{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T19:57:17Z","timestamp":1767211037379,"version":"3.37.3"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2017,10,30]],"date-time":"2017-10-30T00:00:00Z","timestamp":1509321600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2017,10,30]],"date-time":"2017-10-30T00:00:00Z","timestamp":1509321600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["25293393"],"award-info":[{"award-number":["25293393"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004206","name":"Osaka University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004206","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Health Inf Sci Syst"],"published-print":{"date-parts":[[2017,12]]},"DOI":"10.1007\/s13755-017-0031-z","type":"journal-article","created":{"date-parts":[[2017,10,30]],"date-time":"2017-10-30T18:14:10Z","timestamp":1509387250000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Statistical sleep pattern modelling for sleep quality assessment based on sound events"],"prefix":"10.1007","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9356-9754","authenticated-orcid":false,"given":"Hongle","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Takafumi","family":"Kato","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masayuki","family":"Numao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ken-ichi","family":"Fukui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,10,30]]},"reference":[{"issue":"4","key":"31_CR1","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1053\/smrv.2001.0202","volume":"6","author":"T \u00c5kerstedt","year":"2002","unstructured":"\u00c5kerstedt T, Billiard M, Bonnet M, Ficca G, Garma L, Mariotti M, Salzarulo P, Schulz H. Awakening from sleep. Sleep Med Rev. 2002;6(4):267\u201386.","journal-title":"Sleep Med Rev"},{"issue":"7","key":"31_CR2","doi-asserted-by":"publisher","first-page":"R29","DOI":"10.1088\/0967-3334\/34\/7\/R29","volume":"34","author":"J Behar","year":"2013","unstructured":"Behar J, Roebuck A, Domingos JS, Gederi E, Clifford GD. A review of current sleep screening applications for smartphones. Physiol. Meas. 2013;34(7):R29\u201346.","journal-title":"Physiol. Meas."},{"key":"31_CR3","doi-asserted-by":"crossref","unstructured":"Berkhin P. A survey of clustering data mining techniques. In: Grouping multidimensional data. Berlin: Springer; 2006. p. 25\u201371.","DOI":"10.1007\/3-540-28349-8_2"},{"key":"31_CR4","unstructured":"Berry RB, Brooks R, Gamaldo CE, Harding SM, Marcus C, Vaughn B. The AASM manual for the scoring of sleep and associated events. Rules, Terminology\nand Technical Specifications. Darien, IL: American\nAcademy of Sleep Medicine; 2012."},{"issue":"2","key":"31_CR5","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1093\/sleep\/1.2.161","volume":"1","author":"MH Bonnet","year":"1978","unstructured":"Bonnet MH, Johnson LC. Relationship of arousal threshold to sleep stage distribution and subjective estimates of depth and quality of sleep. Sleep. 1978;1(2):161\u20138.","journal-title":"Sleep"},{"issue":"2","key":"31_CR6","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1016\/0165-1781(89)90047-4","volume":"28","author":"DJ Buysse","year":"1989","unstructured":"Buysse DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ. The pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193\u2013213.","journal-title":"Psychiatry Res"},{"key":"31_CR7","doi-asserted-by":"crossref","unstructured":"Chen Z, Lin M, Chen F, Lane ND, Cardone G, Wang R, Li T, Chen Y, Choudhury T, Campbell AT. Unobtrusive sleep monitoring using smartphones. In: 2013 7th International conference on pervasive computing technologies for healthcare and workshops. IEEE; 2013. p. 145\u201352.","DOI":"10.4108\/icst.pervasivehealth.2013.252148"},{"key":"31_CR8","doi-asserted-by":"crossref","unstructured":"Choe EK, Kientz JA, Halko S, Fonville A, Sakaguchi D, Watson NF. Opportunities for computing to support healthy sleep behavior. In: CHI\u201910 extended abstracts on human factors in computing systems. New York: ACM; 2010. p. 3661\u20136.","DOI":"10.1145\/1753846.1754035"},{"key":"31_CR9","volume-title":"Sleep disorders medicine: basic science, technical considerations, and clinical aspects","author":"S Chokroverty","year":"2013","unstructured":"Chokroverty, S. Sleep disorders medicine: basic science, technical considerations, and clinical aspects. Boston: Butterworth-Heinemann; 2013."},{"issue":"3","key":"31_CR10","first-page":"273","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes C, Vapnik V. Support-vector networks. Mach Learn. 1995;20(3):273\u201397.","journal-title":"Mach Learn"},{"issue":"2","key":"31_CR11","doi-asserted-by":"crossref","first-page":"205510291667901","DOI":"10.1177\/2055102916679012","volume":"3","author":"DL Dickinson","year":"1995","unstructured":"Dickinson DL, Cazier J, Cech T. A practical validation study of a commercial accelerometer using good and poor sleepers. Health Psychol Open 2016;3(2):2055102916679012.","journal-title":"Health Psychol Open"},{"key":"31_CR12","doi-asserted-by":"crossref","unstructured":"Freund Y, Schapire RE. A desicion-theoretic generalization of on-line learning and an application to boosting. In: European conference on computational learning theory. New York: Springer; 1995. p. 23\u201337.","DOI":"10.1007\/3-540-59119-2_166"},{"issue":"3","key":"31_CR13","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1299\/jee.6.499","volume":"6","author":"K Fukui","year":"2011","unstructured":"Fukui K, Akasaki S, Sato K, Mizusaki J, Moriyama K, Kurihara S, Numao M. Visualization of damage progress in solid oxide fuel cells. J Environ Eng. 2011;6(3):499\u2013511.","journal-title":"J Environ Eng"},{"issue":"1","key":"31_CR14","doi-asserted-by":"publisher","first-page":"131","DOI":"10.11239\/jsmbe.50.131","volume":"50","author":"H Fukumura","year":"2012","unstructured":"Fukumura H, Okada S, Makikawa M. Estimation of sleep stage using SVM from noncontact measurement of forehead and nasal skin temperature. BME. 2012;50(1):131\u20137. doi:\n                    10.11239\/jsmbe.50.131\n                    \n                  .","journal-title":"BME"},{"key":"31_CR15","doi-asserted-by":"crossref","unstructured":"Gu W, Yang Z, Shangguan L, Sun W, Jin K, Liu Y. Intelligent sleep stage mining service with smartphones. In: Proceedings of the 2014 ACM international joint conference on pervasive and ubiquitous computing. New York: ACM; 2014. p. 649\u201360.","DOI":"10.1145\/2632048.2632084"},{"key":"31_CR16","doi-asserted-by":"publisher","unstructured":"Hao T, Xing G, Zhou G. isleep: unobtrusive sleep quality monitoring using smartphones. In: Proceedings of the 11th ACM conference on embedded networked sensor systems (SenSys \u201913). New York: ACM; 2013. p. 4:1\u20134:14. doi:\n                    10.1145\/2517351.2517359\n                    \n                  .","DOI":"10.1145\/2517351.2517359"},{"issue":"9","key":"31_CR17","doi-asserted-by":"publisher","first-page":"1875","DOI":"10.1162\/0899766054322964","volume":"17","author":"S Haykin","year":"2005","unstructured":"Haykin S, Chen Z. The cocktail party problem. Neural Comput. 2005;17(9):1875\u2013902.","journal-title":"Neural Comput"},{"issue":"3","key":"31_CR18","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1111\/j.1469-8986.1987.tb00298.x","volume":"24","author":"CC Hoch","year":"1987","unstructured":"Hoch CC, Reynolds CF, Kupfer DJ, Berman SR, Houck PR, Stack JA. Empirical note: self-report versus recorded sleep in healthy seniors. Psychophysiology. 1987;24(3):293\u20139.","journal-title":"Psychophysiology"},{"issue":"4","key":"31_CR19","first-page":"478","volume":"149","author":"T Kato","year":"2011","unstructured":"Kato T, Masuda Y, Yoshida A, Morimoto T. Masseter emg activity during sleep and sleep bruxism. Arch Ital Biol. 2011;149(4):478\u201391.","journal-title":"Arch Ital Biol"},{"issue":"4","key":"31_CR20","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1023\/A:1024940629314","volume":"7","author":"J Kleinberg","year":"2003","unstructured":"Kleinberg J. Bursty and hierarchical structure in streams. Data Min Knowl Discov. 2003;7(4):373\u201397.","journal-title":"Data Min Knowl Discov"},{"issue":"1","key":"31_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/S0925-2312(98)00030-7","volume":"21","author":"T Kohonen","year":"1998","unstructured":"Kohonen T. The self-organizing map. Neurocomputing. 1998;21(1):1\u20136.","journal-title":"Neurocomputing"},{"key":"31_CR22","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.neunet.2012.09.018","volume":"37","author":"T Kohonen","year":"2013","unstructured":"Kohonen T. Essentials of the self-organizing map. Neural Netw. 2013;37:52\u201365.","journal-title":"Neural Netw"},{"issue":"3","key":"31_CR23","doi-asserted-by":"publisher","first-page":"574","DOI":"10.1109\/72.846729","volume":"11","author":"T Kohonen","year":"2000","unstructured":"Kohonen T, Kaski S, Lagus K, Saloj\u00e4rvi J, Honkela J, Paatero V, Saarela A. Self organization of a massive document collection. IEEE Trans Neural Netw. 2000;11(3):574\u201385.","journal-title":"IEEE Trans Neural Netw"},{"issue":"1","key":"31_CR24","doi-asserted-by":"publisher","first-page":"546","DOI":"10.1177\/00220345960750010601","volume":"75","author":"G Lavigne","year":"1996","unstructured":"Lavigne G, Rompre P, Montplaisir J. Sleep bruxism: validity of clinical research diagnostic criteria in a controlled polysomnographic study. J Dent Res. 1996;75(1):546\u201352.","journal-title":"J Dent Res"},{"issue":"2","key":"31_CR25","doi-asserted-by":"publisher","first-page":"517","DOI":"10.1109\/78.823977","volume":"48","author":"J Li","year":"2000","unstructured":"Li J, Najmi A, Gray RM. Image classification by a two-dimensional hidden Markov model. IEEE Trans Signal Process. 2000;48(2):517\u201333. doi:\n                    10.1109\/78.823977\n                    \n                  .","journal-title":"IEEE Trans Signal Process"},{"issue":"5","key":"31_CR26","doi-asserted-by":"publisher","first-page":"646","DOI":"10.3390\/s16050646","volume":"16","author":"J Mantua","year":"2016","unstructured":"Mantua J, Gravel N, Spencer R. Reliability of sleep measures from four personal health monitoring devices compared to research-based actigraphy and polysomnography. Sensors. 2016;16(5):646.","journal-title":"Sensors"},{"issue":"1","key":"31_CR27","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1007\/s00779-012-0623-1","volume":"18","author":"V Metsis","year":"2014","unstructured":"Metsis V, Kosmopoulos D, Athitsos V, Makedon F. Non-invasive analysis of sleep patterns via multimodal sensor input. Pers Ubiquitous Comput. 2014;18(1):19\u201326.","journal-title":"Pers Ubiquitous Comput"},{"key":"31_CR28","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.smrv.2015.01.009","volume":"25","author":"T Mollayeva","year":"2016","unstructured":"Mollayeva T, Thurairajah P, Burton K, Mollayeva S, Shapiro CM, Colantonio A. The pittsburgh sleep quality index as a screening tool for sleep dysfunction in clinical and non-clinical samples: a systematic review and meta-analysis. Sleep Med Rev. 2016;25:52\u201373.","journal-title":"Sleep medicine reviews"},{"issue":"1&2","key":"31_CR29","doi-asserted-by":"publisher","first-page":"27","DOI":"10.2978\/jsas.21.27","volume":"21","author":"T Noh","year":"2009","unstructured":"Noh T, Serizawa Y, Kimura T, Yamazaki K, Hayasaka Y, Itoh T, Izumi S, Sasaki T. The assessment of sleep stage utilizing body pressure fluctuation measured by water mat sensors. J Adv Sci. 2009;21(1&2):27\u201330.","journal-title":"J Adv Sci"},{"key":"31_CR30","volume-title":"Systemic homeostasis and poikilostasis in sleep: Is REM sleep a physiological paradox?","author":"PL Parmeggiani","year":"2011","unstructured":"Parmeggiani PL. Systemic homeostasis and poikilostasis in sleep: Is REM sleep a physiological paradox? Singapore: World Scientific; 2011."},{"issue":"2","key":"31_CR31","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1109\/5.18626","volume":"77","author":"LR Rabiner","year":"1989","unstructured":"Rabiner LR. A tutorial on hidden Markov models and selected applications in speech recognition. Proc IEEE. 1989;77(2):257\u201386.","journal-title":"Proc IEEE"},{"issue":"1","key":"31_CR32","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1037\/0882-7974.13.1.159","volume":"13","author":"B Riedel","year":"1998","unstructured":"Riedel B, Lichstein K. Objective sleep measures and subjective sleep satisfaction: how do older adults with insomnia define a good night\u2019s sleep? Psychol Aging. 1998;13(1):159\u201363. doi:\n                    10.1037\/\/0882-7974.13.1.159\n                    \n                  .","journal-title":"Psychol Aging"},{"key":"31_CR33","doi-asserted-by":"crossref","unstructured":"Rokach L, Maimon O. Clustering methods. In: Data mining and knowledge discovery handbook. Heidelberg: Springer; 2005. p. 321\u2013352.","DOI":"10.1007\/0-387-25465-X_15"},{"key":"31_CR34","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/0377-0427(87)90125-7","volume":"20","author":"PJ Rousseeuw","year":"1987","unstructured":"Rousseeuw PJ. Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J Comput Appl Math. 1987;20:53\u201365.","journal-title":"J Comput Appl Math"},{"key":"31_CR35","first-page":"147","volume":"7","author":"K Russo","year":"2015","unstructured":"Russo K, Goparaju B, Bianchi MT. Consumer sleep monitors: is there a baby in the bathwater? Nat Sci Sleep. 2015;7:147\u201357.","journal-title":"Nat Sci Sleep"},{"issue":"2","key":"31_CR36","doi-asserted-by":"crossref","first-page":"121","DOI":"10.5664\/jcsm.26814","volume":"3","author":"MH Silber","year":"2007","unstructured":"Silber MH, Ancoli-Israel S, Bonnet MH, Chokroverty S, Grigg-Damberger MM, Hirshkowitz M, Kapen S, Keenan SA, Kryger MH, Penzel T, et al. The visual scoring of sleep in adults. J Clin Sleep Med. 2007;3(2):121\u201331.","journal-title":"J Clin Sleep Med"},{"key":"31_CR37","first-page":"371","volume":"6","author":"O Simula","year":"1995","unstructured":"Simula O, Kangas J. Process monitoring and visualization using self-organizing maps. Neural Netw Chem Eng. 1995;6:371\u201384.","journal-title":"Neural Netw Chem Eng"},{"key":"31_CR38","first-page":"175","volume":"6","author":"EL Sonnhammer","year":"1998","unstructured":"Sonnhammer EL, Von Heijne G, Krogh A, et al. A hidden Markov model for predicting transmembrane helices in protein sequences. ISMB. 1998;6:175\u201382.","journal-title":"ISMB"},{"issue":"5","key":"31_CR39","doi-asserted-by":"publisher","first-page":"465","DOI":"10.1016\/j.jpsychores.2004.03.002","volume":"56","author":"H Tanaka","year":"2004","unstructured":"Tanaka H, Shirakawa S. Sleep health, lifestyle and mental health in the japanese elderly: ensuring sleep to promote a healthy brain and mind. J Psychosom Res. 2004;56(5):465\u201377.","journal-title":"J Psychosom Res"},{"issue":"3","key":"31_CR40","doi-asserted-by":"publisher","first-page":"586","DOI":"10.1109\/72.846731","volume":"11","author":"J Vesanto","year":"2000","unstructured":"Vesanto J, Alhoniemi E. Clustering of the self-organizing map. IEEE Trans Neural Netw. 2000;11(3):586\u2013600.","journal-title":"IEEE Trans Neural Netw"},{"key":"31_CR41","unstructured":"Wu H, Kato T, Yamada T, Numao M, Fukui K. Personal sleep pattern visualization via clustering on sound data. In: Proceedings of AAAI workshops at the 31st AAAI conference on artificial intelligence; 2017. p. 592\u20139."}],"container-title":["Health Information Science and Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13755-017-0031-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13755-017-0031-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13755-017-0031-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,16]],"date-time":"2020-05-16T23:04:22Z","timestamp":1589670262000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13755-017-0031-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10,30]]},"references-count":41,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2017,12]]}},"alternative-id":["31"],"URL":"https:\/\/doi.org\/10.1007\/s13755-017-0031-z","relation":{},"ISSN":["2047-2501"],"issn-type":[{"type":"electronic","value":"2047-2501"}],"subject":[],"published":{"date-parts":[[2017,10,30]]},"assertion":[{"value":"25 July 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 October 2017","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 October 2017","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"11"}}