Диссертация (Разработка технологии и программно-аппаратного комплекса для исследования структуры сна человека), страница 16
Описание файла
Файл "Диссертация" внутри архива находится в папке "Разработка технологии и программно-аппаратного комплекса для исследования структуры сна человека". PDF-файл из архива "Разработка технологии и программно-аппаратного комплекса для исследования структуры сна человека", который расположен в категории "". Всё это находится в предмете "технические науки" из Аспирантура и докторантура, которые можно найти в файловом архиве МГТУ им. Н.Э.Баумана. Не смотря на прямую связь этого архива с МГТУ им. Н.Э.Баумана, его также можно найти и в других разделах. Архив можно найти в разделе "остальное", в предмете "диссертации и авторефераты" в общих файлах, а ещё этот архив представляет собой кандидатскую диссертацию, поэтому ещё представлен в разделе всех диссертаций на соискание учёной степени кандидата технических наук.
Просмотр PDF-файла онлайн
Текст 16 страницы из PDF
238 p.43. Comorbidity of Chronic Insomnia With Medical Problems / D.J. Taylor[et al.] // Sleep. 2007. Vol. 30, N. 2. P. 213–218.44. Epidemiology of Alcohol and Medication as Aids to Sleep in EarlyAdulthood / E.O. Johnson [et al.] // Sleep. 1998. Vol. 21, N. 2. P. 178–186.45. Embletta X100. URL: http://www.mortara.com/au/products/sleep-diagnostics/portable-sleep-systems/emblettar-x100tm/ (date of access: 04.09.2016).46. Кардио-респираторный мониторинг.URL: http://www.hrap.by/news/kardio-respiratornyi-monitoring (дата обращения: 04.09.2016).47.
Pulse oximetry. URL: https://en.wikipedia.org/wiki/Pulseoximetry (date ofaccess: 04.09.2016).48. Actigraphy. URL: http://www.actigraphy.com/applications/about_actigraphy.html (date of access: 04.09.2016).49. Пример дневника сна. URL: http://buzunov.ru/wp-content/uploads/2012/09/(дата обращения: 04.09.2016).50. Gaina A., Michekazu S., Chen X. Validity of Child Sleep Diary Questionnaireamong Junior High School Children // Journal of Epidemiology.2016.Vol. 14.
2004.51. Baker F.C., Maloney S., Driver H.S. A comparison of subjective estimatesof sleep with objective polysomnographic data in healthy men and women //Journal of Psychosomatic Research. 1999. Vol. 47, N. 4. P. 335–341.12852. KushidaC.,ChangA.,GadkaryC.Comparisonofactigraphic,polysomnographic, and subjective assessment of sleep parameters insleep-disordered patients // Sleep Medicine. 2001. Vol. 2. P. 389–396.53. Determination of Sleep State in Infants Using Respiratory Variability /G.G. Haddad [et al.] // Pediatric Research.
1987. Vol. 21, N. 6. P. 556–562.54. Harper R.M., Schechtman V.L., Kluge K.A. Machine classification of infantsleep state using cardiorespiratory measures // Electroencephalography andClinical Neurophysiology. 1987. Vol. 67, N. 4. P. 379–387.55. Sleep state scoring in infants from respiratory and activity measurements /N.A. Sazonova [et al.] // Annual International Conference of the IEEEEngineering in Medicine and Biology. 2006. Vol. 1.
P. 2462–2465.56. REM Sleep Classification with Respiration Rates / G.S. Chung [et al.] //2007 6th International Special Topic Conference on Information TechnologyApplications in Biomedicine. IEEE, 2007. P. 194–197.57. REM sleep estimation only using respiratory dynamics. / G.S.
Chung [et al.] //Physiological measurement. 2009. Vol. 30, N. 12. P. 1327–40.58. Attractor structure discriminates sleep states: Recurrence plot analysis appliedto infant breathing patterns / P.I. Terrill [et al.] // IEEE Transactions onBiomedical Engineering. 2010. Vol. 57, N. 5. P. 1108–1116.59. Application of recurrence quantification analysis to automatically estimateinfant sleep states using a single channel of respiratory data / P.I. Terrill[et al.] // Medical and Biological Engineering and Computing.
2012. Vol. 50,N. 8. P. 851–865.60. Respiration amplitude analysis for REM and NREM sleep classification /X. Long [et al.] // Proceedings of the Annual International Conference of theIEEE Engineering in Medicine and Biology Society, EMBS. 2013. Vol. 2013.P. 5017–5020.61.
Analyzingrespiratoryeffortamplitudeforautomatedsleepstageclassification / X. Long [et al.] // Biomedical Signal Processing and Control.1292014. Vol. 14, N. 1. P. 197–205.62. Redmond S.J., Heneghan C. Cardiorespiratory-based sleep staging in subjectswith obstructive sleep apnea // IEEE Transactions on Biomedical Engineering.2006. Vol. 53, N. 3.
P. 485–496.63. Sleep staging using cardiorespiratory signals / S.J. Redmond [et al.] //Somnologie. 2007. Vol. 11, N. 4. P. 245–256.64. Time-frequency analysis of heart rate variability for sleep and wakeclassification / X. Long [et al.] // 2012 IEEE 12th International Conferenceon Bioinformatics & Bioengineering (BIBE). 2012. P. 85–90.65. Sleep stage classification with ECG and respiratory effort / P. Fonseca[et al.] // Physiological Measurement. 2015.
Vol. 36, N. 10. P. 2027–2040.66. Sleep and wake classification with actigraphy and respiratory effort usingdynamic warping / X. Long [et al.] // IEEE Journal of Biomedical and HealthInformatics. 2014. Vol. 18, N. 4. P. 1272–1284.67. Measuring dissimilarity between respiratory effort signals based on uniformscaling for sleep staging / X. Long [et al.] // Physiological Measurement.2014. Vol. 35, N. 12. P. 2529–2542.68.
Self-Dissimilarity of Respiratory Effort Across Sleep States and Time /X. Long [et al.] // Meeting of the Associated Professional Sleep Societies.Vol. 37. 2014. P. A36.69. Automatic Feature Selection for Sleep/Wake Classification with Small DataSets / J. Foussier [et al.] // 6th International Conference on BioinformaticsModels, Methods and Algorithms. 2013. P. 1–7.70. Watanabe T., Watanabe K. Noncontact method for sleep stage estimation //IEEE Transactions on Biomedical Engineering.2004.Vol.
51, N. 10.P. 1735–1748.71. Kurihara Y., Watanabe K. Sleep-stage decision algorithm by using heartbeatand body-movement signals // IEEE Transactions on Systems, Man, andCybernetics Part A:Systems and Humans. 2012. Vol. 42, N. 6. P. 1450–1459.13072. Evaluation of the sleep quality based on bed sensor signals: Time variantanalysis / M.O. Mendez [et al.] // 2010 Annual International Conference ofthe IEEE Engineering in Medicine and Biology Society.
2010. Vol. 2010.P. 3994–3997.73. Sleep staging based on signals acquired through bed sensor / J.M. Kortelainen[et al.] // IEEE Transactions on Information Technology in Biomedicine. 2010.Vol. 14, N. 3. P. 776–785.74. Sleep-wake detection based on respiratory signal acquired through a PressureBed Sensor / G. Guerrero-Mora [et al.] // Proceedings of the AnnualInternational Conference of the IEEE Engineering in Medicine and BiologySociety, EMBS. 2012. Vol. 2012.
P. 3452–3455.75. Bianchi A.M., Mendez M.O. Automatic detection of sleep macrostructurebased on a sensorized T-shirt // 2010 Annual International Conference of theIEEE Engineering in Medicine and Biology Society, EMBC’10. 2010. Vol.2010. P. 3606–3609.76. Optimization of Time-Variant Autoregressive Models for tracking REM non REM transitions during sleep / G. Tacchino [et al.] // 2012 AnnualInternational Conference of the IEEE Engineering in Medicine and BiologySociety. Vol.
2012. IEEE, 2012. P. 2236–2239.77. Migliorini M., Nistico D. Time-frequency analysis of the ballistocardiogramfor sleep staging. Milan. Politechico di Milano, 2010. 150 p.78. EMFIT. URL: https://www.emfit.com/ (date of access: 04.09.2016).79.
Emfit.URL:http://cdn.shopify.com/s/files/1/0850/0144/t/2/assets/home-left-right-image-3.png?17599053060246059139(dateofaccess:04.09.2016).80. An evaluation of a non-contact biomotion sensor with actimetry / N.A. Fox[et al.] // Annual International Conference of the IEEE Engineering inMedicine and Biology - Proceedings. 2007. P. 2664–2668.13181. Sleep/wake measurement using a non-contact biomotion sensor / P.
De Chazal[et al.] // Journal of Sleep Research. 2011. Vol. 20, N. 2. P. 356–366.82. Comparison of a novel non-contact biomotion sensor with wrist actigraphy inestimating sleep quality in patients with obstructive sleep apnoea / M. Pallin[et al.] // Journal of Sleep Research. 2014. Vol. 23, N. 4. P. 475–484.83. Automated sleep staging classification using a non-contact biomotion sensor /A. Zaffaroni [et al.] // Journal of Sleep Research. 2014.
Vol. 23, N. Sp. 1.105 p.84. ResMed. URL: https://2nznub4x5d61ra4q12fyu67t-wpengine.netdna-ssl.com/wp-content/uploads/2014/10/ResMed-S-.png (date of access: 04.09.2016).85. Accuracy validation of sleep measurements by a contactless biomotion sensoron subjects with suspected sleep apnea / M. Hashizaki [et al.] // Sleep andBiological Rhythms. 2014.
Vol. 12, N. 2. P. 106–115.86. DoppleSleep: A Contactless Unobtrusive Sleep Sensing System UsingShort-Range Doppler Radar / T. Rahman [et al.] // Proceedings of the 2015ACM International Joint Conference on Pervasive and Ubiquitous Computing- UbiComp ’15. 2015. P. 39–50.87. Shambroom J.
R., Fábregas S. E., Johnstone J. Validation of an automatedwireless system to monitor sleep in healthy adults // Journal of SleepResearch. 2012. Vol. 21, N. 2. P. 221–230.88. Sleep stage classification by body movement index and respiratory intervalindices using multiple radar sensors / M. Kagawa [et al.] // Proceedings of theAnnual International Conference of the IEEE Engineering in Medicine andBiology Society, EMBS. 2015. P. 7606–7609.89. Detection of Nocturnal Slow Wave Sleep Based on Cardiorespiratory Activityin Healthy Adults / X.
Long [et al.] // IEEE Journal of Biomedical and HealthInformatics. 2015. P. 1–11.90. Chouchou F., Desseilles M. Heart rate variability: A tool to explore thesleeping brain? // Frontiers in Neuroscience. 2014. Vol. 8, N. DEC. P. 1–9.13291. 2013 ESH/ESC Guidelines for the management of arterial hypertension /G. Mancia [et al.] // European Heart Journal. 2013. Vol.
34. P. 2159–2219.92. Физиология человека / Под ред. В.М. Покровский, Г.Ф. Коротько.Москва. Медицина, 2007. 656 c.93. Хауликэ И. Вегетативная нервная система.Бухарест. Медицинскоеиздательство Социалистической Республики Бухарест, 1978. 349 c.94. Гриппи М.А.
Патофизиология легких / Под ред. Н.А. Наточин. 2 изд.Москва. Бином, 2005. 304 c.95. Ambient and Unobtrusive Cardiorespiratory Monitoring Techniques /C. Bruser [et al.] // IEEE Reviews in Biomedical Engineering. 2015. Vol. 8.P. 30–43.96. Zeo Sleep Manager Pro.URL: http://www.pcmag.com/article2/0,2817,2413445,00.asp (date of access: 04.09.2016).97. Automatic sleep stage classification using two-channel / J.
Virkkala [et al.] //Journal of Neuroscience Methods. 2007. Vol. 166. P. 109–115.98. Detection of breathing sounds during sleep using non-contact audiorecordings / T. Rosenwein [et al.] // 2014 36th Annual InternationalConference of the IEEE Engineering in Medicine and Biology Society, EMBC2014. 2014. P. 1489–1492.99. Dafna E., Tarasiuk A., Zigel Y. Sleep-wake evaluation from whole-nightnon-contact audio recordings of breathing sounds // PLoS ONE.