{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T05:05:56Z","timestamp":1742965556843,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030200541"},{"type":"electronic","value":"9783030200558"}],"license":[{"start":{"date-parts":[[2019,5,1]],"date-time":"2019-05-01T00:00:00Z","timestamp":1556668800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-20055-8_21","type":"book-chapter","created":{"date-parts":[[2019,4,30]],"date-time":"2019-04-30T09:16:38Z","timestamp":1556615798000},"page":"219-228","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Feature Clustering to Improve Fall Detection: A Preliminary Study"],"prefix":"10.1007","author":[{"given":"Mirko","family":"F\u00e1\u00f1ez","sequence":"first","affiliation":[]},{"given":"Jos\u00e9 Ram\u00f3n","family":"Villar","sequence":"additional","affiliation":[]},{"given":"Enrique","family":"de la Cal","sequence":"additional","affiliation":[]},{"given":"V\u00edctor M.","family":"Gonz\u00e1lez","sequence":"additional","affiliation":[]},{"given":"Javier","family":"Sedano","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,5,1]]},"reference":[{"issue":"6","key":"21_CR1","doi-asserted-by":"publisher","first-page":"883","DOI":"10.1016\/j.pmcj.2012.08.003","volume":"8","author":"S Abbate","year":"2012","unstructured":"Abbate, S., Avvenuti, M., Bonatesta, F., Cola, G., Corsini, P.: AlessioVecchio: a smartphone-based fall detection system. Pervasive Mobile Comput. 8(6), 883\u2013899 (2012)","journal-title":"Pervasive Mobile Comput."},{"key":"21_CR2","doi-asserted-by":"crossref","unstructured":"Abbate, S., Avvenuti, M., Corsini, P., Light, J., Vecchio, A.: Monitoring of human movements for fall detection and activities recognition in elderly care using wireless sensor network: a survey. In: Wireless Sensor Networks: Application - Centric Design, p. 22. Intech (2010)","DOI":"10.5772\/13802"},{"key":"21_CR3","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1016\/j.gaitpost.2006.09.012","volume":"26","author":"A Bourke","year":"2007","unstructured":"Bourke, A., O\u2019Brien, J., Lyons, G.: Evaluation of a threshold-based triaxial accelerometer fall detection algorithm. Gait Posture 26, 194\u2013199 (2007)","journal-title":"Gait Posture"},{"issue":"10","key":"21_CR4","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). \n                    http:\/\/www.mdpi.com\/1424-8220\/14\/10\/19806\/htm","journal-title":"Sensors"},{"key":"21_CR5","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1016\/j.proeng.2014.10.539","volume":"85","author":"YC Fang","year":"2014","unstructured":"Fang, Y.C., Dzeng, R.J.: A smartphone-based detection of fall portents for construction workers. Procedia Eng. 85, 147\u2013156 (2014)","journal-title":"Procedia Eng."},{"key":"21_CR6","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1016\/j.autcon.2017.09.015","volume":"84","author":"YC Fang","year":"2017","unstructured":"Fang, Y.C., Dzeng, R.J.: Accelerometer-based fall-portent detection algorithm for construction tiling operation. Autom. Constr. 84, 214\u2013230 (2017)","journal-title":"Autom. Constr."},{"key":"21_CR7","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.procs.2017.01.188","volume":"105","author":"A Hakim","year":"2017","unstructured":"Hakim, A., Huq, M.S., Shanta, S., Ibrahim, B.: Smartphone based data mining for fall detection: analysis and design. Procedia Comput. Sci. 105, 46\u201351 (2017). \n                    http:\/\/www.sciencedirect.com\/science\/article\/pii\/S1877050917302065","journal-title":"Procedia Comput. Sci."},{"key":"21_CR8","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1155\/2015\/452078","volume":"2015","author":"QT Huynh","year":"2015","unstructured":"Huynh, Q.T., Nguyen, U.D., Irazabal, L.B., Ghassemian, N., Tran, B.Q.: Optimization of an accelerometer and gyroscope-based fall detection algorithm. J. Sens. 2015, 8 (2015)","journal-title":"J. Sens."},{"key":"21_CR9","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1186\/1475-925X-12-66","volume":"12","author":"R Igual","year":"2013","unstructured":"Igual, R., Medrano, C., Plaza, I.: Challenges, issues and trends in fall detection systems. Biomed. Eng. Online 12, 66 (2013). \n                    http:\/\/www.biomedical-engineering-online.com\/content\/12\/1\/66","journal-title":"Biomed. Eng. Online"},{"key":"21_CR10","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1016\/j.gaitpost.2008.01.003","volume":"28","author":"M Kangas","year":"2008","unstructured":"Kangas, M., Konttila, A., Lindgren, P., Winblad, I., J\u00e4msa\u00e4, T.: Comparison of low-complexity fall detection algorithms for body attached accelerometers. Gait Posture 28, 285\u2013291 (2008)","journal-title":"Gait Posture"},{"issue":"5","key":"21_CR11","doi-asserted-by":"publisher","first-page":"1350","DOI":"10.3390\/s18051350","volume":"18","author":"SB Khojasteh","year":"2018","unstructured":"Khojasteh, S.B., Villar, J.R., Chira, C., Gonzalez, V.M., de la Cal, E.: Improving fall detection using an on-wrist wearable accelerometer. Sensors 18(5), 1350 (2018)","journal-title":"Sensors"},{"key":"21_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/s18051350","volume":"18","author":"SB Khojasteh","year":"2018","unstructured":"Khojasteh, S.B., Villar, J.R., Chira, C., Gonz\u00e1lez, V.M., de la Cal, E.: Improving fall detection using an on-wrist wearable accelerometer. Sensors 18, 1\u201320 (2018)","journal-title":"Sensors"},{"key":"21_CR13","unstructured":"Meyer, D., et al.: Probability Theory Group (Formerly: E1071), TU Wien - Package \u2019e1071\u2019 (2019). \n                    https:\/\/cran.r-project.org\/web\/packages\/e1071\/e1071.pdf"},{"key":"21_CR14","unstructured":"Purch.com: Top ten reviews for fall detection of seniors (2018). \n                    www.toptenreviews.com\/health\/senior-care\/best-fall-detection-sensors\/"},{"key":"21_CR15","unstructured":"R Core Team and contributors: K-means clustering in R stats package (2019). \n                    https:\/\/stat.ethz.ch\/R-manual\/R-devel\/library\/stats\/html\/kmeans.html"},{"key":"21_CR16","unstructured":"Ripley, B., Venables, W.: Functions for classification - package \u2018class\u2019 (2019). \n                    https:\/\/cran.r-project.org\/web\/packages\/class\/class.pdf"},{"key":"21_CR17","doi-asserted-by":"crossref","unstructured":"Khojasteh, S.B., Villar, J.R., de la Cal, E., Gonz\u00e1lez, V.M., Sedano, J., Yazg\u0308an, H.R.: Evaluation of a wrist-based wearable fall detection method. In: 13th International Conference on Soft Computing Models in Industrial and Environmental Applications, pp. 377\u2013386 (2018)","DOI":"10.1007\/978-3-319-92639-1_31"},{"key":"21_CR18","unstructured":"Wu, F., Zhao, H., Zhao, Y., Zhong, H.: Development of a wearable-sensor-based fall detection system. Int. J. Telemed. Appl. (2015). \n                    https:\/\/www.hindawi.com\/journals\/ijta\/2015\/576364\/"},{"key":"21_CR19","first-page":"31","volume":"2017","author":"S Zhang","year":"2017","unstructured":"Zhang, S., Wei, Z., Nie, J., Huang, L., Wang, S., Li, Z.: A review on human activity recognition using vision-based method. J. Healthc. Eng. 2017, 31 (2017)","journal-title":"J. Healthc. Eng."},{"key":"21_CR20","doi-asserted-by":"crossref","unstructured":"Zhang, T., Wang, J., Xu, L., Liu, P.: Fall detection by wearable sensor and one-class svm algorithm. In: Huang\u00a0DS., Li\u00a0K., I.G. (ed.) Intelligent Computing in Signal Processing and Pattern Recognition, Lecture Notes in Control and Information Systems, vol. 345, pp. 858\u2013863. Springer Berlin Heidelberg (2006)","DOI":"10.1007\/11816515_104"}],"container-title":["Advances in Intelligent Systems and Computing","14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019)"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-20055-8_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,18]],"date-time":"2019-05-18T04:12:48Z","timestamp":1558152768000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-20055-8_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,1]]},"ISBN":["9783030200541","9783030200558"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-20055-8_21","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2019,5,1]]},"assertion":[{"value":"1 May 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SOCO","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Soft Computing Models in Industrial and Environmental Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Seville","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 May 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 May 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"socomoin2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2019.sococonference.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}