Abstract
The Sleep Apnea is a respiratory disorder that affects a very significant number of patients, with different ages. One of the main consequences of suffering from apneas is the increase in the risk of stroke onsets. This study is concerned with an automatic identification of apnea episodes using a single triaxial accelerometer placed on the center of the chest. The relevance of this approach is that the devices for home recording and the analysis of the data can be highly reduced, increasing the patient comfort during the data gathering and reducing the time needed for the data analysis. A very simple heuristic has been found useful for identifying this type of episodes. For this study, normal subjects have been evaluated with this approach; it is expected that data from patients that might suffer apneas will be available soon, so the performance of this approach on real scenarios can be reported.
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References
Lapi S, Lavorini F, Borgioli G, Calzolai M, Masotti L, Pistolesi M, Fontana GA (2014) Respiratory rate assessments using a dual-accelerometer device. Respir Physiol Neurobiol 191:60–66
Stepnowsky CJ, Palau JJ, Zamora T, Ancoli-Israel S, Loredo JS (2011) Fatigue in sleep apnea: the role of depressive symptoms and self-reported sleep quality. Sleep Med 12:832–837
Lloberes P, Durán-Cantolla J, Martínez-García MÁ, Marín JM, Ferrer A, Corral J, Masa JF, Parra O, Alonso-Álvarez ML, Terán-Santos J (2011) Diagnosis and treatment of sleep apnea-hypopnea syndrome. Arch Bronconeumol 47(3):143–156
Badran M, Ayas N, Laher I (2014) Insights into obstructive sleep apnea research. Sleep Med 15:485–495
Duran-Cantolla J, Barbe F, Rigau J, Oreja D, Martinez-Null C, Santaolalla CE (2013) A new vibratory postural device for the treatment of positional obstructive sleep apnea (OSA). A pilot study Sleep Med 14:e111
Joosten SA, O’Driscoll DM, Berger PJ, Hamilton GS (2014) Supine position related obstructive sleep apnea in adults: pathogenesis and treatment. Sleep Med Rev 18:7–17
Doukas C, Petsatodis T, Boukis C, Maglogiannis I (2012) Automated sleep breath disorders detection utilizing patient sound analysis. Biomed Signal Process Control 7:256–264
Sannino G, Falco ID, Pietro GD (2014) Monitoring obstructive sleep apnea by means of a real-time mobile system based on the automatic extraction of sets of rules through differential evolution. J Biomed Inf 49:84–100
Antonopoulou S, Loukides S, Papatheodorou G, Roussos C, Alchanatis M (2008) Airway inflammation in obstructive sleep apnea: Is leptin the missing link? Respir Med 102:1399–1405
Al-Mardini M, Aloul F, Sagahyroon A, Al-Husseini L (2014) Classifying obstructive sleep apnea using smartphones. J Biomed Inf 52:251–259
Rodes C, Chillrud S, Haskell W, Intille S, Albinali F, Rosenberger M (2012) Predicting adult pulmonary ventilation volume and wearing complianceby on-board accelerometry during personal level exposure assessments. Atmos Environ 57:126–137
Peltokangas M, Verho J, Vehkaoja A (2012) Night-time ekg and hrv monitoring with bed sheet integrated textile electrodes. IEEE Trans Inf Technol Biomed 16:935–942
Villar JR, Gonzlez S, Sedano J, Chira C, Trejo-Gabriel-Galan JM Improving human activity recognition and its application in early stroke diagnosis. Int J Neural Syst. DOI: 10.1142/S0129065714500361
Patiño J, Restrepo J, Rodríguez E (2005) Gases sanguíneos, fisiología de la respiración e insuficiencia respiratoria aguda. Editorial Medica Panamericana Sa de
Myrrha MAC, Vieira DSR, Moraes KS, Lage SM, Parreira VF, Britto RR (2013) Chest wall volumes during inspiratory loaded breathing in COPD patients. Respir Physiol Neurobiol 188:15–20
Bsoul M, Minn H, Member S, Tamil L, Member S (2011) Apnea medassist: real-time sleep apnea monitor using single-lead ecg. In: IEEE Trans Inf Technol Biomed 416–427
Acknowledgments
This research has been funded by the Spanish Ministry of Science and Innovation, under projects TIN2011-24302 and TIN2014-56967-R, Fundación Universidad de Oviedo project FUO-EM-340-13, Junta de Castilla y León projects BIO/BU09/14 and SACYL 2013 GRS/822/A/13.
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González, S., Villar, J.R., Sedano, J., Terán, J., Álvarez, M.L.A., González, J. (2015). Heuristics for Apnea Episodes Recognition. In: Herrero, Á., Sedano, J., Baruque, B., Quintián, H., Corchado, E. (eds) 10th International Conference on Soft Computing Models in Industrial and Environmental Applications. Advances in Intelligent Systems and Computing, vol 368. Springer, Cham. https://doi.org/10.1007/978-3-319-19719-7_22
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DOI: https://doi.org/10.1007/978-3-319-19719-7_22
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