Skip to main content

A Sleep Monitoring Application for u-lifecare Using Accelerometer Sensor of Smartphone

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8276))

Abstract

Ubiquitous lifecare (u-lifecare) is regarded as a seamless technology that can provide services to the patients as well as facilitate the healthy people to maintain an active lifestyle. In this paper, we develop a sleep monitoring application to assists the healthy people for managing their sleep. It provides an unobtrusive and proactive way for the self-management. We utilize the embedded accelerometer sensor of the smartphone as a client node to collect the sleeping data logs. Our proposed model is server-driven approach and process the data over the server machine. We classify the body movements and compute the useful sleep analytics. It facilitates the users to keep the record of daily sleep and assists to change their unhealthy sleeping habits that are identified by our computed sleep analytics such as bed time, wake up, fell asleep, body movements, frequent body movements at different stages of the night, sleep efficiency and time spent in the bed. Furthermore, we also provide our pilot study results to demonstrate the applicability with the real-world service scenarios.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Jeong, C., Joo, S.-C., Jeong, Y.S.: Sleeping situation monitoring system in ubiquitous environments. Journal of Personal and Ubiquitous Computing, 1–8 (2012)

    Google Scholar 

  2. Khai, L.Q., Khoa, T.Q.D., Toi, V.V.: A tool for analysis and classification of sleep stages. In: International Conference on Advanced Technologies for Communications, pp. 307–310 (2011)

    Google Scholar 

  3. Gironda, R.J., Lloyd, J., Clark, M.E., Walker, R.L.: Preliminary Evaluation of the Reliability and Criterion Validity of the Actiwatch-Score. Journal of Rehabilitation Research & Development, 223–230 (2007)

    Google Scholar 

  4. Sleep Diary, http://sleep.buffalo.edu/sleepdiary.pdf (last visited: June 10, 2013)

  5. Le, H.X., Lee, S., Truc, P., Vinh, L.T., Khattak, A.M., Han, M., Hung, V.D., Hassan, M.M., Kim, M., Koo, H.K., Lee, K.Y., Huh, E.N.: Secured WSN-integrated cloud computing for u-life care. In: 7th IEEE Consumer Communications and Networking Conference, pp. 1–2 (2010)

    Google Scholar 

  6. Adriana, M.A., Pavel, M., Tamara, L.H., Clifford, M.S.: Detection of Movement in Bed Using Unobtrusive Load Cell Sensors. IEEE Transactions on Information Technology in Biomedicine 14(2), 481–490 (2010)

    Article  Google Scholar 

  7. Wakemate, http://wakemate.com/ (last visited: June 10, 2013)

  8. Sleep Cycle, http://www.sleepcycle.com/ (last visited: June 10, 2013)

  9. Sleep as android, https://sites.google.com/site/sleepasandroid/ (last visited: June 10, 2013)

  10. Sleep by MotionX, http://sleep.motionx.com/ (last visited: June 10, 2013)

  11. Sleepbot, http://mysleepbot.com/ (last visited: June 10, 2013)

  12. Mizell, D.: Using gravity to estimate accelerometer orientation. In: Proceeding of the IEEE International Symposiumon Wearable Computers, Computer Society, pp. 252–253 (2003)

    Google Scholar 

  13. Scholkopf, B.: Advances in Kernel Methods: Support Vector Learning. MIT Press (1999) ISSBN: 9780585128290

    Google Scholar 

  14. Breus, M.J.: Calculating Your Perfect Bedtime and Sleep Efficiency, http://blog.doctoroz.com/oz-experts/calculating-your-perfect-bedtime-and-sleep-efficiency (last visited: June 10, 2013)

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer International Publishing Switzerland

About this paper

Cite this paper

Fahim, M., Vui, L.B., Fatima, I., Lee, S., Yoon, Y. (2013). A Sleep Monitoring Application for u-lifecare Using Accelerometer Sensor of Smartphone. In: Urzaiz, G., Ochoa, S.F., Bravo, J., Chen, L.L., Oliveira, J. (eds) Ubiquitous Computing and Ambient Intelligence. Context-Awareness and Context-Driven Interaction. Lecture Notes in Computer Science, vol 8276. Springer, Cham. https://doi.org/10.1007/978-3-319-03176-7_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-03176-7_20

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03175-0

  • Online ISBN: 978-3-319-03176-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics