{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:36:43Z","timestamp":1760243803977,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2022,9,20]],"date-time":"2022-09-20T00:00:00Z","timestamp":1663632000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>Good sleep quality is essential in human life due to its impact on health. Currently, technology has focused on providing specific features for quality sleep monitoring in people. This work represents a contribution to state of the art on non-invasive technologies that can help improve the quality of people\u2019s sleep at a low cost. We reviewed the sleep quality of a group of people by analyzing their good and bad sleeping habits. We take that information to feed a proposed algorithm for a non-invasive sensor network in the person\u2019s room for monitoring factors that help them fall asleep. We analyze vital signs and health conditions in order to be able to relate these parameters to the person\u2019s way of sleeping. We help people get valuable information about their sleep with technology to live a healthy life, and we get about a 15% improvement in sleep quality. Finally, we compare the implementations given by the network with wearables to show the improvement in the behavior of the person\u2019s sleep.<\/jats:p>","DOI":"10.3390\/fi14100270","type":"journal-article","created":{"date-parts":[[2022,9,20]],"date-time":"2022-09-20T21:12:53Z","timestamp":1663708373000},"page":"270","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Analysis and Correlation between a Non-Invasive Sensor Network System in the Room and the Improvement of Sleep Quality"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7104-1377","authenticated-orcid":false,"given":"Eduardo","family":"Morales-Vizcarra","sequence":"first","affiliation":[{"name":"Facultad de Ingenier\u00eda, Universidad Panamericana, \u00c1lvaro del Portillo 49, Zapopan 45010, Jalisco, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0272-3275","authenticated-orcid":false,"given":"Carolina","family":"Del-Valle-Soto","sequence":"additional","affiliation":[{"name":"Facultad de Ingenier\u00eda, Universidad Panamericana, \u00c1lvaro del Portillo 49, Zapopan 45010, Jalisco, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4058-4042","authenticated-orcid":false,"given":"Paolo","family":"Visconti","sequence":"additional","affiliation":[{"name":"Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5701-1347","authenticated-orcid":false,"given":"Fabiola","family":"Cortes-Chavez","sequence":"additional","affiliation":[{"name":"Facultad de Ingenier\u00eda, Universidad Panamericana, \u00c1lvaro del Portillo 49, Zapopan 45010, Jalisco, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"24818","DOI":"10.3390\/s151024818","article-title":"A survey on energy conserving mechanisms for the internet of things: Wireless networking aspects","volume":"15","author":"Abbas","year":"2015","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Ayaida, M., Messai, N., Valentin, F., and Marcheras, D. (2022). TalkRoBots: A Middleware for Robotic Systems in Industry 4.0. Future Internet, 14.","DOI":"10.3390\/fi14040109"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"100342","DOI":"10.1016\/j.iot.2020.100342","article-title":"Future smart connected communities to fight covid-19 outbreak","volume":"13","author":"Gupta","year":"2021","journal-title":"Internet Things"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.mser.2017.02.001","article-title":"Recent advances in wearable tactile sensors: Materials, sensing mechanisms, and device performance","volume":"115","author":"Yang","year":"2017","journal-title":"Mater. Sci. Eng. R Rep."},{"key":"ref_5","first-page":"1","article-title":"Wearable sensors for monitoring the internal and external workload of the athlete","volume":"2","author":"Seshadri","year":"2019","journal-title":"NPJ Digit. Med."},{"key":"ref_6","unstructured":"Freedheim, D.K., and Weiner, I.B. (2021). Handbook of Psychology, John Wiley & Sons, Inc."},{"key":"ref_7","first-page":"126","article-title":"Overview of sleep & sleep disorders","volume":"131","author":"Chokroverty","year":"2010","journal-title":"Indian J. Med. Res."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"e12861","DOI":"10.2196\/12861","article-title":"Wearable health technology and electronic health record integration: Scoping review and future directions","volume":"7","author":"Chuang","year":"2019","journal-title":"JMIR MHealth UHealth"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1038\/s41591-020-1123-x","article-title":"Wearable sensor data and self-reported symptoms for COVID-19 detection","volume":"27","author":"Quer","year":"2021","journal-title":"Nat. Med."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1177\/1367549415584857","article-title":"Our metrics, ourselves: A hundred years of self-tracking from the weight scale to the wrist wearable device","volume":"18","author":"Crawford","year":"2015","journal-title":"Eur. J. Cult. Stud."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1002\/cpt.1077","article-title":"Brain monitoring devices in neuroscience clinical research: The potential of remote monitoring using sensors, wearables, and mobile devices","volume":"104","author":"Byrom","year":"2018","journal-title":"Clin. Pharmacol. Ther."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1007\/s12668-013-0089-2","article-title":"Towards measuring stress with smartphones and wearable devices during workday and sleep","volume":"3","author":"Muaremi","year":"2013","journal-title":"BioNanoScience"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1159\/000504838","article-title":"Usability of a wrist-worn smartwatch in a direct-to-participant randomized pragmatic clinical trial","volume":"3","author":"Galarnyk","year":"2019","journal-title":"Digit. Biomark."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"De Fazio, R., Mattei, V., Al-Naami, B., De Vittorio, M., and Visconti, P. (2022). Methodologies and Wearable Devices to Monitor Biophysical Parameters Related to Sleep Dysfunctions: An Overview. Micromachines, 13.","DOI":"10.3390\/mi13081335"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"189","DOI":"10.21103\/Article10(3)_RA2","article-title":"Activity trackers, wearables, noninvasive technologies for early detection, and management of cardiometabolic risks","volume":"10","author":"Tate","year":"2020","journal-title":"Int. J. Biomed."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1093\/sleep\/23.2.1k","article-title":"Practice parameters for the evaluation of chronic insomnia","volume":"23","author":"Chesson","year":"2000","journal-title":"Sleep"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Bruyneel, M. (2019). Telemedicine in the diagnosis and treatment of sleep apnoea. Eur. Respir. Rev., 28.","DOI":"10.1183\/16000617.0093-2018"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"e12789","DOI":"10.1111\/jsr.12789","article-title":"Ability of the Fitbit Alta HR to quantify and classify sleep in patients with suspected central disorders of hypersomnolence: A comparison against polysomnography","volume":"28","author":"Cook","year":"2019","journal-title":"J. Sleep Res."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Kurt Peker, Y., Bello, G., and Perez, A.J. (2022). On the Security of Bluetooth Low Energy in Two Consumer Wearable Heart Rate Monitors\/Sensing Devices. Sensors, 22.","DOI":"10.3390\/s22030988"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1023\/A:1024444917917","article-title":"Development of sensate and robotic bed technologies for vital signs monitoring and sleep quality improvement","volume":"15","author":"Machiel","year":"2003","journal-title":"Auton. Robot."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"969","DOI":"10.1037\/bul0000053","article-title":"Sleep and mental disorders: A meta-analysis of polysomnographic research","volume":"142","author":"Baglioni","year":"2016","journal-title":"Psychol. Bull."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/j.sleep.2005.02.002","article-title":"Actigraphic recordings in quantification of periodic leg movements during sleep in children","volume":"6","author":"Crabtree","year":"2005","journal-title":"Sleep Med."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.jad.2017.04.030","article-title":"Utility of the Fitbit Flex to evaluate sleep in major depressive disorder: A comparison against polysomnography and wrist-worn actigraphy","volume":"217","author":"Cook","year":"2017","journal-title":"J. Affect. Disord."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"83","DOI":"10.4258\/hir.2020.26.2.83","article-title":"Quantified self-using consumer wearable device: Predicting physical and mental health","volume":"26","author":"Pardamean","year":"2020","journal-title":"Healthc. Inform. Res."},{"key":"ref_25","first-page":"1","article-title":"Detecting sleep outside the clinic using wearable heart rate devices","volume":"12","author":"Posa","year":"2022","journal-title":"Sci. Rep."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"103702","DOI":"10.1016\/j.bspc.2022.103702","article-title":"Design and implementation of a hybrid FLC+ PID controller for pressure control of sleep devices","volume":"76","author":"Golcuk","year":"2022","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"108835","DOI":"10.1016\/j.buildenv.2022.108835","article-title":"Data fusion of mobile and environmental sensing devices to understand the effect of the indoor environment on measured and self-reported sleep quality","volume":"214","author":"Fritz","year":"2022","journal-title":"Build. Environ."},{"key":"ref_28","first-page":"768794","article-title":"Recent developments in home sleep-monitoring devices","volume":"2012","author":"Kelly","year":"2012","journal-title":"Int. Sch. Res. Not."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"985","DOI":"10.1007\/s00779-016-0960-6","article-title":"SleepExplorer: A visualization tool to make sense of correlations between personal sleep data and contextual factors","volume":"20","author":"Liang","year":"2016","journal-title":"Pers. Ubiquitous Comput."},{"key":"ref_30","unstructured":"Lawson, S., Jamison-Powell, S., Garbett, A., Linehan, C., Kucharczyk, E., Verbaan, S., Rowland, D.A., and Morgan, K. (May, January 27). Validating a mobile phone application for the everyday, unobtrusive, objective measurement of sleep. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Paris, France."},{"key":"ref_31","unstructured":"Min, J.K., Doryab, A., Wiese, J., Amini, S., Zimmerman, J., and Hong, J.I. (May, January 26). Toss\u2019n\u2019turn: Smartphone as sleep and sleep quality detector. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Toronto, ON, USA."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Kay, M., Choe, E.K., Shepherd, J., Greenstein, B., Watson, N., Consolvo, S., and Kientz, J.A. (2012, January 5\u20138). Lullaby: A capture & access system for understanding the sleep environment. Proceedings of the 2012 ACM Conference on Ubiquitous Computing, Pittsburgh, PA, USA.","DOI":"10.1145\/2370216.2370253"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Hao, T., Xing, G., and Zhou, G. (2013, January 11\u201315). isleep: Unobtrusive sleep quality monitoring using smartphones. Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems, Roma, Italy.","DOI":"10.1145\/2517351.2517359"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Chen, Z., Lin, M., Chen, F., Lane, N.D., Cardone, G., Wang, R., Li, T., Chen, Y., Choudhury, T., and Campbell, A.T. (2013, January 5\u20138). Unobtrusive sleep monitoring using smartphones. Proceedings of the 2013 7th International Conference on Pervasive Computing Technologies for Healthcare and Workshops, Venice, Italy.","DOI":"10.4108\/icst.pervasivehealth.2013.252148"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Liu, X., Cao, J., Tang, S., and Wen, J. (2014, January 2\u20135). Wi-sleep: Contactless sleep monitoring via wifi signals. Proceedings of the 2014 IEEE Real-Time Systems Symposium, Rome, Italy.","DOI":"10.1109\/RTSS.2014.30"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1109\/TBCAS.2016.2541680","article-title":"SleepSense: A noncontact and cost-effective sleep monitoring system","volume":"11","author":"Lin","year":"2016","journal-title":"IEEE Trans. Biomed. Circuits Syst."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"517","DOI":"10.5664\/jcsm.6514","article-title":"Validation of contact-free sleep monitoring device with comparison to polysomnography","volume":"13","author":"Tal","year":"2017","journal-title":"J. Clin. Sleep Med."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"483","DOI":"10.5664\/jcsm.7682","article-title":"Sleep parameter assessment accuracy of a consumer home sleep monitoring ballistocardiograph beddit sleep tracker: A validation study","volume":"15","author":"Tuominen","year":"2019","journal-title":"J. Clin. Sleep Med."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Ren, Y., Wang, C., Yang, J., and Chen, Y. (May, January 26). Fine-grained sleep monitoring: Hearing your breathing with smartphones. Proceedings of the 2015 IEEE Conference on Computer Communications (INFOCOM), Hong Kong, China.","DOI":"10.1109\/INFOCOM.2015.7218494"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3051124","article-title":"Vital sign and sleep monitoring using millimeter wave","volume":"13","author":"Yang","year":"2017","journal-title":"ACM Trans. Sens. Networks (TOSN)"},{"key":"ref_41","unstructured":"Ana Mar\u00eda Concha Villarroel, A.M., L\u00f3pez Guti\u00e9rrez, M.C., Palma Fuentes, J., Pezoa Reyes, R., and Riveros Far\u00edas, C. (2018). Gu\u00eda para la Clasificaci\u00f3n de Dispositivos M\u00e9dicos Seg\u00fan Riesgo, Instituto de Salud P\u00fablica."}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/14\/10\/270\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:34:50Z","timestamp":1760142890000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/14\/10\/270"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,20]]},"references-count":41,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["fi14100270"],"URL":"https:\/\/doi.org\/10.3390\/fi14100270","relation":{},"ISSN":["1999-5903"],"issn-type":[{"type":"electronic","value":"1999-5903"}],"subject":[],"published":{"date-parts":[[2022,9,20]]}}}