{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T14:59:52Z","timestamp":1781103592360,"version":"3.54.1"},"reference-count":20,"publisher":"IGI Global Scientific Publishing","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,10,1]]},"abstract":"<p>The authors introduce an algorithmic framework to process real-time physiological data using nonparametric Bayesian models under the context of developing and testing personalized wellness monitors. A wearable device aggregates signals from various sensors while periodically transmitting the collected data to a backend server, which builds custom user profiles based on inferred hidden Markov states. They discuss how these user profiles can be used in various contexts as proxies for fluctuating physiological states and leveraged for various longitudinal classification tasks. Using data collected in a two-week study hosted at Jaslok Hospital, the authors show how physiological changes induced by different environments with various levels of stress can be quantified by the authors' platform. To minimize the dependence on continuous connectivity with the backend server, they introduce a heuristic to enable real-time state identification using the modest processing capabilities of the wearable device.<\/p>","DOI":"10.4018\/ijehmc.2014100101","type":"journal-article","created":{"date-parts":[[2015,2,27]],"date-time":"2015-02-27T08:02:20Z","timestamp":1425024140000},"page":"1-19","source":"Crossref","is-referenced-by-count":5,"title":["Personalized Monitors for Real-Time Detection of Physiological States"],"prefix":"10.4018","volume":"5","author":[{"given":"Lawrence","family":"Chow","sequence":"first","affiliation":[{"name":"Stanford University, Standford, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicholas","family":"Bambos","sequence":"additional","affiliation":[{"name":"Stanford University, Standford, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alex","family":"Gilman","sequence":"additional","affiliation":[{"name":"Fujitsu Laboratories of America, Sunnyvale, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ajay","family":"Chander","sequence":"additional","affiliation":[{"name":"Fujitsu Laboratories of America, Sunnyvale, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"ijehmc.2014100101-0","first-page":"457","author":"E. B.Fox","year":"2008","journal-title":"Nonparametric Bayesian Learning of Switching Linear Dynamical Systems"},{"key":"ijehmc.2014100101-1","first-page":"549","author":"E. B.Fox","year":"2009","journal-title":"Sharing Features among Dynamical Systems with Beta Processes"},{"issue":"2","key":"ijehmc.2014100101-2","first-page":"156","article-title":"Detecting stress during real-world driving tasks using physiological sensors. Intelligent Transportation Systems","volume":"6","author":"J. A.Healey","year":"2005","journal-title":"IEEE Transactions on"},{"key":"ijehmc.2014100101-3","doi-asserted-by":"publisher","DOI":"10.1007\/s00421-004-1055-z"},{"issue":"4","key":"ijehmc.2014100101-4","first-page":"1052","article-title":"Real-time nonintrusive monitoring and prediction of driver fatigue. Vehicular Technology","volume":"53","author":"Q.Ji","year":"2004","journal-title":"IEEE Transactions on"},{"issue":"4","key":"ijehmc.2014100101-5","first-page":"647","article-title":"RTWPMS: A real-time wireless physiological monitoring system. Information Technology in Biomedicine","volume":"10","author":"B. S.Lin","year":"2006","journal-title":"IEEE Transactions on"},{"key":"ijehmc.2014100101-6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2007.08.012"},{"key":"ijehmc.2014100101-7","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.eurheartj.a014868"},{"key":"ijehmc.2014100101-8","doi-asserted-by":"publisher","DOI":"10.1109\/BSN.2006.27"},{"key":"ijehmc.2014100101-9","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2007.11.002"},{"key":"ijehmc.2014100101-10","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijcard.2003.02.006"},{"issue":"3","key":"ijehmc.2014100101-11","doi-asserted-by":"crossref","first-page":"1081","DOI":"10.1152\/jappl.1999.86.3.1081","article-title":"Wavelet transform to quantify heart rate variability and to assess its instantaneous changes.","volume":"86","author":"V.Pichot","year":"1999","journal-title":"Journal of Applied Physiology"},{"issue":"1","key":"ijehmc.2014100101-12","doi-asserted-by":"crossref","first-page":"H151","DOI":"10.1152\/ajpheart.1985.248.1.H151","article-title":"Assessment of autonomic function in humans by heart rate spectral analysis.","volume":"248","author":"B.Pomeranz","year":"1985","journal-title":"American Journal of Physiology. Heart and Circulatory Physiology"},{"key":"ijehmc.2014100101-13","unstructured":"Saria, S., Koller, D., & Penn, A. (2010). Discovering shared and individual latent structure in multiple time series. arXiv preprint arXiv:1008.2028."},{"key":"ijehmc.2014100101-14","doi-asserted-by":"publisher","DOI":"10.1109\/ISWC.2007.4373774"},{"key":"ijehmc.2014100101-15","author":"Y. W.Teh","year":"2004","journal-title":"Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes"},{"key":"ijehmc.2014100101-16","first-page":"564","article-title":"Hierarchical beta processes and the Indian buffet process.","author":"R.Thibaux","year":"2007","journal-title":"International conference on artificial intelligence and statistics"},{"key":"ijehmc.2014100101-17","doi-asserted-by":"publisher","DOI":"10.3414\/ME9115"},{"key":"ijehmc.2014100101-18","doi-asserted-by":"publisher","DOI":"10.1161\/01.HYP.35.4.880"},{"key":"ijehmc.2014100101-19","doi-asserted-by":"publisher","DOI":"10.1109\/IEMBS.2005.1617049"}],"container-title":["International Journal of E-Health and Medical Communications"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=124284","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T15:59:06Z","timestamp":1654099146000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/ijehmc.2014100101"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2014,10,1]]},"references-count":20,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2014,10]]}},"URL":"https:\/\/doi.org\/10.4018\/ijehmc.2014100101","relation":{},"ISSN":["1947-315X","1947-3168"],"issn-type":[{"value":"1947-315X","type":"print"},{"value":"1947-3168","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,10,1]]}}}