{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T19:21:42Z","timestamp":1751743302934,"version":"3.40.3"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031610400"},{"type":"electronic","value":"9783031610417"}],"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\/978-3-031-61041-7_12","type":"book-chapter","created":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T01:06:47Z","timestamp":1717204007000},"page":"182-199","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Scientific Knowledge Database to\u00a0Support Cybersickness Detection and\u00a0Prevention"],"prefix":"10.1007","author":[{"given":"Milton","family":"Fran\u00e7a","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6400-6258","authenticated-orcid":false,"given":"\u00c2ngelo","family":"Amaral","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9504-496X","authenticated-orcid":false,"given":"Ferrucio de Franco","family":"Rosa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3441-0887","authenticated-orcid":false,"given":"Rodrigo","family":"Bonacin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,6,1]]},"reference":[{"key":"12_CR1","doi-asserted-by":"publisher","unstructured":"Altaheri, H., et al.: Deep learning techniques for classification of electroencephalogram (eeg) motor imagery (mi) signals: a review. Neural Comput. Appl. (2021). https:\/\/doi.org\/10.1007\/s00521-021-06352-5","DOI":"10.1007\/s00521-021-06352-5"},{"key":"12_CR2","doi-asserted-by":"publisher","unstructured":"Batras, D., Guez, J., J\u00e9go, J.F., Tramus, M.H.: A virtual reality agent-based platform for improvisation between real and virtual actors using gestures. Association for Computing Machinery (2016). https:\/\/doi.org\/10.1145\/2927929.2927947","DOI":"10.1145\/2927929.2927947"},{"issue":"11","key":"12_CR3","doi-asserted-by":"publisher","first-page":"1867","DOI":"10.1109\/TLA.2021.9475620","volume":"19","author":"P Bello L\u00f3pez","year":"2021","unstructured":"Bello L\u00f3pez, P., De Ita Luna, G.: An algorithm to belief revision and to verify consistency of a knowledge base. IEEE Lat. Am. Trans. 19(11), 1867\u20131874 (2021). https:\/\/doi.org\/10.1109\/TLA.2021.9475620","journal-title":"IEEE Lat. Am. Trans."},{"key":"12_CR4","doi-asserted-by":"publisher","unstructured":"Boeldt, D., McMahon, E., McFaul, M., Greenleaf, W.: Using virtual reality exposure therapy to enhance treatment of anxiety disorders: identifying areas of clinical adoption and potential obstacles. Front. Psychiatry 10 (2019). https:\/\/doi.org\/10.3389\/fpsyt.2019.00773. https:\/\/www.frontiersin.org\/articles\/10.3389\/fpsyt.2019.00773","DOI":"10.3389\/fpsyt.2019.00773"},{"key":"12_CR5","doi-asserted-by":"publisher","unstructured":"Borck, H., Boddy, M.: Automated case generation using a genetic algorithm, pp. 187\u2013188. Association for Computing Machinery (2017). https:\/\/doi.org\/10.1145\/3067695.3075603","DOI":"10.1145\/3067695.3075603"},{"key":"12_CR6","doi-asserted-by":"publisher","unstructured":"Davis, S., Nesbitt, K., Nalivaiko, E.: A systematic review of cybersickness, pp.\u00a01\u20139. Association for Computing Machinery (2014). https:\/\/doi.org\/10.1145\/2677758.2677780","DOI":"10.1145\/2677758.2677780"},{"key":"12_CR7","doi-asserted-by":"publisher","unstructured":"Dwivedi, P., Cline, D., Joe, C., Etemadpour, R.: Manual assembly training in virtual environments, pp. 395\u2013399 (2018). https:\/\/doi.org\/10.1109\/ICALT.2018.00100","DOI":"10.1109\/ICALT.2018.00100"},{"key":"12_CR8","doi-asserted-by":"publisher","unstructured":"Fatahi, S., Moradi, H., Kashani-Vahid, L.: A survey of personality and learning styles models applied in virtual environments with emphasis on e-learning environments. Artif. Intell. Rev. 46, 413\u2013429 (2016). https:\/\/doi.org\/10.1007\/s10462-016-9469-7","DOI":"10.1007\/s10462-016-9469-7"},{"key":"12_CR9","unstructured":"Fran\u00e7a, M., Rosa, F., Amaral, A.: Cskd repository (2024). https:\/\/github.com\/FrancaFilho\/cybersickness. Accessed 20 Jan 2024"},{"key":"12_CR10","doi-asserted-by":"publisher","unstructured":"Guarnera, G.C., Ghosh, A., Hall, I., Glencross, M., Guarnera, D.: Material capture and representation with applications in virtual reality. Association for Computing Machinery (2017). https:\/\/doi.org\/10.1145\/3084873.3084918","DOI":"10.1145\/3084873.3084918"},{"key":"12_CR11","doi-asserted-by":"publisher","unstructured":"Henshall, G.I., Teahan, W.J., Cenydd, L.A.: Crowd-sourced procedural animation optimisation: comparing desktop and vr behaviour, pp. 48\u201355 (2017). https:\/\/doi.org\/10.1109\/CW.2017.52","DOI":"10.1109\/CW.2017.52"},{"key":"12_CR12","doi-asserted-by":"publisher","unstructured":"Izard, S.G., M\u00e9ndez, J.A.J., Palomera, P.R., Garc\u00eda-Pe\u00f1alvo, F.J.: Applications of virtual and augmented reality in biomedical imaging. J. Med. Syst. 43, 102 (2019). https:\/\/doi.org\/10.1007\/s10916-019-1239-z","DOI":"10.1007\/s10916-019-1239-z"},{"key":"12_CR13","doi-asserted-by":"publisher","unstructured":"Kim, H., et al.: Effect of virtual reality on stress reduction and change of physiological parameters including heart rate variability in people with high stress: an open randomized crossover trial. Front. Psychiatry 12 (2021). https:\/\/doi.org\/10.3389\/fpsyt.2021.614539, https:\/\/www.frontiersin.org\/articles\/10.3389\/fpsyt.2021.614539","DOI":"10.3389\/fpsyt.2021.614539"},{"key":"12_CR14","doi-asserted-by":"publisher","unstructured":"Kitchenham, B.A.: Systematic reviews, pp. xii\u2013xii (2004). https:\/\/doi.org\/10.1109\/METRIC.2004.1357885","DOI":"10.1109\/METRIC.2004.1357885"},{"key":"12_CR15","doi-asserted-by":"publisher","unstructured":"K\u00e1n, P., Kaufmann, H.: Automated interior design using a genetic algorithm. Association for Computing Machinery (2017). https:\/\/doi.org\/10.1145\/3139131.3139135","DOI":"10.1145\/3139131.3139135"},{"key":"12_CR16","doi-asserted-by":"publisher","unstructured":"Ramos, M.A., Mu\u00f1oz-Jim\u00e9nez, V., Ramos, F.F., Romero, J.R.M., L\u00f3pez, A., G, B.E.O.: Evolutive autonomous behaviors for agents system in serious games, pp. 226\u2013231 (2015). https:\/\/doi.org\/10.1109\/CSCI.2015.175","DOI":"10.1109\/CSCI.2015.175"},{"key":"12_CR17","doi-asserted-by":"publisher","unstructured":"Rautaray, S.S., Agrawal, A.: Vision based hand gesture recognition for human computer interaction: a survey. Artif. Intell. Rev. 43, 1\u201354 (2015). https:\/\/doi.org\/10.1007\/s10462-012-9356-9","DOI":"10.1007\/s10462-012-9356-9"},{"key":"12_CR18","doi-asserted-by":"publisher","unstructured":"Rechy-Ramirez, E.J., Marin-Hernandez, A., Rios-Figueroa, H.V.: Impact of commercial sensors in human computer interaction: a review. J. Ambient. Intell. Humaniz. Comput. 9, 1479\u20131496 (2018). https:\/\/doi.org\/10.1007\/s12652-017-0568-3","DOI":"10.1007\/s12652-017-0568-3"},{"key":"12_CR19","doi-asserted-by":"publisher","unstructured":"kumar Renganayagalu, S., Mallam, S.C., Nazir, S.: Effectiveness of vr head mounted displays in professional training: a systematic review. Technol. Knowl. Learn. 26, 999\u20131041 (2021). https:\/\/doi.org\/10.1007\/s10758-020-09489-9","DOI":"10.1007\/s10758-020-09489-9"},{"issue":"1","key":"12_CR20","doi-asserted-by":"publisher","first-page":"682","DOI":"10.1109\/TVCG.2018.2864903","volume":"25","author":"A Sarikaya","year":"2019","unstructured":"Sarikaya, A., Correll, M., Bartram, L., Tory, M., Fisher, D.: What do we talk about when we talk about dashboards? IEEE Trans. Visual Comput. Graphics 25(1), 682\u2013692 (2019). https:\/\/doi.org\/10.1109\/TVCG.2018.2864903","journal-title":"IEEE Trans. Visual Comput. Graphics"},{"key":"12_CR21","doi-asserted-by":"publisher","unstructured":"Sarker, I.H.: Ai-based modeling: techniques, applications and research issues towards automation, intelligent and smart systems. SN Comput. Sci. 3, 158 (2022). https:\/\/doi.org\/10.1007\/s42979-022-01043-x","DOI":"10.1007\/s42979-022-01043-x"},{"key":"12_CR22","doi-asserted-by":"publisher","unstructured":"Sra, M., Garrido-Jurado, S., Schmandt, C., Maes, P.: Procedurally generated virtual reality from 3d reconstructed physical space, pp. 191\u2013200. Association for Computing Machinery (2016). https:\/\/doi.org\/10.1145\/2993369.2993372","DOI":"10.1145\/2993369.2993372"},{"key":"12_CR23","doi-asserted-by":"publisher","unstructured":"Steshina, L., Petukhov, I., Glazyrin, A., Zlateva, P., Velev, D.: An intelligent virtual environment for training with dynamic parameters, pp. 79\u201384. Association for Computing Machinery (2021). https:\/\/doi.org\/10.1145\/3442705.3442718","DOI":"10.1145\/3442705.3442718"},{"key":"12_CR24","doi-asserted-by":"publisher","first-page":"161329","DOI":"10.1109\/ACCESS.2019.2949993","volume":"7","author":"L Su","year":"2019","unstructured":"Su, L., He, T., Fan, Z., Zhang, Y., Guizani, M.: Answer acquisition for knowledge base question answering systems based on dynamic memory network. IEEE Access 7, 161329\u2013161339 (2019). https:\/\/doi.org\/10.1109\/ACCESS.2019.2949993","journal-title":"IEEE Access"},{"key":"12_CR25","doi-asserted-by":"publisher","unstructured":"Sun, X., Xu, C., Li, B., Duan, Y., Lu, X.: Enabling feature location for api method recommendation and usage location. IEEE Access 7, 49872\u201349881 (2019). https:\/\/doi.org\/10.1109\/ACCESS.2019.2910732","DOI":"10.1109\/ACCESS.2019.2910732"},{"key":"12_CR26","doi-asserted-by":"publisher","unstructured":"Takacs, A., et al.: Descriptor generation and optimization for a specific outdoor environment. IEEE Access 8, 52550\u201352565 (2020). https:\/\/doi.org\/10.1109\/ACCESS.2020.2975474","DOI":"10.1109\/ACCESS.2020.2975474"},{"issue":"4","key":"12_CR27","doi-asserted-by":"publisher","first-page":"332","DOI":"10.1147\/sj.124.0332","volume":"12","author":"PP Uhrowczik","year":"1973","unstructured":"Uhrowczik, P.P.: Data dictionary\/directories. IBM Syst. J. 12(4), 332\u2013350 (1973). https:\/\/doi.org\/10.1147\/sj.124.0332","journal-title":"IBM Syst. J."},{"issue":"6","key":"12_CR28","doi-asserted-by":"publisher","first-page":"4127","DOI":"10.1109\/TDSC.2021.3121216","volume":"19","author":"S Valluripally","year":"2022","unstructured":"Valluripally, S., Gulhane, A., Hoque, K.A., Calyam, P.: Modeling and defense of social virtual reality attacks inducing cybersickness. IEEE Trans. Dependable Secure Comput. 19(6), 4127\u20134144 (2022). https:\/\/doi.org\/10.1109\/TDSC.2021.3121216","journal-title":"IEEE Trans. Dependable Secure Comput."},{"key":"12_CR29","doi-asserted-by":"publisher","unstructured":"Wang, X., Wang, J., Wu, C., Xu, S., Ma, W.: Engineering brain: metaverse for future engineering. AI Civil Eng. 1, 2 (2022). https:\/\/doi.org\/10.1007\/s43503-022-00001-z","DOI":"10.1007\/s43503-022-00001-z"},{"key":"12_CR30","doi-asserted-by":"publisher","unstructured":"Yang, A.H.X., Kasabov, N., Cakmak, Y.O.: Machine learning methods for the study of cybersickness: a systematic review. Brain Inform. 9, 24 (2022). https:\/\/doi.org\/10.1186\/s40708-022-00172-6","DOI":"10.1186\/s40708-022-00172-6"},{"key":"12_CR31","doi-asserted-by":"publisher","unstructured":"Zahabi, M., Razak, A.M.A.: Adaptive virtual reality-based training: a systematic literature review and framework. Virtual Reality 24, 725\u2013752 (2020). https:\/\/doi.org\/10.1007\/s10055-020-00434-w","DOI":"10.1007\/s10055-020-00434-w"},{"key":"12_CR32","doi-asserted-by":"publisher","unstructured":"Zhang, Y., Fei, G., Shang, W.: 3d architecture facade optimization based on genetic algorithm and neural network, pp. 693\u2013698 (2017). https:\/\/doi.org\/10.1109\/ICIS.2017.7960082","DOI":"10.1109\/ICIS.2017.7960082"},{"key":"12_CR33","doi-asserted-by":"publisher","first-page":"110426","DOI":"10.1109\/ACCESS.2022.3214206","volume":"10","author":"Y Zhang","year":"2022","unstructured":"Zhang, Y., Yang, G.: Optimization of the virtual scene layout based on the optimal 3d viewpoint. IEEE Access 10, 110426\u2013110443 (2022). https:\/\/doi.org\/10.1109\/ACCESS.2022.3214206","journal-title":"IEEE Access"}],"container-title":["Lecture Notes in Computer Science","Virtual, Augmented and Mixed Reality"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-61041-7_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T02:05:49Z","timestamp":1717207549000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-61041-7_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031610400","9783031610417"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-61041-7_12","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":"1 June 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"HCII","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Human-Computer Interaction","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Washington DC","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","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":"29 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 July 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"hcii2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2024.hci.international\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}