Unobtrusive Movement Detection during Sleep based on Load Cell Dynamics
Resumo
Changes in the pattern of motor activities during sleep can be a disease marker, or can reflect various abnormal physiological and neurological conditions. Currently, there are no unobtrusive ways to assess the quality of sleep at point of care outside of a clinic. In this paper, we propose an alternative method of detecting movements during sleep that can be deployed unobtrusively in a patient’s own home by using load cells sensors. This subject-independent method uses a linear discriminant function to detect periods of movement in a cohort of 17 patients admitted to a sleep lab. The system yields a sensitivity of 97.5% and a specificity of 99% when compared to technicians’ annotations.Referências
Adami, A. M., Adami, A. G., Schwarz, G., Beattie, Z. T. and Hayes, T. L. (2010). A Subject State Detection Approach to Determine Rest-Activity Patterns Using Load Cells. In 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Buenos Aires, Argentina.
Austin, D., Beattie, Z. T., Riley, T., Adami, A. M., Hagen, C. C. and Hayes, T. L. (2012). Unobtrusive Classification of Sleep and Wakefulness Using Load Cells Under the Bed. In 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Diego, California, USA.
Beattie, Z. T., Hagen, C. C. and Hayes, T. L. (2011). Classification of lying position using load cells under the bed. In Engineering in Medicine and Biology Society,EMBC, 2011 Annual International Conference of the IEEE.
Beattie, Z. T., Hagen, C. C., Pavel, M. and Hayes, T. L. (2009). "Classification of Breathing Events Using Load Cells under the Bed". 31st Annual International Conference of the IEEE EMBS Minneapolis, Minnesota: 3921-3924.
Cheng, C. M., Hsu, Y.-L. and Young, C. M. (2008). Development of a Portable Device for Telemonitoring of Physical Activities During Sleep. Telemedicine and e-Health 14(10): 1044-1056.
Chokroverty, S., Hening, W. A. and Walters, A. S. (2003). Sleep and Movement Disorders. Philadelphia, PA, Elsevier Science.
Culebras, A. (2004). Who Should be Tested in the Sleep Laboratory? Reviews in Neurological Diseases 1(3): 124-132.
Duda, R. O., Hart, P. E. and Stork, D. G. (2001). Pattern Classification. New York, NY, John Wiley & Sons, Inc.
Fukunaga, K. (1990). Introduction to Statistical Pattern Recognition, Academic Press, 2nd ed.
Guimarães, G. M. N., Silva, H. B. G. d., Ladeira, M. and Viegas, C. A. d. A. (2006). "Aprendizagem de Classificadores para Diagnóstico da Síndrome da Apnéia Obstrutiva do Sono". VI Workshop de Informática Médica. Vila Velha, ES: 193-202.
Hyyppa, M. T. and Kronholm, E. (1987). Sleep Movements and Poor Sleep in Patients with Non-Specific Somatic Complaints II. Affective Disorders and Sleep Quality. Journal of Psychosomatic Research 31(5): 631-637.
Jones, M. H., Goubran, R. and Knoefel, F. (2006). "Identifying Movement Onset Times for a Bed-Based Pressure Sensor Array". International Workshop on Medical Measurement and Applications. Benevento, Italy: 111-114.
Muzet, A. (1986). Dynamics of Body Movements in Normal Sleep. In Eighth European Congress on Sleep Research, Szeged, Hungary, Gustav Fisher Verlag.
Phillips, B. (2004). Movement Disorders: A Sleep Specialist's Perspective. Neurology 62: S9-S16.
Shin, J. H., Chee, Y. J., Jeong, D. U. and Park, K. S. (2010). Nonconstrained Sleep Monitoring System and Algorithms Using Air-Matress with Balancing Tube Method. IEEE Transactions on Information Technology in Biomedicine 14(1): 147-156.
Tryon, W. W. (2004). Issues of Validity in Actigraphic Sleep Assessment. Sleep 27(1): 158-165.
Verhaert, V., Haex, B., De Wilde, T., Berckmans, D., Vandekerckhove, M., Verbraecken, J. and Sloten, J. V. (2011). Unobtrusive Assessment of Motor Patterns During Sleep Based on Mattress Indentation Measurements. Information Technology in Biomedicine, IEEE Transactions on 15(5): 787-794.
Watanabe, K., Watanabe, T., Watanabe, H., Ando, H., Ishikawa, T. and Kobayashi, K. (2005). Noninvasive Measurement of Heartbeat, Respiration, Snoring and Body Movements of a Subject in Bed Via a Pneumatic Method. IEEE Transactions on Biomedical Engineering 52(12): 2100-2107.
Austin, D., Beattie, Z. T., Riley, T., Adami, A. M., Hagen, C. C. and Hayes, T. L. (2012). Unobtrusive Classification of Sleep and Wakefulness Using Load Cells Under the Bed. In 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Diego, California, USA.
Beattie, Z. T., Hagen, C. C. and Hayes, T. L. (2011). Classification of lying position using load cells under the bed. In Engineering in Medicine and Biology Society,EMBC, 2011 Annual International Conference of the IEEE.
Beattie, Z. T., Hagen, C. C., Pavel, M. and Hayes, T. L. (2009). "Classification of Breathing Events Using Load Cells under the Bed". 31st Annual International Conference of the IEEE EMBS Minneapolis, Minnesota: 3921-3924.
Cheng, C. M., Hsu, Y.-L. and Young, C. M. (2008). Development of a Portable Device for Telemonitoring of Physical Activities During Sleep. Telemedicine and e-Health 14(10): 1044-1056.
Chokroverty, S., Hening, W. A. and Walters, A. S. (2003). Sleep and Movement Disorders. Philadelphia, PA, Elsevier Science.
Culebras, A. (2004). Who Should be Tested in the Sleep Laboratory? Reviews in Neurological Diseases 1(3): 124-132.
Duda, R. O., Hart, P. E. and Stork, D. G. (2001). Pattern Classification. New York, NY, John Wiley & Sons, Inc.
Fukunaga, K. (1990). Introduction to Statistical Pattern Recognition, Academic Press, 2nd ed.
Guimarães, G. M. N., Silva, H. B. G. d., Ladeira, M. and Viegas, C. A. d. A. (2006). "Aprendizagem de Classificadores para Diagnóstico da Síndrome da Apnéia Obstrutiva do Sono". VI Workshop de Informática Médica. Vila Velha, ES: 193-202.
Hyyppa, M. T. and Kronholm, E. (1987). Sleep Movements and Poor Sleep in Patients with Non-Specific Somatic Complaints II. Affective Disorders and Sleep Quality. Journal of Psychosomatic Research 31(5): 631-637.
Jones, M. H., Goubran, R. and Knoefel, F. (2006). "Identifying Movement Onset Times for a Bed-Based Pressure Sensor Array". International Workshop on Medical Measurement and Applications. Benevento, Italy: 111-114.
Muzet, A. (1986). Dynamics of Body Movements in Normal Sleep. In Eighth European Congress on Sleep Research, Szeged, Hungary, Gustav Fisher Verlag.
Phillips, B. (2004). Movement Disorders: A Sleep Specialist's Perspective. Neurology 62: S9-S16.
Shin, J. H., Chee, Y. J., Jeong, D. U. and Park, K. S. (2010). Nonconstrained Sleep Monitoring System and Algorithms Using Air-Matress with Balancing Tube Method. IEEE Transactions on Information Technology in Biomedicine 14(1): 147-156.
Tryon, W. W. (2004). Issues of Validity in Actigraphic Sleep Assessment. Sleep 27(1): 158-165.
Verhaert, V., Haex, B., De Wilde, T., Berckmans, D., Vandekerckhove, M., Verbraecken, J. and Sloten, J. V. (2011). Unobtrusive Assessment of Motor Patterns During Sleep Based on Mattress Indentation Measurements. Information Technology in Biomedicine, IEEE Transactions on 15(5): 787-794.
Watanabe, K., Watanabe, T., Watanabe, H., Ando, H., Ishikawa, T. and Kobayashi, K. (2005). Noninvasive Measurement of Heartbeat, Respiration, Snoring and Body Movements of a Subject in Bed Via a Pneumatic Method. IEEE Transactions on Biomedical Engineering 52(12): 2100-2107.
Publicado
23/07/2013
Como Citar
ADAMI, Adriana Miorelli; ADAMI, André Gustavo; HAYES, Tamara; BEATTIE, Zachary.
Unobtrusive Movement Detection during Sleep based on Load Cell Dynamics. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 13. , 2013, Maceió/AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2013
.
p. 1147-1155.
ISSN 2763-8952.
