{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T13:26:24Z","timestamp":1769520384308,"version":"3.49.0"},"reference-count":50,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2019,2,26]],"date-time":"2019-02-26T00:00:00Z","timestamp":1551139200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005357","name":"Agent\u00fara na Podporu V\u00fdskumu a V\u00fdvoja","doi-asserted-by":"publisher","award":["APVV-16-0213"],"award-info":[{"award-number":["APVV-16-0213"]}],"id":[{"id":"10.13039\/501100005357","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005357","name":"Agent\u00fara na Podporu V\u00fdskumu a V\u00fdvoja","doi-asserted-by":"publisher","award":["APVV-15-0731"],"award-info":[{"award-number":["APVV-15-0731"]}],"id":[{"id":"10.13039\/501100005357","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Analyses of user experience in the electronic entertainment industry currently rely on self-reporting methods, such as surveys, ratings, focus group interviews, etc. We argue that self-reporting alone carries inherent problems\u2014mainly the misinterpretation and temporal delay during longer experiments\u2014and therefore, should not be used as a sole metric. To tackle this problem, we propose the possibility of modeling consumer experience using psychophysiological measures and demonstrate how such models can be trained using machine learning methods. We use a machine learning approach to model user experience using real-time data produced by the autonomic nervous system and involuntary psychophysiological responses. Multiple psychophysiological measures, such as heart rate, electrodermal activity, and respiratory activity, have been used in combination with self-reporting to prepare training sets for machine learning algorithms. The training data was collected from 31 participants during hour-long experiment sessions, where they played multiple video-games. Afterwards, we trained and compared the results of four different machine learning models, out of which the best one produced \u223c96% accuracy. The results suggest that psychophysiological measures can indeed be used to assess the enjoyment of digital entertainment consumers.<\/jats:p>","DOI":"10.3390\/s19050989","type":"journal-article","created":{"date-parts":[[2019,2,26]],"date-time":"2019-02-26T11:00:44Z","timestamp":1551178844000},"page":"989","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Psychophysiological Indicators for Modeling User Experience in Interactive Digital Entertainment"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1284-1352","authenticated-orcid":false,"given":"Martin","family":"\u010certick\u00fd","sequence":"first","affiliation":[{"name":"Department of Cybernetics and Artificial Intelligence, Technical University in Ko\u0161ice, Letn\u00e1 9, 040 01 Ko\u0161ice, Slovakia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2424-7556","authenticated-orcid":false,"given":"Michal","family":"\u010certick\u00fd","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Czech Technical University in Prague, 166 36 Prague, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter","family":"Sin\u010d\u00e1k","sequence":"additional","affiliation":[{"name":"Department of Cybernetics and Artificial Intelligence, Technical University in Ko\u0161ice, Letn\u00e1 9, 040 01 Ko\u0161ice, Slovakia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gergely","family":"Magyar","sequence":"additional","affiliation":[{"name":"Department of Cybernetics and Artificial Intelligence, Technical University in Ko\u0161ice, Letn\u00e1 9, 040 01 Ko\u0161ice, Slovakia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0585-4115","authenticated-orcid":false,"given":"J\u00e1n","family":"Va\u0161\u010d\u00e1k","sequence":"additional","affiliation":[{"name":"Department of Cybernetics and Artificial Intelligence, Technical University in Ko\u0161ice, Letn\u00e1 9, 040 01 Ko\u0161ice, Slovakia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7432-5033","authenticated-orcid":false,"given":"Filippo","family":"Cavallo","sequence":"additional","affiliation":[{"name":"The Biorobotics Institute, Scuola Superiore Sant\u2019Anna, 560 25 Pisa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,2,26]]},"reference":[{"key":"ref_1","unstructured":"(2019, February 25). 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