SLEEPIC - Developments for a Wearable On-line Sleep and Wake Discrimination System

Walter Karlen, Dario Floreano

2011

Abstract

The design of wearable systems comes with constraints in computational and power resources. We describe the development of customized hardware for the wearable discrimination of human sleep and wake based on cardio-respiratory signals. The device was designed for efficient and low-power computation of Fast Fourier Transforms and artificial neural networks required for the on-line classification. We discuss methods for reducing computational load and consequently power requirements. The SleePic prototype was tested for autonomy and comfort on eight healthy subjects. SleePic showed an energetic autonomy of more than 36 hours. The SleePic device will require further integration for increased comfort and improved user interaction.

References

  1. Colten, H. and Altevogt, B. (2006). Sleep disorders and sleep deprivation: an unmet public health problem. National Academies Press, Washington, DC.
  2. de Souza, L., Benedito-Silva, A., Pires, M., Poyares, D., Tufik, S., and Calil, H. (2003). Further validation of actigraphy for sleep studies. Sleep, 26(1):81-5.
  3. Karlen, W., Mattiussi, C., and Floreano, D. (2008). Improving actigraph sleep/wake classification with cardiorespiratory signals. In Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pages 5262-5.
  4. Karlen, W., Mattiussi, C., and Floreano, D. (2009). Sleep and Wake Classification With ECG and Respiratory Effort Signals. IEEE Transactions on Biomedical Circuits and Systems, 3(2):71-8.
  5. Martin, T., Jovanov, E., and Raskovic, D. (2000). Issues in Wearable Computing for Medical Monitoring Applications: A Case Study of a Wearable ECG Monitoring Device. International Symposium on Wearable Computers ISWC 2000, Atlanta, October.
  6. Ogilvie, R. (2001). The process of falling asleep. Sleep Medicine Reviews, 5(3):247-70.
  7. Patel, M. R. and Davidson, T. M. (2007). Home sleep testing in the diagnosis and treatment of sleep disordered breathing. Otolaryngologic Clinics of North America, 40(4):761-784.
  8. Sadeh, A. (2002). The role of actigraphy in sleep medicine. Sleep Medicine Reviews, 6(2):113-124.
  9. Scheffler, M. and Hirt, E. (2004). Wearable devices for emerging healthcare applications. In Proc. 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEMBS 7804, volume 2, pages 3301-3304.
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Paper Citation


in Harvard Style

Karlen W. and Floreano D. (2011). SLEEPIC - Developments for a Wearable On-line Sleep and Wake Discrimination System . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011) ISBN 978-989-8425-35-5, pages 132-137. DOI: 10.5220/0003131701320137


in Bibtex Style

@conference{biosignals11,
author={Walter Karlen and Dario Floreano},
title={SLEEPIC - Developments for a Wearable On-line Sleep and Wake Discrimination System},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011)},
year={2011},
pages={132-137},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003131701320137},
isbn={978-989-8425-35-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011)
TI - SLEEPIC - Developments for a Wearable On-line Sleep and Wake Discrimination System
SN - 978-989-8425-35-5
AU - Karlen W.
AU - Floreano D.
PY - 2011
SP - 132
EP - 137
DO - 10.5220/0003131701320137