field of science. Modern research in Affective Computing, often rely on datasets containing experiments-originated data such as biosignals, video clips, or images. Moreover, conducting experiments with a vast number of participants to build datasets for Affective Computing research is time-consuming and expensive. Therefore, it is extremely important to...
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How to Design Affect-aware Educational Systems – the AFFINT Process Approach
PublicationComputer systems, that support learning processes, can adapt to the needs and states of a learner. The adaptation might directly address the knowledge deficits and most tutoring systems apply an adaptable learning path of that kind. Apart from a preliminary knowledge state, there are more factors, that influence education effectiveness and among those there are fluctuating emotional states. The tutoring systems may recognize or...
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Ontological Model for Contextual Data Defining Time Series for Emotion Recognition and Analysis
PublicationOne of the major challenges facing the field of Affective Computing is the reusability of datasets. Existing affective-related datasets are not consistent with each other, they store a variety of information in different forms, different formats, and the terms used to describe them are not unified. This paper proposes a new ontology, ROAD, as a solution to this problem, by formally describing the datasets and unifying the terms...
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Ontological Modeling for Contextual Data Describing Signals Obtained from Electrodermal Activity for Emotion Recognition and Analysis
PublicationMost of the research in the field of emotion recognition is based on datasets that contain data obtained during affective computing experiments. However, each dataset is described by different metadata, stored in various structures and formats. This research can be counted among those whose aim is to provide a structural and semantic pattern for affective computing datasets, which is an important step to solve the problem of data...
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Limitations of Emotion Recognition in Software User Experience Evaluation Context
PublicationThis paper concerns how an affective-behavioural- cognitive approach applies to the evaluation of the software user experience. Although it may seem that affect recognition solutions are accurate in determining the user experience, there are several challenges in practice. This paper aims to explore the limitations of the automatic affect recognition applied in the usability context as well as...
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Human emotion recognition with biosignals
PublicationThis chapter presents issues in the field of affective computing. Basic preliminary information for the recognition of emotions is given and models of emotions, various ways of evoking emotions, as well as their theoretical foundations are discussed. The particular attention is given to the use of physiological signals in recognizing emotions. This subject is outlined further below by presenting selected biosignals, their relationship...
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A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone Sensors
PublicationIn recent years, emotion recognition algorithms have achieved high efficiency, allowing the development of various affective and affect-aware applications. This advancement has taken place mainly in the environment of personal computers offering the appropriate hardware and sufficient power to process complex data from video, audio, and other channels. However, the increase in computing and communication capabilities of smartphones,...
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Applicability of Emotion Recognition and Induction Methods to Study the Behavior of Programmers
PublicationRecent studies in the field of software engineering have shown that positive emotions can increase and negative emotions decrease the productivity of programmers. In the field of affective computing, many methods and tools to recognize the emotions of computer users were proposed. However, it has not been verified yet which of them can be used to monitor the emotional states of software developers. The paper describes a study carried...
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Emotion Recognition from Physiological Channels Using Graph Neural Network
PublicationIn recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...
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IMAGE CORRELATION AS A TOLL FOR TRACKING FACIAL CHANGES CAUSING BY EXTERNAL STIMULI
PublicationExpressions of the human face bring a lot of information, which are a valuable source in the areas of computer vision, remote sensing and affective computing. For years, by analyzing the movement of the skin and facial muscles scientists are trying to create the perfect tool, based on image analysis, allowing the recognition of emotional states of human beings. To create a reliable algorithm, it is necessary to explore and examine...
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Michał Czubenko dr inż.
PeopleMichał Czubenko is a distinguished 2009 graduate of the Faculty of Electronics, Telecommunications, and Informatics at Gdańsk University of Technology, specializing in the discipline of automatic control and robotics. Currently, he serves as an adjunct in the Department of Robotics and Decision Systems at the same institution. In 2012, he embarked on a three-month internship at Kingston University London, broadening his horizons...