{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T10:49:31Z","timestamp":1761648571228},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2018,7,31]],"date-time":"2018-07-31T00:00:00Z","timestamp":1532995200000},"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":["J Reliable Intell Environ"],"published-print":{"date-parts":[[2018,9]]},"DOI":"10.1007\/s40860-018-0065-2","type":"journal-article","created":{"date-parts":[[2018,7,31]],"date-time":"2018-07-31T08:40:34Z","timestamp":1533026434000},"page":"131-139","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Fall detection in smart home environments using UWB sensors and unsupervised change detection"],"prefix":"10.1007","volume":"4","author":[{"given":"G.","family":"Mokhtari","sequence":"first","affiliation":[]},{"given":"S.","family":"Aminikhanghahi","sequence":"additional","affiliation":[]},{"given":"Qing","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"D. J.","family":"Cook","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,7,31]]},"reference":[{"key":"65_CR1","first-page":"23","volume-title":"IoT-based fall detection for smart home environments","author":"S Greene","year":"2016","unstructured":"Greene S, Thapliyal H, Carpenter D (2016) IoT-based fall detection for smart home environments. IEEE, Piscataway, pp 23\u201328"},{"key":"65_CR2","doi-asserted-by":"publisher","first-page":"1503","DOI":"10.1109\/JSEN.2017.2647960","volume":"17","author":"G Mokhtari","year":"2017","unstructured":"Mokhtari G, Zhang Q, Nourbakhsh G, Ball S, Karunanithi M (2017) BLUESOUND: a new resident identification sensor\u2014using ultrasound array and BLE technology for smart home platform. IEEE Sens J 17:1503\u20131512","journal-title":"IEEE Sens J"},{"key":"65_CR3","doi-asserted-by":"crossref","unstructured":"Mokhtari G, Zhang Q, Fazlollahi A (2017) Non-wearable UWB sensor to detect falls in smart home environment. In: 2017 IEEE international conference on pervasive computing and communications workshop. IEEE, Piscataway, pp 274\u2013278","DOI":"10.1109\/PERCOMW.2017.7917571"},{"key":"65_CR4","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2018.2798062","author":"A Alberdi","year":"2018","unstructured":"Alberdi A, Weakley A, Schmitter-Edgecombe M, Cook DJ, Aztiria A, Basarab A, Barrenechea M (2018) Smart home-based prediction of multi-domain symptoms related to Alzheimer\u2019s disease. J Biomed Health Inform. \n                    https:\/\/doi.org\/10.1109\/JBHI.2018.2798062","journal-title":"J Biomed Health Inform"},{"key":"65_CR5","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 (2007) Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm. Gait Posture 26:194\u2013199","journal-title":"Gait Posture"},{"key":"65_CR6","first-page":"292","volume-title":"PerFallD: a pervasive fall detection system using mobile phones","author":"J Dai","year":"2010","unstructured":"Dai J, Bai X, Yang Z, Shen Z, Xuan D (2010) PerFallD: a pervasive fall detection system using mobile phones. IEEE, Piscataway, pp 292\u2013297"},{"key":"65_CR7","doi-asserted-by":"publisher","first-page":"616","DOI":"10.1007\/978-3-540-77046-6_76","volume-title":"Pattern recognition and machine intelligence","author":"V Vishwakarma","year":"2007","unstructured":"Vishwakarma V, Mandal C, Sural S (2007) Automatic detection of human fall in video. In: Pattern recognition and machine intelligence. Springer, Berlin, pp 616\u2013623"},{"key":"65_CR8","first-page":"1405","volume-title":"RGBD-camera based get-up event detection for hospital fall prevention","author":"B Ni","year":"2012","unstructured":"Ni B, Nguyen CD, Moulin P (2012) RGBD-camera based get-up event detection for hospital fall prevention. IEEE, Piscataway, pp 1405\u20131408"},{"key":"65_CR9","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2016.7590763","author":"M Skubic","year":"2016","unstructured":"Skubic M, Harris BH, Stone E, Ho KC, Su B-Y, Rantz M (2016) Testing non-wearable fall detection methods in the homes of older adults. Conf Proc IEEE Eng Med Biol Soc. \n                    https:\/\/doi.org\/10.1109\/EMBC.2016.7590763","journal-title":"Conf Proc IEEE Eng Med Biol Soc"},{"key":"65_CR10","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1007\/s11045-011-0161-4","volume":"23","author":"T Liu","year":"2012","unstructured":"Liu T, Guo X, Wang G (2012) Elderly-falling detection using distributed direction-sensitive pyroelectric infrared sensor arrays. Multidimens Syst Signal Process 23:451\u2013467","journal-title":"Multidimens Syst Signal Process"},{"key":"65_CR11","doi-asserted-by":"publisher","first-page":"581","DOI":"10.1109\/TMC.2016.2557792","volume":"16","author":"Y Wang","year":"2017","unstructured":"Wang Y, Wu K, Ni LM (2017) WiFall: device-free fall detection by wireless networks. IEEE Trans Mob Comput 16:581\u2013594","journal-title":"IEEE Trans Mob Comput"},{"key":"65_CR12","doi-asserted-by":"publisher","first-page":"3332","DOI":"10.1109\/JSEN.2017.2694555","volume":"17","author":"G Mokhtari","year":"2017","unstructured":"Mokhtari G, Zhang Q, Hargrave C, Ralston JC (2017) Non-wearable UWB sensor for human identification in smart home. IEEE Sens J 17:3332\u20133340","journal-title":"IEEE Sens J"},{"key":"65_CR13","doi-asserted-by":"publisher","first-page":"968","DOI":"10.1109\/TIFS.2016.2647225","volume":"12","author":"P Kumar","year":"2017","unstructured":"Kumar P, Braeken A, Gurtov A, Iinatti J, Ha PH (2017) Anonymous secure framework in connected smart home environments. IEEE Trans Inf Forensics Secur 12:968\u2013979","journal-title":"IEEE Trans Inf Forensics Secur"},{"key":"65_CR14","unstructured":"Hou E, Dai L, Wen Z (2017) Method, apparatus and electronic device for controlling smart home device smart home device, US Patent 9691272B2"},{"key":"65_CR15","doi-asserted-by":"crossref","unstructured":"Jeon S, Kang K-D, Lee H, Son SH (2016) Smart-bin using ultrawideband localization to assist people with movement disabilities. In: IEEE 22nd International Conference on Embedded and Real-time Computing Systems and Applications (RTCSA)","DOI":"10.1109\/RTCSA.2016.32"},{"key":"65_CR16","unstructured":"Pittella E (2010) UWB radar system for breath activity monitoring, PhD dissertation"},{"key":"65_CR17","unstructured":"Adams RP, MacKay DJC (2007) Bayesian online changepoint detection. Machine Learning. arXiv:0710.3742"},{"key":"65_CR18","first-page":"927","volume-title":"ICML'10 Proceedings of the 27th International conference on machine learning","author":"Y Saat\u00e7i","year":"2010","unstructured":"Saat\u00e7i Y, Turner RD, Rasmussen CE (2010) Gaussian process change point models. In: ICML'10 Proceedings of the 27th International conference on machine learning, Omnipress, Haifa, Israel, USA, pp 927\u2013934"},{"key":"65_CR19","volume-title":"Detection of abrupt changes: theory and application","author":"M Basseville","year":"1993","unstructured":"Basseville M, Nikiforov I (1993) Detection of abrupt changes: theory and application. Prentice Hall, Englewood Cliffs"},{"key":"65_CR20","doi-asserted-by":"crossref","unstructured":"Yamanishi K, Takeuchi J (2002) A unifying framework for detecting outliers and change points from non-stationary time series data. In: 8th ACM SIGKDD international conference on knowledge discovery and data mining-KDD 02. ACM Press, New York, p 676","DOI":"10.1145\/775047.775148"},{"key":"65_CR21","doi-asserted-by":"publisher","unstructured":"Kawahara Y, Sugiyama M (2009) Sequential change-point detection based on direct density-ratio estimation. In: SIAM international conference on data mining, pp 389\u2013400. \n                    https:\/\/doi.org\/10.1137\/1.9781611972795.34","DOI":"10.1137\/1.9781611972795.34"},{"key":"65_CR22","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1016\/j.neunet.2013.01.012","volume":"43","author":"S Liu","year":"2013","unstructured":"Liu S, Yamada M, Collier N, Sugiyama M (2013) Change-point detection in time-series data by relative density-ratio estimation. Neural Netw Off J Int Neural Netw Soc 43:72\u201383","journal-title":"Neural Netw Off J Int Neural Netw Soc"},{"key":"65_CR23","doi-asserted-by":"publisher","first-page":"699","DOI":"10.1007\/s10463-008-0197-x","volume":"60","author":"M Sugiyama","year":"2008","unstructured":"Sugiyama M, Suzuki T, Nakajima S, Kashima H, von B\u00fcnau P, Kawanabe M (2008) Direct importance estimation for covariate shift adaptation. Ann Inst Stat Math 60:699\u2013746","journal-title":"Ann Inst Stat Math"},{"key":"65_CR24","first-page":"1391","volume":"10","author":"T Kanamori","year":"2009","unstructured":"Kanamori T, Hido S, Sugiyama M (2009) A least-squares approach to direct importance estimation. J Mach Learn Res 10:1391\u20131445","journal-title":"J Mach Learn Res"},{"key":"65_CR25","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2850347","author":"S Aminikhanghahi","year":"2018","unstructured":"Aminikhanghahi S, Wang T, Cook DJ, Fellow I (2018) Real-time change point detection with application to smart home time series data. IEEE Trans Knowl Data Eng. \n                    https:\/\/doi.org\/10.1109\/TKDE.2018.2850347","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"65_CR26","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1016\/j.cmpb.2014.09.005","volume":"117","author":"B Kwolek","year":"2014","unstructured":"Kwolek B, Kepski M (2014) Human fall detection on embedded platform using depth maps and wireless accelerometer. Comput Methods Programs Biomed 117:489\u2013501","journal-title":"Comput Methods Programs Biomed"},{"key":"65_CR27","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1016\/j.gaitpost.2006.09.012","volume":"26","author":"AK Bourke","year":"2007","unstructured":"Bourke AK, O\u2019Brien JV, Lyons GM (2007) Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm. Gait Posture 26:194\u2013199","journal-title":"Gait Posture"}],"container-title":["Journal of Reliable Intelligent Environments"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s40860-018-0065-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s40860-018-0065-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s40860-018-0065-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,7,30]],"date-time":"2019-07-30T23:14:34Z","timestamp":1564528474000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s40860-018-0065-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,31]]},"references-count":27,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2018,9]]}},"alternative-id":["65"],"URL":"https:\/\/doi.org\/10.1007\/s40860-018-0065-2","relation":{},"ISSN":["2199-4668","2199-4676"],"issn-type":[{"value":"2199-4668","type":"print"},{"value":"2199-4676","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,7,31]]},"assertion":[{"value":"20 May 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 July 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 July 2018","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The UWB participant data was collected with ethics approval from CSIRO Health and Medical Research Ethics Committee-Proposal #LR 12\/2016. This work was supported in part by the National Science Foundation under Grant no. 1543656.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics committee approval"}}]}}