{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T02:24:54Z","timestamp":1772763894683,"version":"3.50.1"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2020,12,22]],"date-time":"2020-12-22T00:00:00Z","timestamp":1608595200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,12,22]],"date-time":"2020-12-22T00:00:00Z","timestamp":1608595200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100010016","name":"Nottingham Trent University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010016","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2022,2]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Human activity recognition (HAR) is used to support older adults to live independently in their own homes. Once activities of daily living (ADL) are recognised, gathered information will be used to identify abnormalities in comparison with the routine activities. Ambient sensors, including occupancy sensors and door entry sensors, are often used to monitor and identify different activities. Most of the current research in HAR focuses on a single-occupant environment when only one person is monitored, and their activities are categorised. The assumption that home environments are occupied by one person all the time is often not true. It is common for a resident to receive visits from family members or health care workers, representing a multi-occupancy environment. Entropy analysis is an established method for irregularity detection in many applications; however, it has been rarely applied in the context of ADL and HAR. In this paper, a novel method based on different entropy measures, including Shannon Entropy, Permutation Entropy, and Multiscale-Permutation Entropy, is employed to investigate the effectiveness of these entropy measures in identifying visitors in a home environment. This research aims to investigate whether entropy measures can be utilised to identify a visitor in a home environment, solely based on the information collected from motion detectors [e.g., passive infra-red] and door entry sensors. The entropy measures are tested and evaluated based on a dataset gathered from a real home environment. Experimental results are presented to show the effectiveness of entropy measures to identify visitors and the time of their visits without the need for employing extra wearable sensors to tag the visitors. The results obtained from the experiments show that the proposed entropy measures could be used to detect and identify a visitor in a home environment with a high degree of accuracy.<\/jats:p>","DOI":"10.1007\/s12652-020-02824-z","type":"journal-article","created":{"date-parts":[[2020,12,22]],"date-time":"2020-12-22T15:03:17Z","timestamp":1608649397000},"page":"1093-1106","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Employing entropy measures to identify visitors in multi-occupancy environments"],"prefix":"10.1007","volume":"13","author":[{"given":"Aadel","family":"Howedi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5139-6565","authenticated-orcid":false,"given":"Ahmad","family":"Lotfi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amir","family":"Pourabdollah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,12,22]]},"reference":[{"key":"2824_CR1","doi-asserted-by":"crossref","unstructured":"Aicha AN, Englebienne G, Kr\u00f6se B (2012) How busy is my supervisor? Detecting the visits in the office of my supervisor using a sensor network. In: Proceedings of the 5th international conference on pervasive technologies related to assistive environments. ACM, p\u00a012","DOI":"10.1145\/2413097.2413112"},{"key":"2824_CR2","doi-asserted-by":"crossref","unstructured":"Aicha AN, Englebienne G, Kr\u00f6se B (2014) Modeling visit behaviour in smart homes using unsupervised learning. In: Proceedings of the 2014 ACM international joint conference on pervasive and ubiquitous computing: adjunct publication. ACM, pp 1193\u20131200","DOI":"10.1145\/2638728.2638809"},{"key":"2824_CR3","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1016\/j.pmcj.2016.05.003","volume":"34","author":"AN Aicha","year":"2017","unstructured":"Aicha AN, Englebienne G, Kr\u00f6se B (2017) Unsupervised visit detection in smart homes. Pervasive Mob Comput 34:157\u2013167","journal-title":"Pervasive Mob Comput"},{"issue":"4","key":"2824_CR4","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1007\/s12652-016-0440-x","volume":"8","author":"H Alemdar","year":"2017","unstructured":"Alemdar H, Ersoy C (2017) Multi-resident activity tracking and recognition in smart environments. J Ambient Intell Humaniz Comput 8(4):513\u2013529","journal-title":"J Ambient Intell Humaniz Comput"},{"issue":"12","key":"2824_CR5","doi-asserted-by":"publisher","first-page":"31314","DOI":"10.3390\/s151229858","volume":"15","author":"F Attal","year":"2015","unstructured":"Attal F, Mohammed S, Dedabrishvili M, Chamroukhi F, Oukhellou L, Amirat Y (2015) Physical human activity recognition using wearable sensors. Sensors 15(12):31314\u201331338","journal-title":"Sensors"},{"key":"2824_CR6","doi-asserted-by":"crossref","unstructured":"Aziz W, Arif M (2005) Multiscale permutation entropy of physiological time series. In: 2005 Pakistan section multitopic conference. IEEE, pp 1\u20136","DOI":"10.1109\/INMIC.2005.334494"},{"issue":"17","key":"2824_CR7","doi-asserted-by":"publisher","first-page":"174102","DOI":"10.1103\/PhysRevLett.88.174102","volume":"88","author":"C Bandt","year":"2002","unstructured":"Bandt C, Pompe B (2002) Permutation entropy: a natural complexity measure for time series. Phys Rev Lett 88(17):174102","journal-title":"Phys Rev Lett"},{"issue":"3","key":"2824_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2835372","volume":"48","author":"A Benmansour","year":"2015","unstructured":"Benmansour A, Bouchachia A, Feham M (2015) Multioccupant activity recognition in pervasive smart home environments. ACM Comput Surv (CSUR) 48(3):1\u201336","journal-title":"ACM Comput Surv (CSUR)"},{"issue":"3","key":"2824_CR9","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1145\/2835372","volume":"48","author":"A Benmansour","year":"2016","unstructured":"Benmansour A, Bouchachia A, Feham M (2016) Multioccupant activity recognition in pervasive smart home environments. ACM Comput Surv (CSUR) 48(3):34","journal-title":"ACM Comput Surv (CSUR)"},{"key":"2824_CR10","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1016\/j.neucom.2016.05.110","volume":"230","author":"A Benmansour","year":"2017","unstructured":"Benmansour A, Bouchachia A, Feham M (2017) Modeling interaction in multi-resident activities. Neurocomputing 230:133\u2013142","journal-title":"Neurocomputing"},{"issue":"1","key":"2824_CR11","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1515\/slgr-2015-0039","volume":"43","author":"M Borowska","year":"2015","unstructured":"Borowska M (2015) Entropy-based algorithms in the analysis of biomedical signals. Stud Log Gramm Rhetor 43(1):21\u201332","journal-title":"Stud Log Gramm Rhetor"},{"key":"2824_CR12","doi-asserted-by":"crossref","unstructured":"Chernbumroong S, Lotfi A, Langensiepen C (2014) (2014) Prediction of mobility entropy in an ambient intelligent environment. In: IEEE symposium on intelligent agents (IA). IEEE, pp 65\u201372","DOI":"10.1109\/IA.2014.7009460"},{"issue":"4","key":"2824_CR13","doi-asserted-by":"publisher","first-page":"500","DOI":"10.1002\/andp.18501550403","volume":"155","author":"R Clausius","year":"1850","unstructured":"Clausius R (1850) On the motive power of heat and the laws which can be deduced therefrom regarding the theory of heat. Ann Phys 155(4):500\u2013524","journal-title":"Ann Phys"},{"key":"2824_CR14","unstructured":"Dheeru D, Taniskidou E (2017) UCI machine learning repository. https:\/\/archive.ics.uci.edu\/ml\/index.php. Accessed 18 Jan 2019"},{"key":"2824_CR15","doi-asserted-by":"crossref","unstructured":"Eldib M, Deboeverie F, Haerenborgh DV, Philips W, Aghajan H (2015) Detection of visitors in elderly care using a low-resolution visual sensor network. In: Proceedings of the 9th international conference on distributed smart cameras. ACM, pp 56\u201361","DOI":"10.1145\/2789116.2789137"},{"key":"2824_CR16","doi-asserted-by":"crossref","unstructured":"Ghosh A, Chakraborty A, Kumbhakar J, Saha M, Saha S (2020) Humansense: a framework for collective human activity identification using heterogeneous sensor grid in multi-inhabitant smart environments. Pers Ubiquitous Comput","DOI":"10.1007\/s00779-020-01402-6"},{"key":"2824_CR17","doi-asserted-by":"crossref","unstructured":"Gochoo M, Tan TH, Jean FR, Huang SC, Kuo SY (2017) Device-free non-invasive front-door event classification algorithm for forget event detection using binary sensors in the smart house. In: IEEE international conference on systems, man, and cybernetics. IEEE, pp 405\u2013409","DOI":"10.1109\/SMC.2017.8122638"},{"key":"2824_CR18","unstructured":"Han M, Xu W, Tao H, Gong Y (2004) An algorithm for multiple object trajectory tracking. In: Proceedings of the 2004 IEEE computer society conference on computer vision and pattern recognition, 2004. CVPR 2004, vol 1. IEEE, pp I\u2013I"},{"key":"2824_CR19","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/j.neucom.2018.08.033","volume":"318","author":"J Hao","year":"2018","unstructured":"Hao J, Bouzouane A, Gaboury S (2018) Recognizing multi-resident activities in non-intrusive sensor-based smart homes by formal concept analysis. Neurocomputing 318:75\u201389","journal-title":"Neurocomputing"},{"issue":"4","key":"2824_CR20","doi-asserted-by":"publisher","first-page":"416","DOI":"10.3390\/e21040416","volume":"21","author":"A Howedi","year":"2019","unstructured":"Howedi A, Lotfi A, Pourabdollah A (2019) Exploring entropy measurements to identify multi-occupancy in activities of daily living. Entropy 21(4):416","journal-title":"Entropy"},{"key":"2824_CR21","doi-asserted-by":"crossref","unstructured":"Hsu KC, Chiang YT, Lin GY, Lu CH, Hsu JYJ, Fu LC (2010) Strategies for inference mechanism of conditional random fields for multiple-resident activity recognition in a smart home. In: International conference on industrial, engineering and other applications of applied intelligent systems. Springer, Berlin, pp 417\u2013426","DOI":"10.1007\/978-3-642-13022-9_42"},{"key":"2824_CR22","doi-asserted-by":"crossref","unstructured":"Hu R, Pham H, Buluschek P, Gatica-Perez D (2017) Elderly people living alone: detecting home visits with ambient and wearable sensing. In: Proceedings of the 2nd international workshop on multimedia for personal health and health care. ACM, pp 85\u201388","DOI":"10.1145\/3132635.3132649"},{"key":"2824_CR23","unstructured":"Huang Q, Ge Z, Lu C (2016) Occupancy estimation in smart buildings using audio-processing techniques. arXiv:160208507"},{"key":"2824_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.36680\/j.itcon.2019.001","volume":"24","author":"Q Huang","year":"2019","unstructured":"Huang Q, Rodriguez K, Whetstone N, Habel S (2019) Rapid internet of Things (IoT) prototype for accurate people counting towards energy efficient buildings. ITcon 24:1\u201313","journal-title":"ITcon"},{"issue":"1","key":"2824_CR25","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1109\/MPRV.2010.7","volume":"9","author":"E Kim","year":"2009","unstructured":"Kim E, Helal S, Cook D (2009) Human activity recognition and pattern discovery. IEEE Pervasive Comput 9(1):48\u201353","journal-title":"IEEE Pervasive Comput"},{"key":"2824_CR26","doi-asserted-by":"crossref","unstructured":"Langensiepen C, Lotfi A (2017) Uncertainty measures in an ambient intelligence environment. In: 2017 IEEE international conference on fuzzy systems (FUZZ-IEEE). IEEE, pp 1\u20135","DOI":"10.1109\/FUZZ-IEEE.2017.8015765"},{"key":"2824_CR27","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1016\/j.procs.2020.03.082","volume":"170","author":"P Lapointe","year":"2020","unstructured":"Lapointe P, Chapron K, Bouchard K et al (2020) A new device to track and identify people in a multi-residents context. Procedia Comput Sci 170:403\u2013410","journal-title":"Procedia Comput Sci"},{"issue":"2","key":"2824_CR28","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1007\/s10877-012-9419-0","volume":"27","author":"D Li","year":"2013","unstructured":"Li D, Liang Z, Wang Y, Hagihira S, Sleigh JW, Li X (2013) Parameter selection in permutation entropy for an electroencephalographic measure of isoflurane anesthetic drug effect. J Clin Monit Comput 27(2):113\u2013123","journal-title":"J Clin Monit Comput"},{"key":"2824_CR29","doi-asserted-by":"crossref","unstructured":"Li Q, Gravina R, Li Y, Alsamhi SH, Sun F, Fortino G (2020) Multi-user activity recognition: challenges and opportunities. Inf Fusion","DOI":"10.1016\/j.inffus.2020.06.004"},{"issue":"12","key":"2824_CR30","doi-asserted-by":"publisher","first-page":"2744","DOI":"10.1109\/TKDE.2017.2750669","volume":"29","author":"BD Minor","year":"2017","unstructured":"Minor BD, Doppa JR, Cook DJ (2017) Learning activity predictors from sensor data: algorithms, evaluation, and applications. IEEE Trans Knowl Data Eng 29(12):2744\u20132757","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"6","key":"2824_CR31","doi-asserted-by":"publisher","first-page":"21","DOI":"10.14257\/ijsh.2017.11.6.03","volume":"11","author":"R Mohamed","year":"2017","unstructured":"Mohamed R, Perumal T, Sulaiman MN, Mustapha N (2017a) Multi resident complex activity recognition in smart home: a literature review. Int J Smart Home 11(6):21\u201332","journal-title":"Int J Smart Home"},{"issue":"(2\u201311)","key":"2824_CR32","first-page":"39","volume":"9","author":"R Mohamed","year":"2017","unstructured":"Mohamed R, Perumal T, Sulaiman MN, Mustapha N, Manaf SA (2017b) Tracking and recognizing the activity of multi resident in smart home environments. J Telecommun Electron Comput Eng (JTEC) 9((2\u201311)):39\u201343","journal-title":"J Telecommun Electron Comput Eng (JTEC)"},{"issue":"3","key":"2824_CR33","doi-asserted-by":"publisher","first-page":"908","DOI":"10.3390\/s18030908","volume":"18","author":"G Mokhtari","year":"2018","unstructured":"Mokhtari G, Anvari-Moghaddam A, Zhang Q, Karunanithi M (2018) Multi-residential activity labelling in smart homes with wearable tags using BLE technology. Sensors 18(3):908","journal-title":"Sensors"},{"issue":"7","key":"2824_CR34","doi-asserted-by":"publisher","first-page":"1186","DOI":"10.3390\/e14071186","volume":"14","author":"FC Morabito","year":"2012","unstructured":"Morabito FC, Labate D, La Foresta F, Bramanti A, Morabito G, Palamara I (2012) Multivariate multi-scale permutation entropy for complexity analysis of Alzheimer\u2019s disease EEG. Entropy 14(7):1186\u20131202","journal-title":"Entropy"},{"key":"2824_CR35","volume-title":"Machine learning: a probabilistic perspective","author":"KP Murphy","year":"2012","unstructured":"Murphy KP (2012) Machine learning: a probabilistic perspective. MIT Press, Cambridge"},{"key":"2824_CR36","doi-asserted-by":"crossref","unstructured":"Nait Aicha A, Englebienne G, Kr\u00f6se B (2013) How lonely is your grandma? Detecting the visits to assisted living elderly from wireless sensor network data. In: Proceedings of the ACM conference on pervasive and ubiquitous computing adjunct publication, pp 1285\u20131294","DOI":"10.1145\/2494091.2497283"},{"key":"2824_CR37","doi-asserted-by":"crossref","unstructured":"Najar F, Bourouis S, Bouguila N, Belghith S (2019) Unsupervised learning of finite full covariance multivariate generalized gaussian mixture models for human activity recognition. Multimed Tools Appl 1\u201323","DOI":"10.1007\/s11042-018-7116-9"},{"key":"2824_CR38","doi-asserted-by":"crossref","unstructured":"Nguyen D, Nguyen L, Nguyen S (2020) A novel approach of ontology-based activity segmentation and recognition using pattern discovery in multi-resident homes. In: Frontiers in intelligent computing: theory and applications. Springer, Berlin, pp 167\u2013178","DOI":"10.1007\/978-981-32-9186-7_19"},{"issue":"1","key":"2824_CR39","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1186\/1743-0003-9-21","volume":"9","author":"S Patel","year":"2012","unstructured":"Patel S, Park H, Bonato P, Chan L, Rodgers M (2012) A review of wearable sensors and systems with application in rehabilitation. J Neuroeng Rehabilit 9(1):21","journal-title":"J Neuroeng Rehabilit"},{"key":"2824_CR40","doi-asserted-by":"crossref","unstructured":"Petersen J, Larimer N, Kaye JA, Pavel M, Hayes TL (2012) SVM to detect the presence of visitors in a smart home environment. In: 2012 Annual international conference of the IEEE engineering in medicine and biology society (EMBC), pp 5850\u20135853","DOI":"10.1109\/EMBC.2012.6347324"},{"key":"2824_CR41","unstructured":"R\u00e9nyi A, et al (1961) On measures of entropy and information. In: Proceedings of the fourth Berkeley symposium on mathematical statistics and probability, volume 1: contributions to the theory of statistics, The Regents of the University of California"},{"issue":"1","key":"2824_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s12652-015-0294-7","volume":"7","author":"N Roy","year":"2016","unstructured":"Roy N, Misra A, Cook D (2016) Ambient and smartphone sensor assisted ADL recognition in multi-inhabitant smart environments. J Ambient Intell Humaniz Comput 7(1):1\u201319","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"2824_CR43","doi-asserted-by":"crossref","unstructured":"Schumitsch B, Schwarz H, Wiegand T (2005) Optimization of transform coefficient selection and motion vector estimation considering interpicture dependencies in hybrid video coding. In: Image and video communications and processing 2005, International society for optics and photonics, vol 5685, pp 327\u2013335","DOI":"10.1117\/12.591950"},{"issue":"3","key":"2824_CR44","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1002\/j.1538-7305.1948.tb01338.x","volume":"27","author":"CE Shannon","year":"1948","unstructured":"Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27(3):379\u2013423","journal-title":"Bell Syst Tech J"},{"key":"2824_CR45","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1016\/j.aei.2016.12.008","volume":"33","author":"W Shen","year":"2017","unstructured":"Shen W, Newsham G, Gunay B (2017) Leveraging existing occupancy-related data for optimal control of commercial office buildings: a review. Adv Eng Inform 33:230\u2013242","journal-title":"Adv Eng Inform"},{"issue":"1","key":"2824_CR46","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1007\/s12652-009-0007-1","volume":"1","author":"G Singla","year":"2010","unstructured":"Singla G, Cook DJ, Schmitter-Edgecombe M (2010) Recognizing independent and joint activities among multiple residents in smart environments. J Ambient Intell Humaniz Comput 1(1):57\u201363","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"2824_CR47","doi-asserted-by":"publisher","first-page":"10734","DOI":"10.1109\/ACCESS.2017.2711495","volume":"5","author":"TH Tan","year":"2017","unstructured":"Tan TH, Gochoo M, Jean FR, Huang SC, Kuo SY (2017) Front-door event classification algorithm for elderly people living alone in smart house using wireless binary sensors. IEEE Access 5:10734\u201310743","journal-title":"IEEE Access"},{"issue":"23","key":"2824_CR48","doi-asserted-by":"publisher","first-page":"9718","DOI":"10.1109\/JSEN.2018.2866806","volume":"18","author":"TH Tan","year":"2018","unstructured":"Tan TH, Gochoo M, Huang SC, Liu YH, Liu SH, Huang YF (2018) Multi-resident activity recognition in a smart home using RGB activity image and DCNN. IEEE Sens J 18(23):9718\u20139727","journal-title":"IEEE Sens J"},{"key":"2824_CR49","doi-asserted-by":"crossref","unstructured":"Tran SN, Zhang Q (2020) Towards multi-resident activity monitoring with smarter safer home platform. In: Smart assisted living. Springer, Berlin, pp 249\u2013267","DOI":"10.1007\/978-3-030-25590-9_12"},{"issue":"16","key":"2824_CR50","doi-asserted-by":"publisher","first-page":"3123","DOI":"10.1177\/1077546314520830","volume":"21","author":"V Vakharia","year":"2015","unstructured":"Vakharia V, Gupta V, Kankar P (2015) A multiscale permutation entropy based approach to select wavelet for fault diagnosis of ball bearings. J Vib Control 21(16):3123\u20133131","journal-title":"J Vib Control"},{"issue":"3","key":"2824_CR51","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1016\/j.pmcj.2010.11.008","volume":"7","author":"L Wang","year":"2011","unstructured":"Wang L, Gu T, Tao X, Chen H, Lu J (2011) Recognizing multi-user activities using wearable sensors in a smart home. Pervasive Mob Comput 7(3):287\u2013298","journal-title":"Pervasive Mob Comput"},{"issue":"8","key":"2824_CR52","doi-asserted-by":"publisher","first-page":"1343","DOI":"10.3390\/e14081343","volume":"14","author":"SD Wu","year":"2012","unstructured":"Wu SD, Wu PH, Wu CW, Ding JJ, Wang CC (2012) Bearing fault diagnosis based on multiscale permutation entropy and support vector machine. Entropy 14(8):1343\u20131356","journal-title":"Entropy"},{"issue":"8","key":"2824_CR53","doi-asserted-by":"publisher","first-page":"960","DOI":"10.1177\/0037549713489918","volume":"90","author":"Z Yang","year":"2014","unstructured":"Yang Z, Li N, Becerik-Gerber B, Orosz M (2014) A systematic approach to occupancy modeling in ambient sensor-rich buildings. Simulation 90(8):960\u2013977","journal-title":"Simulation"},{"key":"2824_CR54","doi-asserted-by":"crossref","unstructured":"Zhao J, Frumkin N, Konrad J, Ishwar P (2018) Privacy-preserving indoor localization via active scene illumination. In: Proceedings of the IEEE conference on computer vision and pattern recognition workshops, pp 1580\u20131589","DOI":"10.1109\/CVPRW.2018.00208"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-020-02824-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-020-02824-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-020-02824-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,2,8]],"date-time":"2022-02-08T14:31:33Z","timestamp":1644330693000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-020-02824-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,22]]},"references-count":54,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2022,2]]}},"alternative-id":["2824"],"URL":"https:\/\/doi.org\/10.1007\/s12652-020-02824-z","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"value":"1868-5137","type":"print"},{"value":"1868-5145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12,22]]},"assertion":[{"value":"6 December 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 December 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 December 2020","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 authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}