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===== Papers ===== | ===== Papers ===== | ||
- | ==== Sensors2019 ==== | + | === MRC2021b |
- | * **//" | + | * L. Żuchowska, K. Kutt, and G. J. Nalepa, "**Bartle Taxonomy-based Game for Affective |
- | * Abstract: In this paper, we consider the use of wearable sensors for providing affect-based adaptation in Ambient Intelligence (AmI) systems. We begin with discussion of selected issues regarding | + | * {{http://ceur-ws.org/ |
- | * DOI: 10.3390/ | + | * ++Abstract | The paper presents |
- | | + | === MRC2021a === |
+ | | ||
+ | * {{http://ceur-ws.org/Vol-2995/paper6.pdf|Full text available online}} | ||
+ | * ++Abstract | The paper provides insights into two main threads of analysis of the BIRAFFE2 dataset concerning the associations between personality and physiological signals and concerning the game logs' generation and processing. Alongside the presentation of results, we propose the generation of event-marked maps as an important step in the exploratory analysis of game data. The paper concludes with a set of guidelines for using games as a context-rich experimental environment.++ | ||
- | ==== ICAISC2019b | + | === Sensors2021 |
- | * **//"Affective Context-Aware Systems: | + | * K. Kutt, D. Drążyk, S. Bobek, and G. J. Nalepa, " |
- | * Abstract: Affective | + | * DOI: [[https:// |
+ | * [[https:// | ||
+ | * ++Abstract | In this article, we propose using personality assessment as a way to adapt affective intelligent systems. This psychologically-grounded mechanism will divide users into groups that differ in their reactions to affective stimuli for which the behaviour of the system can be adjusted. In order to verify the hypotheses, we conducted an experiment on 206 people, which consisted of two proof-of-concept demonstrations: | ||
+ | |||
+ | === ICAISC2020 | ||
+ | * S. Bobek, M. M. Tragarz, M. Szelążek, and G. J. Nalepa, "**Explaining Machine Learning Models of Emotion Using the BIRAFFE Dataset**," | ||
+ | * DOI: [[https://doi.org/ | ||
+ | * [[https:// | ||
+ | * ++Abstract | Development of models for emotion detection is often based on the use of machine learning. However, it poses practical challenges, due to the limited understanding of modeling of emotions, as well as the problems regarding measurements of bodily signals. In this paper we report on our recent work on improving such models, by the use of explainable AI methods. We are using the BIRAFFE data set we created previously during our own experiment in affective computing.++ | ||
+ | |||
+ | === HAIIW2020 === | ||
+ | * K. Kutt, D. Drążyk, M. Szelążek, S. Bobek, and G. J. Nalepa, | ||
+ | * [[https:// | ||
+ | * ++Abstract | The paper describes BIRAFFE2 data set, which is a result | ||
+ | |||
+ | === MRC2020 === | ||
+ | * L. Żuchowska, K. Kutt, K. Geleta, S. Bobek, and G. J. Nalepa, " | ||
+ | * {{http://ceur-ws.org/ | ||
+ | | ||
+ | |||
+ | === AfCAI2019 === | ||
+ | | ||
+ | * {{http:// | ||
+ | * ++Abstract | In this paper we introduce the BIRAFFE data set which is the result of the experiment in affective | ||
+ | |||
+ | === SEMANTiCS2019 === | ||
+ | * B. Giżycka, K. Kutt, and G. J. Nalepa, " | ||
+ | * {{http:// | ||
+ | * ++Abstract | Tools for automatization of knowledge on game mechanics | ||
+ | |||
+ | === Sensors2019 === | ||
+ | * G. J. Nalepa, K. Kutt, B. Giżycka, P. Jemioło, and S. Bobek, " | ||
+ | * DOI: 10.3390/ | ||
+ | * [[https:// | ||
+ | * ++Abstract | In this paper, we consider the use of wearable sensors for providing affect-based adaptation in Ambient Intelligence (AmI) systems. We begin with discussion of selected issues regarding the applications of affective computing techniques. We describe our experiments for affect change detection with a range of wearable devices, such as wristbands and the BITalino platform, and discuss an original software solution, which we developed | ||
+ | === ICAISC2019b === | ||
+ | * M. Z. Łępicki and S. Bobek, " | ||
* [[https:// | * [[https:// | ||
+ | * ++Abstract | Affective computing gained a lot of attention from researchers and business over the last decade. However, most of the attempts for building systems that try to predict, or provoke affective state of users were done for specific and narrow domains. This complicates reusing such systems in other, even similar domains. In this paper we present such a solution, that aims at solving such problem by providing a general framework architecture for building affective-aware systems. It supports designing and development of affective-aware solutions, in a holistic and domain independent way.++ | ||
- | ==== ICAISC2019a | + | === ICAISC2019a === |
- | * **//"Prototypes of Arcade Games Enabling Affective Interaction"//**, Paweł Jemioło, Barbara Giżycka i Grzegorz J. Nalepa | + | * P. Jemioło, B. Giżycka, and G. J. Nalepa, "**Prototypes of Arcade Games Enabling Affective Interaction**" |
* Presented at [[http:// | * Presented at [[http:// | ||
- | * Abstract: The use of emotions in the process of creating video games is still a challenge for the developers from the fields of Human-Computer Interaction and Affective Computing. In our work, we aim at demonstrating architectures of two operating game prototypes, implemented with the use of affective design patterns. We ground our account in biological signals, i.e. heart rate, galvanic skin response and muscle electrical activity. Using these modalities and the game context, we reason about emotional states of the player. For this purpose, we focus on defining rules with linguistic terms. What is more, we address the need for explainablity of biological mechanics and individual differences in terms of reactions to different stimuli. We provide a benchmark, in the form of a survey, to verify our approach. | ||
* DOI: 10.1007/ | * DOI: 10.1007/ | ||
- | |||
* {{ : | * {{ : | ||
+ | * ++Abstract | The use of emotions in the process of creating video games is still a challenge for the developers from the fields of Human-Computer Interaction and Affective Computing. In our work, we aim at demonstrating architectures of two operating game prototypes, implemented with the use of affective design patterns. We ground our account in biological signals, i.e. heart rate, galvanic skin response and muscle electrical activity. Using these modalities and the game context, we reason about emotional states of the player. For this purpose, we focus on defining rules with linguistic terms. What is more, we address the need for explainablity of biological mechanics and individual differences in terms of reactions to different stimuli. We provide a benchmark, in the form of a survey, to verify our approach.++ | ||
- | ==== CoSECiVi2018 | + | === CoSECiVi2018 === |
- | * **//"How a mobile platform for emotion identification supports designing affective games"//**, Grzegorz J. Nalepa, Barbara Giżycka | + | * G. J. Nalepa and B. Giżycka, "**How a mobile platform for emotion identification supports designing affective games**" |
* Presented at the [[https:// | * Presented at the [[https:// | ||
- | * Abstract: Afective | + | * {{https:// |
- | * [[https:// | + | * ++Abstract | Affective |
- | ==== GEM2018 | + | === GEM2018 === |
- | * **//"Emotion in models meets emotion in design: building true affective games"//**, Barbara Giżycka, Grzegorz J. Nalepa | + | * B. Giżycka and G. J. Nalepa, "**Emotion in models meets emotion in design: building true affective games**" |
* Presented at the [[http:// | * Presented at the [[http:// | ||
- | * Abstract: A relatively new field of research on affective gaming suggests applying affective computing solutions to develop games that can interact with the player on the emotional level. To bring together selected models of affect and affect-driven frameworks developed to date, we propose an approach based on affective design patterns. We build on the assumption that player’s emotional reactions to in-game events can be evoked by patterns used early in the design phase. We provide description of experiments conducted to test our hypothesis so far, along with some tentative observations, | ||
* DOI: 10.1109/ | * DOI: 10.1109/ | ||
- | |||
* {{ : | * {{ : | ||
+ | * ++Abstract | A relatively new field of research on affective gaming suggests applying affective computing solutions to develop games that can interact with the player on the emotional level. To bring together selected models of affect and affect-driven frameworks developed to date, we propose an approach based on affective design patterns. We build on the assumption that player’s emotional reactions to in-game events can be evoked by patterns used early in the design phase. We provide description of experiments conducted to test our hypothesis so far, along with some tentative observations, | ||
- | ==== HAI2018 | + | === HAI2018 === |
- | * **//"AIded with emotions – a new design approach towards affective computer systems"//** Barbara Giżycka, Grzegorz J. Nalepa and Paweł Jemioło | + | * B. Giżycka, G. J. Nalepa, and P. Jemioło, "**AIded with emotions – a new design approach towards affective computer systems**" |
* Presented at the [[https:// | * Presented at the [[https:// | ||
- | * Abstract: As technologies become more and more pervasive, there is a need for considering the affective dimension of interaction with computer systems to make them more human-like. Current demands for this matter include accurate emotion recognition, | + | * [[https:// |
+ | * ++Abstract | As technologies become more and more pervasive, there is a need for considering the affective dimension of interaction with computer systems to make them more human-like. Current demands for this matter include accurate emotion recognition, | ||
- | * [[https:// | + | === CCSC2018 === |
- | + | * B. Giżycka, "**Using Affective Loop as Auxilliary Design Tool for Video Games**" | |
- | ==== CCSC2018 | + | |
- | * //**"Using Affective Loop as Auxilliary Design Tool for Video Games"**// Barbara Giżycka | + | |
* Presented at the: 10th Cracow Cognitive Science Conference | * Presented at the: 10th Cracow Cognitive Science Conference | ||
- | * Abstract: As modern technologies become more apparent and persis-tent, human-computer interaction becomes an important research topic.With birth of affective computing, which aims at developing systems | + | * {{http:// |
- | + | * ++Abstract | As modern technologies become more apparent and persistent, human-computer interaction becomes an important research topic. With birth of affective computing, which aims at developing systems | |
- | * [[http:// | + | |
- | ==== HSI2018 | + | === HSI2018 === |
- | * **//"BandReader – A Mobile Application for Data Acquisition from Wearable Devices in Affective Computing Experiments"//**, Krzysztof Kutt, Grzegorz J. Nalepa, Barbara Giżycka, Paweł Jemioło, Marcin Adamczyk | + | * K. Kutt, G. J. Nalepa, B. Giżycka, P. Jemioło, and M. Adamczyk, "**BandReader – A Mobile Application for Data Acquisition from Wearable Devices in Affective Computing Experiments**, |
* Presented at [[http:// | * Presented at [[http:// | ||
- | * Abstract: In the paper we describe a new software solution for mobile devices that allows for data acquisition from wristbands. The application reads physiological data from wristbands and supports multiple recent hardware. In our work we focus on the Heart Rate (HR) and Galvanic Skin Response (GSR) readings. This data is used in the affective computing experiments for human emotion recognition. | ||
* DOI: 10.1109/ | * DOI: 10.1109/ | ||
- | |||
* {{ : | * {{ : | ||
+ | * ++Abstract | In the paper we describe a new software solution for mobile devices that allows for data acquisition from wristbands. The application reads physiological data from wristbands and supports multiple recent hardware. In our work we focus on the Heart Rate (HR) and Galvanic Skin Response (GSR) readings. This data is used in the affective computing experiments for human emotion recognition.++ | ||
- | ==== FGCS2018b | + | === FGCS2018b === |
- | * **//"Affective patterns in serious games"//**, Jan K. Argasiński, | + | * J. K. Argasiński and P. Węgrzyn, "**Affective patterns in serious games**" |
* Published in [[https:// | * Published in [[https:// | ||
- | * Abstract: We discuss affective serious games that combine learning, gaming and emotions. We describe a novel framework for the creation and evaluation of serious affective games. Our approach is based on merging pertinent design patterns in order to recognize educational claims, educational assessment, best game design practices, as well as models and solutions of affective computing. Björk’s and Holopainen’s game design patterns have been enhanced by Evidence Centered Design components and affective components. A serious game has been designed and created to demonstrate how to outline a complex game system in a communicative way, and show methods to trace how theoretically-driven design decisions influence learning outcomes and impacts. We emphasize the importance of patterns in game design. Design patterns are an advantageous and convenient way of outlining complex game systems. Design patterns also provide favorable language of communication between multidisciplinary teams working on serious games. | ||
* DOI: 10.1016/ | * DOI: 10.1016/ | ||
- | |||
* [[https:// | * [[https:// | ||
- | ==== ICAISC2018 | + | * ++Abstract | We discuss affective serious games that combine learning, gaming and emotions. We describe a novel framework for the creation and evaluation of serious affective games. Our approach is based on merging pertinent design patterns in order to recognize educational claims, educational assessment, best game design practices, as well as models and solutions of affective computing. Björk’s and Holopainen’s game design patterns have been enhanced by Evidence Centered Design components and affective components. A serious game has been designed and created to demonstrate how to outline a complex game system in a communicative way, and show methods to trace how theoretically-driven design decisions influence learning outcomes and impacts. We emphasize the importance of patterns in game design. Design patterns are an advantageous and convenient way of outlining complex game systems. Design patterns also provide favorable language of communication between multidisciplinary teams working on serious games.++ |
- | * **//"Towards the Development of Sensor Platform for Processing Physiological Data from Wearable Sensors"//**, Krzysztof Kutt, Wojciech Binek, Piotr Misiak, Grzegorz J. Nalepa, Szymon Bobek | + | |
+ | === ICAISC2018 === | ||
+ | * K. Kutt, W. Binek, P. Misiak, G. J. Nalepa, and S. Bobek, "**Towards the Development of Sensor Platform for Processing Physiological Data from Wearable Sensors**," in ICAISC 2018, vol. 10842 LNAI, Springer, 2018, pp. 168–178. | ||
* Presented at [[http:// | * Presented at [[http:// | ||
- | * Abstract: The paper outlines a mobile sensor platform aimed at processing physiological data from wearable sensors. We discuss the requirements related to the use of low-cost portable devices in this scenario. Experimental analysis of four such devices, namely Microsoft Band 2, Empatica E4, eHealth Sensor Platform and BITalino (r)evolution is provided. Critical comparison of quality of HR and GSR signals leads to the conclusion that future works should focus on the BITalino, possibly combined with the MS Band 2 in some cases. This work is a foundation for possible applications in affective computing and telemedicine. | ||
* {{ : | * {{ : | ||
+ | * ++Abstract | The paper outlines a mobile sensor platform aimed at processing physiological data from wearable sensors. We discuss the requirements related to the use of low-cost portable devices in this scenario. Experimental analysis of four such devices, namely Microsoft Band 2, Empatica E4, eHealth Sensor Platform and BITalino (r)evolution is provided. Critical comparison of quality of HR and GSR signals leads to the conclusion that future works should focus on the BITalino, possibly combined with the MS Band 2 in some cases. This work is a foundation for possible applications in affective computing and telemedicine.++ | ||
- | ==== AfCAI2018 | + | === AfCAI2018 === |
- | * **//"Development of Mobile Platform for Affect Interpretation. Current Progress"//**, Grzegorz J. Nalepa, Krzysztof Kutt, Szymon Bobek, Barbara Giżycka | + | * G. J. Nalepa, K. Kutt, S. Bobek, and B. Giżycka, "**Development of Mobile Platform for Affect Interpretation. Current Progress**," in Proceedings of the Workshop on Affective Computing and Context Awareness in Ambient Intelligence (AfCAI 2018), 2018. |
* Presented at [[https:// | * Presented at [[https:// | ||
- | * Abstract: In this overview paper we focus on our recent progress in the work on the mobile platform for AfC. We provide the main assumptions about the platform, as well as describe affective data acquisition and interpretation. We discuss our most recent experiments and provide an outlook of our future works. | + | * {{http:// |
- | * [[http:// | + | * ++Abstract | In this overview paper we focus on our recent progress in the work on the mobile platform for AfC. We provide the main assumptions about the platform, as well as describe affective data acquisition and interpretation. We discuss our most recent experiments and provide an outlook of our future works.++ |
- | ==== FGCS2018a | + | === FGCS2018a === |
- | * **//"Mobile platform for affective context-aware systems"//**, Grzegorz J. Nalepa, Krzysztof Kutt, Szymon Bobek, | + | * G. J. Nalepa, K. Kutt, and S. Bobek, "**Mobile platform for affective context-aware systems**," Futur. Gener. Comput. Syst., vol. 92, pp. 490–503, Mar. 2019. |
* Published in [[https:// | * Published in [[https:// | ||
- | * Abstract: In our work, we focus on detection of affective states, their proper identification and interpretation with use of wearable and mobile devices. We propose a data acquisition layer based on wearable devices able to gather physiological data, and we integrate it with mobile context-aware framework. Furthermore, | ||
* [[https:// | * [[https:// | ||
+ | * ++Abstract | In our work, we focus on detection of affective states, their proper identification and interpretation with use of wearable and mobile devices. We propose a data acquisition layer based on wearable devices able to gather physiological data, and we integrate it with mobile context-aware framework. Furthermore, | ||
- | ==== FedCSIS2017 | + | === FedCSIS2017 === |
- | * **//" | + | * G. J. Nalepa, |
* Presented at [[https:// | * Presented at [[https:// | ||
- | * Abstract: The emotional state of the user is a new dimension in human-computer interaction, | ||
* DOI: 10.15439/ | * DOI: 10.15439/ | ||
- | |||
* [[https:// | * [[https:// | ||
+ | * ++Abstract | The emotional state of the user is a new dimension in human-computer interaction, | ||
- | ==== AfCAI2016b | + | === AfCAI2016b === |
- | * | + | * |
* Presented at [[pub: | * Presented at [[pub: | ||
- | * [[http:// | + | * {{http:// |
+ | * ++Abstract | In this paper we discuss selected important challenges in designing experiments that lead to data and information collection on affective states of participants. We aim at acquiring data that would be basis to formulate and evaluate computer methods for detection, identification and interpretation of such affective states, and ultimately human emotions.++ | ||
- | ==== AfCAI2016a | + | === AfCAI2016a === |
- | * **//"AfCAI systems: Affective Computing with Context Awareness for Ambient Intelligence. Research proposal"//**, Grzegorz J. Nalepa, Krzysztof Kutt, Szymon Bobek, Mateusz Z. Łępicki | + | * G. J. Nalepa, K. Kutt, S. Bobek, and M. Z. Łępicki, "**AfCAI systems: Affective Computing with Context Awareness for Ambient Intelligence. Research proposal**," in Proceedings of the Workshop on Affective Computing and Context Awareness in Ambient Intelligence (AfCAI 2016), 2016, vol. 1794. |
* Presented at [[pub: | * Presented at [[pub: | ||
- | * [[http:// | + | * {{http:// |
+ | * ++Abstract | We are aiming at developing a technology to detect, identify and interpret human emotional states. We believe, that it can be provided based on the integration of context-aware systems and affective computing paradigms. We are planning to identify and characterize affective context data, and provide knowledge-based models to identify and interpret affects based on this data. A working name for this technology is simply AfCAI: Affective Computing with Context Awareness for Ambient Intelligence.++ | ||
+ | |||
===== Tools and Datasets ===== | ===== Tools and Datasets ===== | ||
==== Bandreader ==== | ==== Bandreader ==== | ||
Line 114: | Line 152: | ||
==== Prototypes of Affective Games ==== | ==== Prototypes of Affective Games ==== | ||
+ | * [[pub: | ||
* [[pub: | * [[pub: | ||
* [[pub: | * [[pub: | ||
- | * [[pub:londonbridge|London Bridge]] (scrollrunner game) | + | * [[pub:prototypes# |
==== Datasets ==== | ==== Datasets ==== |