Non-Invasive Device for Environmental Monitoring of the Sleep
Abstract
Sleep disorders are recurrent problems in society and have gained attention in recent years, especially when considering the changes imposed by Information and Communication Technologies (ICT) because they allow the de- velopment of solutions aimed at the evaluation of sleep. These disorders are usually associated with some clinical condition and usually the diagnosis is ob- tained through laboratory polysomnography, however, this is an expensive tech- nique and may be inconvenient to patients. Therefore, it is worth emphasizing the importance of the sleep environment in the context of the diagnosis, since the variables associated to it play an important role in sleep quality. In this sense, the article presents the development of a non-invasive and low-cost device for monitoring the sleep environment, designed under the Design Science Research Methodology, to aid in the treatment of sleep disorders.
References
Buxton, O. M. and Marcelli, E. (2010). Short and long sleep are positively associated with obesity, diabetes, hypertension, and cardiovascular disease among adults in the united states. Social science & medicine, 71(5):1027–1036. http://dx.doi.org/10.1016/j.socscimed.2010.05.041
de Menezes Duarte, R. L., da Silva, R. Z. M., and da Silveira, F. J. M. (2010). Métodos resumidos no diagnóstico da apnéia do sono. Pulmão RJ, 19(3-4):78–82.
Guimarães, G. M. (2010). Diagnóstico polissonográfico. Pulmão.(Rio de Janeiro), 9(3-4):88–92.
Jansen, J. M., Lopes, A. J., Jansen, U., Capone, D., Maeda, T. Y., Noronha, A., and Magalhães, G. (2007). Medicina da noite: da cronobiologia à prática clı́nica. SciELO- Editora FIOCRUZ.
Lee, J., Hong, M., and Ryu, S. (2015). Sleep monitoring system using kinect sensor. International Journal of Distributed Sensor Networks, 11(10):875371. http://dx.doi.org/10.1155/2015/875371
Lin, F., Zhuang, Y., Song, C., Wang, A., Li, Y., Gu, C., Li, C., and Xu, W. (2016). Sleep-Sense: A Noncontact and Cost-Effective Sleep Monitoring System. IEEE Transactions on Biomedical Circuits and Systems, 11(1):189–202. http://dx.doi.org/10.1109/TBCAS.2016.2541680
Lobato, F., Silva, B., Bem, R., and Miranda, D. (2015). Non-invasive sleep-environment monitoring system. In PETRA ’15: Proceedings of the 8th International Conference on PErvasive Technologies Related to Assistive Environments, Corfu, Greece. ACM. http://dx.doi.org/10.1145/2769493.2769563
Lobato, F. M. F., de Resende, D. C. O., do Nascimento, R. P., Siqueira, A. L. C., Jacob, A. F. L., and de Santana, Á. L. (2017). Multimodal Low-Invasive System for Sleep Quality Monitoring and Improvement. In Batalla, J. M., Mastorakis, G., Mavromoustakis, C. X., and Pallis, E., editors, Beyond the Internet of Things: Everything Interconnected, pages 223–242. Springer International Publishing, Cham. http://dx.doi.org/10.1007/978-3-319-50758-3_9
Müller, M. R. and Guimarães, S. S. (2007). Impacto dos transtornos do sono sobre o funcionamento diário e a qualidade de vida. Estudos de psicologia, 24(4):519–528.
Nam, Y., Kim, Y., and Lee, J. (2016). Sleep monitoring based on a tri-axial accelerometer and a pressure sensor. Sensors, 16(5):1–14. http://dx.doi.org/10.3390/s16050750
