{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:19:12Z","timestamp":1767323952830,"version":"3.48.0"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032133113","type":"print"},{"value":"9783032133120","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-13312-0_14","type":"book-chapter","created":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:14:36Z","timestamp":1767323676000},"page":"234-249","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Synthetic Data Generation Using a\u00a0Smart Floor Digital Twin for\u00a0Fall Detection"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-1677-0398","authenticated-orcid":false,"given":"Milan","family":"Milivoj\u010devi\u0107","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1082-0697","authenticated-orcid":false,"given":"Niki","family":"Hrovatin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7876-5009","authenticated-orcid":false,"given":"Jernej","family":"Vi\u010di\u010d","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5627-4420","authenticated-orcid":false,"given":"Aleksandar","family":"To\u0161i\u0107","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,1,2]]},"reference":[{"key":"14_CR1","doi-asserted-by":"crossref","unstructured":"Anderson, D., Keller, J.M., Skubic, M., Chen, X., He, Z.: Recognizing falls from silhouettes. In: 2006 International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 6388\u20136391. IEEE (2006)","DOI":"10.1109\/IEMBS.2006.259594"},{"key":"14_CR2","unstructured":"Borkman, S., et\u00a0al.: Unity perception: generate synthetic data for computer vision. arXiv preprint: arXiv:2107.04259 (2021)"},{"key":"14_CR3","doi-asserted-by":"crossref","unstructured":"Cauli, N., Recupero, D.R.: Synthetic data augmentation for video action classification using unity. IEEE Access (2024)","DOI":"10.1109\/ACCESS.2024.3485199"},{"key":"14_CR4","doi-asserted-by":"crossref","unstructured":"Chen, J., Kwong, K., Chang, D., Luk, J., Bajcsy, R.: Wearable sensors for reliable fall detection. In: 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, pp. 3551\u20133554. IEEE (2006)","DOI":"10.1109\/IEMBS.2005.1617246"},{"key":"14_CR5","doi-asserted-by":"crossref","unstructured":"Chen, Y.J., et\u00a0al.: Pressure-sensor-based gait analysis for disabled people. Sensors Mater. 34 (2022)","DOI":"10.18494\/SAM3559"},{"key":"14_CR6","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/j.pmcj.2016.01.007","volume":"30","author":"J Cheng","year":"2016","unstructured":"Cheng, J., Sundholm, M., Zhou, B., Hirsch, M., Lukowicz, P.: Smart-surface: large scale textile pressure sensors arrays for activity recognition. Pervasive Mob. Comput. 30, 97\u2013112 (2016)","journal-title":"Pervasive Mob. Comput."},{"issue":"6","key":"14_CR7","doi-asserted-by":"publisher","first-page":"3162","DOI":"10.3390\/s23063162","volume":"23","author":"F Cocconcelli","year":"2023","unstructured":"Cocconcelli, F., Matrella, G., Mora, N., Casu, I., Vargas Godoy, D.A., Ciampolini, P.: IoT smart flooring supporting active and healthy lifestyles. Sensors 23(6), 3162 (2023)","journal-title":"Sensors"},{"issue":"10","key":"14_CR8","doi-asserted-by":"publisher","first-page":"19806","DOI":"10.3390\/s141019806","volume":"14","author":"YS Delahoz","year":"2014","unstructured":"Delahoz, Y.S., Labrador, M.A.: Survey on fall detection and fall prevention using wearable and external sensors. Sensors 14(10), 19806\u201319842 (2014)","journal-title":"Sensors"},{"issue":"2","key":"14_CR9","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1080\/14639230410001684387","volume":"29","author":"G Demiris","year":"2004","unstructured":"Demiris, G., et al.: Older adults\u2019 attitudes towards and perceptions of \u2018smart home\u2019 technologies: a pilot study. Med. Inform. Internet Med. 29(2), 87\u201394 (2004)","journal-title":"Med. Inform. Internet Med."},{"key":"14_CR10","doi-asserted-by":"crossref","unstructured":"Grieves, M., Vickers, J.: Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems. In: Transdisciplinary Perspectives on Complex Systems: New Findings and Approaches, pp. 85\u2013113. Springer (2016)","DOI":"10.1007\/978-3-319-38756-7_4"},{"key":"14_CR11","doi-asserted-by":"crossref","unstructured":"Jang, I.S., Li, K.J., Joo, E.O., Kim, M.S.: Synthetic training dataset generation using a digital twin-based autonomous driving simulator. Sensors Mater. 36 (2024)","DOI":"10.18494\/SAM5343"},{"issue":"5","key":"14_CR12","doi-asserted-by":"publisher","first-page":"1801","DOI":"10.3390\/app14051801","volume":"14","author":"HC Kim","year":"2024","unstructured":"Kim, H.C., Lam, H.K., Lee, S.H., Ok, S.Y.: Early fire detection system by using automatic synthetic dataset generation model based on digital twins. Appl. Sci. 14(5), 1801 (2024)","journal-title":"Appl. Sci."},{"key":"14_CR13","doi-asserted-by":"crossref","unstructured":"Lopes, P.V., Silveira, L., Guimaraes\u00a0Aquino, R.D., Ribeiro, C.H., Skoogh, A., Verri, F.A.N.: Synthetic data generation for digital twins: enabling production systems analysis in the absence of data. Int. J. Comput. Integr. Manuf. 37(10-11), 1252\u20131269 (2024)","DOI":"10.1080\/0951192X.2024.2322981"},{"key":"14_CR14","doi-asserted-by":"publisher","first-page":"178627","DOI":"10.1109\/ACCESS.2020.3027535","volume":"8","author":"F Muheidat","year":"2020","unstructured":"Muheidat, F., Lo\u2019Ai, A.T.: In-home floor based sensor system-smart carpet-to facilitate healthy aging in place (AIP). IEEE Access 8, 178627\u2013178638 (2020)","journal-title":"IEEE Access"},{"key":"14_CR15","unstructured":"Murphy, D., Zhu, J., Liang, P.P., Matusik, W., Luo, Y.: WiReSens toolkit: an open-source platform towards accessible wireless tactile sensing. arXiv preprint: arXiv:2412.00247 (2024)"},{"key":"14_CR16","doi-asserted-by":"publisher","first-page":"100546","DOI":"10.1016\/j.cosrev.2023.100546","volume":"48","author":"H Murtaza","year":"2023","unstructured":"Murtaza, H., Ahmed, M., Khan, N.F., Murtaza, G., Zafar, S., Bano, A.: Synthetic data generation: state of the art in health care domain. Comput. Sci. Rev. 48, 100546 (2023)","journal-title":"Comput. Sci. Rev."},{"key":"14_CR17","unstructured":"Sabir, A., et al.: Synthetic data generation with unity 3D and unreal engine for construction hazard scenarios: a comparative analysis. In: International Conference on Construction Engineering and Project Management, pp. 1286\u20131288. Korea Institute of Construction Engineering and Management (2024)"},{"issue":"15","key":"14_CR18","doi-asserted-by":"publisher","first-page":"6700","DOI":"10.3390\/s23156700","volume":"23","author":"Y Shi","year":"2023","unstructured":"Shi, Y., Zhang, Y., Li, Z., Yuan, S., Zhu, S.: IMU\/UWB fusion method using a complementary filter and a Kalman filter for hybrid upper limb motion estimation. Sensors 23(15), 6700 (2023)","journal-title":"Sensors"},{"key":"14_CR19","doi-asserted-by":"publisher","first-page":"205520762211496","DOI":"10.1177\/20552076221149651","volume":"9","author":"T Sun","year":"2023","unstructured":"Sun, T., He, X., Li, Z.: Digital twin in healthcare: recent updates and challenges. Digital Health 9, 20552076221149652 (2023)","journal-title":"Digital Health"},{"key":"14_CR20","doi-asserted-by":"publisher","first-page":"107253","DOI":"10.1016\/j.dib.2021.107253","volume":"37","author":"A To\u0161i\u0107","year":"2021","unstructured":"To\u0161i\u0107, A., Hrovatin, N., Vi\u010di\u010d, J.: Data about fall events and ordinary daily activities from a sensorized smart floor. Data Brief 37, 107253 (2021)","journal-title":"Data Brief"},{"key":"14_CR21","doi-asserted-by":"crossref","unstructured":"Uhlenberg, L., Haeusler, L.O., Amft, O.: SynHAR: augmenting human activity recognition with synthetic inertial sensor data generated from human surface models. IEEE Access (2024)","DOI":"10.1109\/ACCESS.2024.3513477"},{"issue":"15","key":"14_CR22","doi-asserted-by":"publisher","first-page":"5134","DOI":"10.3390\/s21155134","volume":"21","author":"S Usmani","year":"2021","unstructured":"Usmani, S., Saboor, A., Haris, M., Khan, M.A., Park, H.: Latest research trends in fall detection and prevention using machine learning: a systematic review. Sensors 21(15), 5134 (2021)","journal-title":"Sensors"},{"issue":"5","key":"14_CR23","doi-asserted-by":"publisher","first-page":"1118","DOI":"10.1109\/JSAC.2017.2679658","volume":"35","author":"W Wang","year":"2017","unstructured":"Wang, W., Liu, A.X., Shahzad, M., Ling, K., Lu, S.: Device-free human activity recognition using commercial WiFi devices. IEEE J. Sel. Areas Commun. 35(5), 1118\u20131131 (2017)","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"14_CR24","unstructured":"World Health Organization: Falls (2021). https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/falls"},{"key":"14_CR25","doi-asserted-by":"crossref","unstructured":"Zompanti, A., Romeo, P., Sabatini, A., Vollero, L., Santonico, M., Pennazza, G.: Energy-harvesting smart tiles for human\u2013machine interface applications. In: Proceedings, vol.\u00a097, p.\u00a035. MDPI (2024)","DOI":"10.3390\/proceedings2024097035"}],"container-title":["Lecture Notes in Computer Science","Sensor-Based Activity Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-13312-0_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T03:14:39Z","timestamp":1767323679000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-13312-0_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032133113","9783032133120"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-13312-0_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"2 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"iWOAR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Sensor-Based Activity Recognition and Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Enschede","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 September 2025","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":"iwoar2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.iwoar.org","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}