{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T09:13:04Z","timestamp":1742980384170,"version":"3.40.3"},"publisher-location":"Cham","reference-count":11,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030004330"},{"type":"electronic","value":"9783030004347"}],"license":[{"start":{"date-parts":[[2018,8,15]],"date-time":"2018-08-15T00:00:00Z","timestamp":1534291200000},"content-version":"unspecified","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":[[2019]]},"DOI":"10.1007\/978-3-319-98678-4_53","type":"book-chapter","created":{"date-parts":[[2018,8,14]],"date-time":"2018-08-14T09:25:31Z","timestamp":1534238731000},"page":"533-541","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Recognition of the Pathology of the Human Movement with the Use of Mobile Technology and Machine Learning"],"prefix":"10.1007","author":[{"given":"Kazimierz","family":"Fr\u0105czkowski","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sandra","family":"\u0141aska","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,8,15]]},"reference":[{"key":"53_CR1","doi-asserted-by":"crossref","unstructured":"Bao, L., Intille, S.S.: Activity recognition from user-annotated acceleration data. In: International Conference on Pervasive Computing. Springer, Heidelberg (2004)","DOI":"10.1007\/978-3-540-24646-6_1"},{"issue":"3","key":"53_CR2","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1016\/S0169-2607(00)00137-1","volume":"64","author":"R Bellazzi","year":"2001","unstructured":"Bellazzi, R., et al.: Web-based telemedicine systems for home-care: technical issues and experiences. Comput. Methods Programs Biomed. 64(3), 175\u2013187 (2001)","journal-title":"Comput. Methods Programs Biomed."},{"key":"53_CR3","doi-asserted-by":"crossref","unstructured":"Berndt, R.D., et al.: SaaS-platform for mobile health applications. In: 2012 9th International Multi-Conference on Systems, Signals and Devices (SSD). IEEE (2012)","DOI":"10.1109\/SSD.2012.6198120"},{"key":"53_CR4","first-page":"77","volume":"6","author":"MFA Abdullah bin","year":"2012","unstructured":"bin Abdullah, M.F.A., et al.: Classification algorithms in human activity recognition using smartphones. Int. J. Comput. Inf. Eng. 6, 77\u201384 (2012)","journal-title":"Int. J. Comput. Inf. Eng."},{"key":"53_CR5","first-page":"3","volume":"160","author":"SB Kotsiantis","year":"2007","unstructured":"Kotsiantis, S.B., Zaharakis, I., Pintelas, P.: Supervised machine learning: a review of classification techniques. Emerg. Artif. Intell. Appl. Comput. Eng. 160, 3\u201324 (2007)","journal-title":"Emerg. Artif. Intell. Appl. Comput. Eng."},{"issue":"2","key":"53_CR6","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1145\/1964897.1964918","volume":"12","author":"JR Kwapisz","year":"2011","unstructured":"Kwapisz, J.R., Weiss, G.M., Moore, S.A.: Activity recognition using cell phone accelerometers. ACM SIGKDD Explor. Newsl. 12(2), 74\u201382 (2011)","journal-title":"ACM SIGKDD Explor. Newsl."},{"issue":"1","key":"53_CR7","doi-asserted-by":"publisher","first-page":"134","DOI":"10.3390\/s16010134","volume":"16","author":"A Mannini","year":"2016","unstructured":"Mannini, A., et al.: A machine learning framework for gait classification using inertial sensors: application to elderly, post-stroke and huntington\u2019s disease patients. Sensors 16(1), 134 (2016)","journal-title":"Sensors"},{"issue":"3-4","key":"53_CR8","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1007\/s00508-016-1096-4","volume":"129","author":"W Pirker","year":"2017","unstructured":"Pirker, W., Katzenschlager, R.: Gait disorders in adults and the elderly. Wien. Klin. Wochenschr. 129(3-4), 81\u201395 (2017)","journal-title":"Wien. Klin. Wochenschr."},{"issue":"2","key":"53_CR9","first-page":"49","volume":"12","author":"RW Soutas-Little","year":"1998","unstructured":"Soutas-Little, R.W.: Motion analysis and biomechanics. J. Rehabil. Res. Dev. 12(2), 49\u201368 (1998)","journal-title":"J. Rehabil. Res. Dev."},{"issue":"2","key":"53_CR10","doi-asserted-by":"publisher","first-page":"180","DOI":"10.3923\/jas.2012.180.185","volume":"12","author":"NM Tahir","year":"2012","unstructured":"Tahir, N.M., Manap, H.H.: Parkinson disease gait classification based on machine learning approach. J. Appl. Sci. 12(2), 180\u2013185 (2012)","journal-title":"J. Appl. Sci."},{"key":"53_CR11","unstructured":"Zheng, X., Ordieres-Mer\u00e9, J.: Development of a human movement monitoring system based on wearable devices. In: The International Conference on Electronics, Signal Processing and Communication Systems (ESPCO 2014) (2014)"}],"container-title":["Lecture Notes in Computer Science","Cryptology and Network Security"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-98678-4_53","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,22]],"date-time":"2019-10-22T04:47:31Z","timestamp":1571719651000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-98678-4_53"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,15]]},"ISBN":["9783030004330","9783030004347"],"references-count":11,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-98678-4_53","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018,8,15]]}}}