Abstract
This research is concerned with analyzing a real world problem: the detection of a sleep disorder called Obstructive Apnea Hypopnea Syndrome. The sleep apnea affects a significant number of adults, but children are affected as well. This study is focused on finding the apnea patterns using a well known time series representation method and several distance measures. In this preliminary work, the aim is twofold: on one hand, finding the most relevant features that characterize the apnea episodes; on the other hand, choosing the most promising distance measurements among patterns. The experiments were carried out at the Hospital Universitario de Burgos’s Sleep Laboratory with real subjects and with technicians monitoring the Conventional Polysomnography.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Alonso Álvarez, M.L., Terán Santos, J., Cordero Guevara, J., González Martínez, M., Rodríguez Pascual, L., Viejo Bañuelos, J.L., Marañón Cabello, A.: Fiabilidad de la poligrafía respiratoria domiciliaria para el diagnóstico del síndrome de apneas/hipopneas durante el sueño. análisis de costes. Arch. Bronconeumol. 44(1), 22–28 (2008)
Alonso Álvarez, M.L., Canet, T., Cubel Alarco, M., Estivill, E., Fernandez Julian, E., Gozal, D., Jurado Luqué, M.J., Lluch Roselló, A., Martínez Pérez, F., Merino-Andreu, M., Pin-Arboledas, G., Roure, N., Sanmartí, F., Sans Capdevila, O., Segarra Isern, F., Tomás Vila, M., Terán Santos, J.: Documento de consenso del síndrome de apneas-hipopneas durante el sueño en niños. Archivos de Bronconeumología 47(5), 1–18 (2011)
Somers, V.K., White, D.P., Amin, R., Abraham, W.T., Costa, F., Culebras, A., Daniels, S., Floras, J.S., Hunt, C.E., Olson, L.J., Pickering, T.G., Russell, R., Woo, M., Young, T.: Sleep apnea and cardiovascular diseasean american heart association/american college of cardiology foundation scientific statement from the american heart association council for high blood pressure research professional education committee, council on clinical cardiology, stroke council, and council on cardiovascular nursing in collaboration with the national heart, lung, and blood institute national center on sleep disorders research (national institutes of health). Journal of the American College of Cardiology 52, 686–717 (2008)
Kushida, C.A., Littner, M.R., Morgenthaler, T., Alessi, C.A., Bailey, D., Coleman, J.J., Friedman, L., Hirshkowitz, M., Kapen, S., Kramer, M., Lee-Chiong, T., Loube, D.L., Owens, J., Pancer, J.P., Wise, M.: Practice parameters for the indications for polysomnography and related procedures: an update for 2005, 28, 499–521 (2005)
Lloberes, P., Durán-Cantolla, J., Martínez-García, M.Á., Marín, J.M., Jaime Corralf, A., Masa, J.F., Parra, O., Alonso-Álvarez, M.L., Santos., J.T.: Normativa sobre diagnóstico y tratamiento del síndrome de apneas-hipopneas del sueño 47(3), 143–156 (2011)
Berry, R., Brooks, R., Gamaldo, C., Harding, S., Marcus, C., Vaughn, B., Tangredi, M.: The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specification. American Academy of Sleep Medicine, Darien (2012)
Banos, O., Damas, M., Pomares, H., Prieto, A., Rojas, I.: Daily living activity recognition based on statistical feature quality group selection. Expert Systems with Applications 39(9), 8013–8021 (2012)
Martiskainen, P., Järvinen, M., Skön, J.P., Tiirikainen, J., Kolehmainen, M., Mononen, J.: Cow behaviour pattern recognition using a three-dimensional accelerometer and support vector machines. Applied Animal Behaviour Science 119(1-2), 32–38 (2009)
Fuentes, D., Gonzalez-Abril, L., Angulo, C., Ortega, J.A.: Online motion recognition using an accelerometer in a mobile device. Expert Systems with Applications 39(3), 2461–2465 (2012)
Wang, J., Chen, R., Sun, X., She, M.F.H., Wu, Y.: Recognizing human daily activities from accelerometer signal. Procedia Engineering 15, 1780–1786 (2011)
Chen, Y.P., Yang, J.Y., Liou, S.N., Lee, G.Y., Wang, J.S.: Online classifier construction algorithm for human activity detection using a tri-axial accelerometer. Applied Mathematics and Computation 205(2), 849–860 (2008)
Ávarez-Álvarez, A., Triviño, G., Cordón, O.: Body posture recognition by means of a genetic fuzzy finite state machine. In: IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS), pp. 60–65 (2011)
González, S., Villar, J.R., Sedano, J., Chira, C.: A preliminary study on early diagnosis of illnesses based on activity disturbances. In: Omatu, S., Neves, J., Rodriguez, J.M.C., Paz Santana, J.F., Gonzalez, S.R. (eds.) Distrib. Computing & Artificial Intelligence. AISC, vol. 217, pp. 521–527. Springer, Heidelberg (2013)
Villar, J.R., González, S., Sedano, J., Chira, C., Trejo, J.M.: Early diagnosis of stroke: bridging the gap through wearable sensors and computational models. In: Proceedings of the 9th International Conference on Applied Mathematics (2013)
Sedano, J., González, S., Baruque, B., Herrero, Á., Corchado, E.: Soft computing for the analysis of people movement classification. In: Snasel, V., Abraham, A., Corchado, E.S. (eds.) SOCO Models in Industrial & Environmental Appl. AISC, vol. 188, pp. 241–248. Springer, Heidelberg (2013)
Villar, J.R., González, S., Sedano, J., Chira, C., Trejo, J.M.: Human activity recognition and feature selection for stroke early diagnosis. In: Pan, J.-S., Polycarpou, M.M., Woźniak, M., de Carvalho, A.C.P.L.F., Quintián, H., Corchado, E. (eds.) HAIS 2013. LNCS, vol. 8073, pp. 659–668. Springer, Heidelberg (2013)
Sedano, J., Chira, C., Gonzalez, J., Villar, J.R.: Intelligent system to measuring stress: Stresstic. DYNA 87-3, 336–344 (2012)
Hausdorff, J.M., Schaafsma, J.D., Balash, Y., Bartels, A.L., Gurevich, T., Giladi, N.: Impaired regulation of stride variability in parkinson’s disease subjects with freezing of gait 149, 187–194 (2003)
Shoeb, A., Edwards, H., Connolly, J., Bourgeois, B., Treves, S.T., Guttag, J.: Patient-specific seizure onset detection. Epilepsy & Behavior 5(4), 483–498 (2004)
Chen, L., Özsu, M.T., Oria, V.: Robust and fast similarity search for moving object trajectories. In: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data, SIGMOD 2005, pp. 491–502. ACM, New York (2005)
Riedel, D.E., Venkatesh, S., Liu, W.: Recognising online spatial activities using a bioinformatics inspired sequence alignment approach. Pattern Recognition 41(11), 3481–3492 (2008)
Tormene, P., Giorgino, T., Quaglini, S., Stefanelli, M.: Matching incomplete time series with dynamic time warping: an algorithm and an application to post-stroke rehabilitation. Artificial Intelligence in Medicine 45(1), 11–34 (2009)
Munich, M.E., Perona, P.: Continuous dynamic time warping for translation-invariant curve alignment with applications to signature verification. In: Proceedings of 7th International Conference on Computer Vision, pp. 108–115 (1999)
Vlachos, M., Hadjieleftheriou, M., Gunopulos, D., Keogh, E.J.: Indexing multidimensional time-series. VLDB J. 15(1), 1–20 (2006)
Frentzos, E., Gratsias, K., Theodoridis, Y., Frentzos, E., Gratsias, K., Theodoridis, Y.: 1 index-based most similar trajectory search (November 2006)
Yi, B.K., Faloutsos, C.: Fast time sequence indexing for arbitrary lp norms. In: Proceedings of the 26th International Conference on Very Large Data Bases, VLDB 2000, pp. 385–394. Morgan Kaufmann Publishers Inc., San Francisco (2000)
Chen, Y., Nascimento, M.A., Chin, B., Anthony, O., Tung, K.H.: Spade: On shape-based pattern detection in streaming time series. In: ICDE 2007, pp. 786–795 (2007)
Xie, H., Fedder, G.K., Sulouff, R.E.: 2.05 - accelerometers. In: Yogesh Gianchandani, E., Tabata, O., Zappe, H. (eds.) Comprehensive Microsystems, pp. 135–180. Elsevier, Oxford (2008)
Diz, M.L.B., Baruque, B., Corchado, E., Bajo, J., Corchado, J.M.: Hybrid neural intelligent system to predict business failure in small-to-medium-size enterprises. Int. J. Neural Syst. 21(4), 277–296 (2011)
Abraham, A.: Special issue: Hybrid approaches for approximate reasoning. Journal of Intelligent and Fuzzy Systems 23(2-3), 41–42 (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Álvarez, M.L.A. et al. (2014). Hybrid Systems for Analyzing the Movements during a Temporary Breath Inability Episode. In: Polycarpou, M., de Carvalho, A.C.P.L.F., Pan, JS., Woźniak, M., Quintian, H., Corchado, E. (eds) Hybrid Artificial Intelligence Systems. HAIS 2014. Lecture Notes in Computer Science(), vol 8480. Springer, Cham. https://doi.org/10.1007/978-3-319-07617-1_48
Download citation
DOI: https://doi.org/10.1007/978-3-319-07617-1_48
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07616-4
Online ISBN: 978-3-319-07617-1
eBook Packages: Computer ScienceComputer Science (R0)