Towards an accurate sleep apnea detection based on ECG signal: The quintessential of a wise feature selection
暂无分享,去创建一个
Nuno M. Garcia | Bruno M. C. Silva | Nuno Pombo | Kouamana Bousson | Andre Miguel da Silva Pinho | A. S. Pinho | Bruno M. C. Silva | Nuno Pombo | N. Garcia | K. Bousson | A. Pinho
[1] Nuno M. Garcia,et al. ubiSleep: An ubiquitous sensor system for sleep monitoring , 2016, 2016 IEEE 12th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob).
[2] Khaled M. Elleithy,et al. Apnea Detection based on Respiratory Signal Classification , 2013, EUSPN/ICTH.
[3] Philip de Chazal,et al. Automated detection of obstructive sleep apnoea by single-lead ECG through ELM classification , 2014, Computing in Cardiology 2014.
[4] Peter Tarczy-Hornoch,et al. Bioinformatics Challenges and Opportunities , 2005 .
[5] T. Aswathy Devi,et al. Obstructive sleep apnea detection from ECG signal using neuro-fuzzy classifier , 2017, 2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT).
[6] G. Moody,et al. The apnea-ECG database , 2000, Computers in Cardiology 2000. Vol.27 (Cat. 00CH37163).
[7] Antonio J. Serrano,et al. Feature selection using ROC curves on classification problems , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).
[8] Sabine Van Huffel,et al. Sleep apnea classification using least-squares support vector machines on single lead ECG , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[9] Wai-Chi Fang,et al. An electrocardiography system design for obstructive sleep apnea detection based on improved lomb frequency analysis algorithm , 2017, 2017 IEEE Biomedical Circuits and Systems Conference (BioCAS).
[10] A.H. Khandoker,et al. Automatic recognition of obstructive sleep apnoea syndrome using power spectral analysis of electrocardiogram and Hidden Markov Models , 2008, 2008 International Conference on Intelligent Sensors, Sensor Networks and Information Processing.
[11] M. Mukaka,et al. Statistics corner: A guide to appropriate use of correlation coefficient in medical research. , 2012, Malawi medical journal : the journal of Medical Association of Malawi.
[12] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[13] Masatoshi Nakamura,et al. Automatic EEG arousal detection for sleep apnea syndrome , 2009, Biomed. Signal Process. Control..
[14] Isabelle Guyon,et al. An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..
[15] Hlaing Minn,et al. Apnea MedAssist: Real-time Sleep Apnea Monitor Using Single-Lead ECG , 2011, IEEE Transactions on Information Technology in Biomedicine.
[16] Hlaing Minn,et al. Real-Time Sleep Apnea Detection by Classifier Combination , 2012, IEEE Transactions on Information Technology in Biomedicine.
[17] Kemal Polat,et al. A new feature selection method on classification of medical datasets: Kernel F-score feature selection , 2009, Expert Syst. Appl..
[18] G. Tomlinson,et al. Obstructive Sleep Apnea and Risk of Cardiovascular Events and All-Cause Mortality: A Decade-Long Historical Cohort Study , 2014, PLoS medicine.
[19] C. Yancy,et al. Worldwide disparities in cardiovascular disease: Challenges and solutions. , 2016, International journal of cardiology.
[20] Chien-Chang Hsu,et al. A novel sleep apnea detection system in electroencephalogram using frequency variation , 2011, Expert Syst. Appl..
[21] C. Santhosh Kumar,et al. Automated system for obstructive sleep apnea detection using heart rate variability and respiratory rate variability , 2017, 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI).
[22] J. Hanley,et al. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. , 1983, Radiology.
[23] J. McNames,et al. Obstructive sleep apnea classification based on spectrogram patterns in the electrocardiogram , 2000, Computers in Cardiology 2000. Vol.27 (Cat. 00CH37163).
[24] Necmettin Sezgin,et al. EMG classification in obstructive sleep apnea syndrome and periodic limb movement syndrome patients by using wavelet packet transform and extreme learning machine , 2015 .
[25] Larry A. Rendell,et al. A Practical Approach to Feature Selection , 1992, ML.
[26] R. Moddemeijer. On estimation of entropy and mutual information of continuous distributions , 1989 .
[27] Parmjit Singh,et al. The new AASM criteria for scoring hypopneas: impact on the apnea hypopnea index. , 2009, Sleep.
[28] A. Tewfik,et al. Monitoring of Obstructive Sleep Apnea in Heart Failure Patients , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[29] Yvan Saeys,et al. Robust Feature Selection Using Ensemble Feature Selection Techniques , 2008, ECML/PKDD.
[30] Mohammed Imamul Hassan Bhuiyan,et al. Computerized obstructive sleep apnea diagnosis from single-lead ECG signals using dual-tree complex wavelet transform , 2017, 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC).
[31] James F. Kaiser,et al. Some useful properties of Teager's energy operators , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[32] Feng Jiang,et al. Recurrent Neural Network Based Classification of ECG Signal Features for Obstruction of Sleep Apnea Detection , 2017, 22017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC).
[33] Conor Heneghan,et al. Automated processing of the single-lead electrocardiogram for the detection of obstructive sleep apnoea , 2003, IEEE Transactions on Biomedical Engineering.
[34] B. Pliska,et al. Prediction of oral appliance treatment outcomes in obstructive sleep apnea: A systematic review. , 2016, Sleep medicine reviews.
[35] F. J. Nieto,et al. Relation of sleepiness to respiratory disturbance index: the Sleep Heart Health Study. , 1999, American journal of respiratory and critical care medicine.
[36] Vivek Kanhangad,et al. Gabor Filter-Based One-Dimensional Local Phase Descriptors for Obstructive Sleep Apnea Detection Using Single-Lead ECG , 2018, IEEE Sensors Letters.
[37] Mustafa Poyraz,et al. An expert system for automated recognition of patients with obstructive sleep apnea using electrocardiogram recordings , 2011, Expert Syst. Appl..
[38] Nuno M. Garcia,et al. Classification techniques on computerized systems to predict and/or to detect Apnea: A systematic review , 2017, Comput. Methods Programs Biomed..