{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T03:47:59Z","timestamp":1743133679696,"version":"3.40.3"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031611391"},{"type":"electronic","value":"9783031611407"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-61140-7_44","type":"book-chapter","created":{"date-parts":[[2024,5,30]],"date-time":"2024-05-30T07:10:33Z","timestamp":1717053033000},"page":"465-475","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Emotion Prediction in\u00a0Real-Life Scenarios: On the\u00a0Way to\u00a0the\u00a0BIRAFFE3 Dataset"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5453-9763","authenticated-orcid":false,"given":"Krzysztof","family":"Kutt","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8182-4225","authenticated-orcid":false,"given":"Grzegorz J.","family":"Nalepa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,5,31]]},"reference":[{"issue":"1","key":"44_CR1","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1186\/s40708-023-00196-6","volume":"10","author":"P Bhatt","year":"2023","unstructured":"Bhatt, P., et al.: Machine learning for cognitive behavioral analysis: datasets, methods, paradigms, and research directions. Brain Inform. 10(1), 18 (2023). https:\/\/doi.org\/10.1186\/s40708-023-00196-6","journal-title":"Brain Inform."},{"key":"44_CR2","unstructured":"Bradley, M.M., Lang, P.J.: The international affective digitized sounds (2nd edition; iads-2): affective ratings of sounds and instruction manual. technical report B-3. Technical report, University of Florida, Gainsville, FL (2007)"},{"key":"44_CR3","unstructured":"Costa, P., McCrae, R.: Revised NEO Personality Inventory (NEO-PI-R) and NEO Five Factor Inventory (NEO-FFI). Professional manual. Psychological Assessment Resources, Odessa, FL (1992)"},{"issue":"2","key":"44_CR4","doi-asserted-by":"publisher","first-page":"468","DOI":"10.3758\/s13428-011-0064-1","volume":"43","author":"ES Dan-Glauser","year":"2011","unstructured":"Dan-Glauser, E.S., Scherer, K.R.: The geneva affective picture database (GAPED): a new 730-picture database focusing on valence and normative significance. Behav. Res. Methods 43(2), 468\u2013477 (2011). https:\/\/doi.org\/10.3758\/s13428-011-0064-1","journal-title":"Behav. Res. Methods"},{"issue":"2","key":"44_CR5","doi-asserted-by":"publisher","first-page":"298","DOI":"10.1016\/j.physbeh.2012.01.020","volume":"106","author":"M van Dooren","year":"2012","unstructured":"van Dooren, M., de Vries, J.J.G., Janssen, J.H.: Emotional sweating across the body: comparing 16 different skin conductance measurement locations. Physiol. Behav. 106(2), 298\u2013304 (2012)","journal-title":"Physiol. Behav."},{"issue":"3","key":"44_CR6","doi-asserted-by":"publisher","first-page":"592","DOI":"10.3390\/s20030592","volume":"20","author":"A Dzedzickis","year":"2020","unstructured":"Dzedzickis, A., Kaklauskas, A., Bucinskas, V.: Human emotion recognition: review of sensors and methods. Sensors 20(3), 592 (2020). https:\/\/doi.org\/10.3390\/s20030592","journal-title":"Sensors"},{"key":"44_CR7","doi-asserted-by":"publisher","unstructured":"Fanourakis, M., Chanel, G.: AMuCS: affective multimodal counter-strike video game dataset (2024). https:\/\/doi.org\/10.36227\/techrxiv.170630398.84528625\/v1","DOI":"10.36227\/techrxiv.170630398.84528625\/v1"},{"issue":"15","key":"44_CR8","doi-asserted-by":"publisher","first-page":"5015","DOI":"10.3390\/s21155015","volume":"21","author":"MA Hasnul","year":"2021","unstructured":"Hasnul, M.A., Aziz, N.A.B.A., Alelyani, S., Mohana, M., Aziz, A.A.: Electrocardiogram-based emotion recognition systems and their applications in healthcare - a review. Sensors 21(15), 5015 (2021). https:\/\/doi.org\/10.3390\/s21155015","journal-title":"Sensors"},{"key":"44_CR9","unstructured":"IJsselsteijn, W.A., de Kort, Y.A.W., Poels, K.: The Game Experience Questionnaire. Technische Universiteit Eindhoven (2013)"},{"issue":"3","key":"44_CR10","doi-asserted-by":"publisher","first-page":"502","DOI":"10.1109\/TSMCA.2008.918624","volume":"38","author":"CD Katsis","year":"2008","unstructured":"Katsis, C.D., Katertsidis, N.S., Ganiatsas, G., Fotiadis, D.I.: Toward emotion recognition in car-racing drivers: a biosignal processing approach. IEEE Trans. Syst. Man Cybern. Part A 38(3), 502\u2013512 (2008). https:\/\/doi.org\/10.1109\/TSMCA.2008.918624","journal-title":"IEEE Trans. Syst. Man Cybern. Part A"},{"key":"44_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/J.INFFUS.2023.102019","volume":"102","author":"SK Khare","year":"2024","unstructured":"Khare, S.K., Blanes-Vidal, V., Nadimi, E.S., Acharya, U.R.: Emotion recognition and artificial intelligence: a systematic review (2014\u20132023) and research recommendations. Inf. Fusion 102, 102019 (2024). https:\/\/doi.org\/10.1016\/J.INFFUS.2023.102019","journal-title":"Inf. Fusion"},{"key":"44_CR12","unstructured":"Kutt, K., Bobek, S., Nalepa, G.J.: BIRAFFE: bio-reactions and faces for emotion-based personalization. Zenodohttps:\/\/doi.org\/10.5281\/zenodo.3442143 (2020)"},{"issue":"1","key":"44_CR13","doi-asserted-by":"publisher","first-page":"163","DOI":"10.3390\/s21010163","volume":"21","author":"K Kutt","year":"2021","unstructured":"Kutt, K., Dr\u0105\u017cyk, D., Bobek, S., Nalepa, G.J.: Personality-based affective adaptation methods for intelligent systems. Sensors 21(1), 163 (2021). https:\/\/doi.org\/10.3390\/s21010163","journal-title":"Sensors"},{"key":"44_CR14","unstructured":"Kutt, K., et al.: BIRAFFE: bio-reactions and faces for emotion-based personalization. In: AfCAI 2019. CEUR Workshop Proceedings, vol.\u00a02609. CEUR-WS.org (2020)"},{"key":"44_CR15","doi-asserted-by":"publisher","first-page":"274","DOI":"10.1038\/s41597-022-01402-6","volume":"9","author":"K Kutt","year":"2022","unstructured":"Kutt, K., Dr\u0105\u017cyk, D., \u017buchowska, L., Szel\u0105\u017cek, M., Bobek, S., Nalepa, G.J.: BIRAFFE2, a multimodal dataset for emotion-based personalization in rich affective game environments. Sci. Data 9, 274 (2022). https:\/\/doi.org\/10.1038\/s41597-022-01402-6","journal-title":"Sci. Data"},{"key":"44_CR16","doi-asserted-by":"publisher","unstructured":"Kutt, K., \u015aciga, \u0141., Nalepa, G.J.: Emotion-based dynamic difficulty adjustment in video games. In: DSAA 2023, pp.\u00a01\u20135. IEEE (2023). https:\/\/doi.org\/10.1109\/DSAA60987.2023.10302578","DOI":"10.1109\/DSAA60987.2023.10302578"},{"key":"44_CR17","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1007\/978-3-031-06527-9_7","volume-title":"IWINAC 2022 Proceedings, Part II","author":"K Kutt","year":"2022","unstructured":"Kutt, K., Sobczyk, P., Nalepa, G.J.: Evaluation of selected APIs for emotion recognition from facial expressions. In: Ferr\u00e1ndez Vicente, J.M., \u00c1lvarez-S\u00e1nchez, J.R., de la Paz L\u00f3pez, F., Adeli, H. (eds.) IWINAC 2022. LNCS, vol. 13259, pp. 65\u201374. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-06527-9_7"},{"key":"44_CR18","unstructured":"Lang, P.J., Bradley, M.M., Cuthbert, B.N.: International affective picture system (IAPs): affective ratings of pictures and instruction manual. technical report B-3. Technical report, The Center for Research in Psychophysiology, University of Florida, Gainsville, FL (2008)"},{"key":"44_CR19","doi-asserted-by":"publisher","first-page":"516","DOI":"10.1016\/j.future.2017.12.056","volume":"92","author":"R Lara-Cabrera","year":"2019","unstructured":"Lara-Cabrera, R., Camacho, D.: A taxonomy and state of the art revision on affective games. Futur. Gener. Comput. Syst. 92, 516\u2013525 (2019)","journal-title":"Futur. Gener. Comput. Syst."},{"issue":"4","key":"44_CR20","doi-asserted-by":"publisher","first-page":"1407","DOI":"10.3758\/s13428-016-0797-y","volume":"49","author":"JM Micha\u0142owski","year":"2017","unstructured":"Micha\u0142owski, J.M., Dro\u017adziel, D., Matuszewski, J., Koziejowski, W., Jednor\u00f3g, K., Marchewka, A.: The set of fear inducing pictures (SFIP): development and validation in fearful and nonfearful individuals. Behav. Res. Methods 49(4), 1407\u20131419 (2017). https:\/\/doi.org\/10.3758\/s13428-016-0797-y","journal-title":"Behav. Res. Methods"},{"key":"44_CR21","doi-asserted-by":"publisher","unstructured":"Milkowski, P., Saganowski, S., Gruza, M., Kazienko, P., Piasecki, M., Kocon, J.: Multitask personalized recognition of emotions evoked by textual content. In: PerCom 2022 Workshops, pp. 347\u2013352. IEEE (2022). https:\/\/doi.org\/10.1109\/PerComWorkshops53856.2022.9767502","DOI":"10.1109\/PerComWorkshops53856.2022.9767502"},{"issue":"11","key":"44_CR22","doi-asserted-by":"publisher","first-page":"2509","DOI":"10.3390\/s19112509","volume":"19","author":"GJ Nalepa","year":"2019","unstructured":"Nalepa, G.J., Kutt, K., Gi\u017cycka, B., Jemio\u0142o, P., Bobek, S.: Analysis and use of the emotional context with wearable devices for games and intelligent assistants. Sensors 19(11), 2509 (2019). https:\/\/doi.org\/10.3390\/s19112509","journal-title":"Sensors"},{"issue":"1","key":"44_CR23","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1038\/s41597-020-00630-y","volume":"7","author":"CY Park","year":"2020","unstructured":"Park, C.Y., et al.: K-EmoCon, a multimodal sensor dataset for continuous emotion recognition in naturalistic conversations. Sci. Data 7(1), 293 (2020). https:\/\/doi.org\/10.1038\/s41597-020-00630-y","journal-title":"Sci. Data"},{"issue":"1","key":"44_CR24","doi-asserted-by":"publisher","first-page":"195","DOI":"10.3758\/s13428-018-01193-y","volume":"51","author":"J Peirce","year":"2019","unstructured":"Peirce, J., et al.: Psychopy2: experiments in behavior made easy. Behav. Res. Methods 51(1), 195\u2013203 (2019). https:\/\/doi.org\/10.3758\/s13428-018-01193-y","journal-title":"Behav. Res. Methods"},{"key":"44_CR25","doi-asserted-by":"publisher","unstructured":"Phan, L.V., Rauthmann, J.F.: Personality computing: New frontiers in personality assessment. Soc. Pers. Psychol. Compass 15(7) (2021). https:\/\/doi.org\/10.1111\/spc3.12624","DOI":"10.1111\/spc3.12624"},{"issue":"10","key":"44_CR26","doi-asserted-by":"publisher","first-page":"2750","DOI":"10.3390\/s20102750","volume":"20","author":"M Prokop","year":"2020","unstructured":"Prokop, M., Pilar, L., Tich\u00e1, I.: Impact of think-aloud on eye-tracking: a comparison of concurrent and retrospective think-aloud for research on decision-making in the game environment. Sensors 20(10), 2750 (2020). https:\/\/doi.org\/10.3390\/s20102750","journal-title":"Sensors"},{"issue":"1","key":"44_CR27","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TAFFC.2022.3176135","volume":"12","author":"S Saganowski","year":"2021","unstructured":"Saganowski, S., Perz, B., Polak, A.G., Kazienko, P.: Emotion recognition for everyday life using physiological signals from wearables: a systematic literature review. IEEE Trans. Affect. Comput. 12(1), 1\u201321 (2021). https:\/\/doi.org\/10.1109\/TAFFC.2022.3176135","journal-title":"IEEE Trans. Affect. Comput."},{"key":"44_CR28","unstructured":"Zawadzki, B., Strelau, J., Szczepaniak, P., \u015aliwi\u0144ska, M.: Inwentarz osobowo\u015bci NEO-FFI Costy i McCrae. Adaptacja polska. Pracownia Test\u00f3w Psychologicznych, Warszawa (1998)"},{"key":"44_CR29","doi-asserted-by":"publisher","unstructured":"Zhao, S., Gholaminejad, A., Ding, G., Gao, Y., Han, J., Keutzer, K.: Personalized emotion recognition by personality-aware high-order learning of physiological signals. ACM Trans. Multim. Comput. Commun. Appl. 15(1s), 14:1\u201314:18 (2019). https:\/\/doi.org\/10.1145\/3233184","DOI":"10.1145\/3233184"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence for Neuroscience and Emotional Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-61140-7_44","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,30]],"date-time":"2024-05-30T07:35:38Z","timestamp":1717054538000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-61140-7_44"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031611391","9783031611407"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-61140-7_44","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"31 May 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"IWINAC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Work-Conference on the Interplay Between Natural and Artificial Computation","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Olh\u00e2o","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 May 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iwinac2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/iwinac.eu\/iwinac.org\/iwinac2024\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}