Abstract
In recent years, because of the development of ubiquitous technology in health care, research is actively progress. We describe a sleeping situation monitoring system, created to support home healthcare services. We discuss the method we used to develop the system and how to use the sleep activity monitor to support home health care. Information about the sleeping situation is collected from motion detection, sound, and vibration sensors. And this information is based on real-time processing, we used the TMO (Time-trigger and Message-trigger Object) schema and TMOSM (TMO Support Middleware) into the development software environment of the healthcare application. To verify the practical use of sleeping situation information as recorded by the system discussed in this paper, we relate an example of the monitoring of a sleeping situation using our system, and we describe the results of an experimental evaluation.








Similar content being viewed by others
References
Biswas J, Jayachandran M, Shue L, Xiao W, Yap P (2007) An extensible system for sleep activity pattern monitoring. In: Proceedings of the ISSNIP 2007, Melbourne, Australia
World Health Organization (2004) WHO technical meeting on sleep and health. Report, World Health Organization
Nowack WJ Polysomnography: overview and clinical application. http://ww.medicine.com/neuro/topic566.htm
Tamura T (2011) Monitoring and evaluation of blood pressure changes with a home healthcare system. IEEE Trans Inf Technol Biomed 15(4):602–607
Gaddam A, Kaur K, Sen Gupta G, Mukhopadhyay SC Determination of sleep quality of inhabitant in a smart home using an intelligent bed sensing system. In: International Instrumentation and Measurement Technology Conference (12MTC), May 3–6, Austin, Texas, United States, pp 1613–1617
Shin JH, Chee YJ, Jeong D-U, Park KS (2010) Nonconstrained sleep monitoring system and algorithms using air-mattress with balancing tube method. IEEE Trans Inf Technol Biomed 14(1):147–156
Alexander GL, Rantz M, Skubic M, Koopman RJ, Phillips LJ, Guevara RD, Miller SJ (2011) Evolution of an early illness warning system to monitor frail elders in independent living. J Healthc Eng 2(2):259–286 (in press)
Scanaill et al (2006) Evaluation of an accelerometer-based mobility telemonitoring device in a smart home environment. In: Nugent C, Augusto JC (eds) Smart homes and beyond, IOS Press, 2006. Proceedings of ICOST 2006
Lotjonen J et al (2003) Automatic sleep-wake and nap analysis with a new wrist worn online activity monitoring device vivago wristcare. Sleep 26(1):86–90
Guilemaud R, Caritu Y, David D, Favre-Reguillon F, Fontaine D, Bonnet S (2004) Body motion capture for activity monitoring. In: Lymberis A, de Rossi D (eds) Wearable ehealth systems for personalised health management. IOS Press, Amsterdam, pp 286–291
Roussos G et al (2006) A blueprint for pervasive self-care infrastructures. In: IEEE international workshop on pervasive computing and communications workshop
Adami AM, Hayes TL, Pavel M (2003) Unobtrusive monitoring of sleep patterns. In: Proceedings of the 25th international conference of the IEEE engineering in medicien and biology society (EMBS), Cancum, Mexico, Sept 2003
Ohta S, Nakamoto H, Shinagawa Y, Tanikawa T (2002) A health monitoring system for elderly people living alone. J Telemed Telec 8(3):151–156
Shin C-S, Jeong C-W, Joo S-C (2004) Construction of distributed object group framework and its execution analysis using distributed application simulation. In: International conference EUC 2004, Aug 2004, pp 724–733
Jeong C-W, Kim D-H, Joo S-C (2007) Mobile collaboration framework for u-healthcare agent services and its application using PDAs. Lecture notes in computer science, vol 4496, pp 747–756, 31 May–1 June 2007
Jeong C-W, Shin C-S, Joo S-C (2008) Construction of mobile collaboration environment for ubiquitous computing and its application. JKSII 9(3):25–42
Joo S-C, Jeong C-W, Park S-J (2009) Context based dynamic security service for healthcare adaptive application in home environments. 2009 software technologies for future dependable distributed systems (STFSSD.2009.14) Tokyo, Japan, pp 220–224, 17 March 2009
Joo S-C, Jeong C-W, Kim KH (2010) A study of context-based adaptive service model in home environments. In: WCC 2010, FTRA world convergence conference, Gwangju, Korea, pp 95–104, 9–11 Dec 2010
Kim KH, Ishida M, Liu J (1999) An efficient middleware architecture supporting time- triggered message-triggered objects and an NT-based implementation. In: Proceedings of the IEEE CS 2nd international symposium on object-oriented real-time distributed computing (ISORC’99), pp 54–63
Tseng BL, Lin C-Y, Naphade M, Natsev A, Smith JR (2003) Normalized classifier fusion for semantic visual concept detection. In: Proceedings of the international conference on image processing, Sept 2003
Acknowledgments
This paper was supported by Wonkwang university in 2012.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Jeong, CW., Joo, SC. & Jeong, Y.S. Sleeping situation monitoring system in ubiquitous environments. Pers Ubiquit Comput 17, 1357–1364 (2013). https://doi.org/10.1007/s00779-012-0570-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00779-012-0570-x