Evaluation of a Multichannel Non-Contact ECG System and Signal Quality Algorithms for Sleep Apnea Detection and Monitoring

Sleep-related conditions require high-cost and low-comfort diagnosis at the hospital during one night or longer. To overcome this situation, this work aims to evaluate an unobtrusive monitoring technique for sleep apnea. This paper presents, for the first time, the evaluation of contactless capacitively-coupled electrocardiography (ccECG) signals for the extraction of sleep apnea features, together with a comparison of different signal quality indicators. A multichannel ccECG system is used to collect signals from 15 subjects in a sleep environment from different positions. Reference quality labels were assigned for every 30-s segment. Quality indicators were calculated, and their signal classification performance was evaluated. Features for the detection of sleep apnea were extracted from capacitive and reference signals. Sleep apnea features related to heart rate and heart rate variability achieved high similarity to the reference values, with p-values of 0.94 and 0.98, which is in line with the more than 95% beat-matching obtained. Features related to signal morphology presented lower similarity with the reference, although signal similarity metrics of correlation and coherence were relatively high. Quality-based automatic classification of the signals had a maximum accuracy of 91%. Best-performing quality indicators were based on template correlation and beat-detection. Results suggest that using unobtrusive cardiac signals for the automatic detection of sleep apnea can achieve similar performance as contact signals, and indicates clinical value of ccECG. Moreover, signal segments can automatically be classified by the proposed quality metrics as a pre-processing step. Including contactless respiration signals is likely to improve the performance and provide a complete unobtrusive cardiorespiratory monitoring solution; this is a promising alternative that will allow the screening of more patients with higher comfort, for a longer time, and at a reduced cost.

[1]  Archisman Sarkar,et al.  A health monitoring system using multiple non-contact ECG sensors for automotive drivers , 2016, 2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings.

[2]  R. Strecker,et al.  Recent Developments in Home Sleep-Monitoring Devices , 2012, ISRN neurology.

[3]  Chris Van Hoof,et al.  Robust wireless capacitive ECG system with adaptive signal quality and motion artifact reduction , 2016, 2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA).

[4]  Akinori Ueno,et al.  Non-Contact Simultaneous Measurements of Electrocardiogram and Respiratory Movements Using Capacitive Sheet Electrodes , 2017 .

[5]  David A. Clifton,et al.  Signal-Quality Indices for the Electrocardiogram and Photoplethysmogram: Derivation and Applications to Wireless Monitoring , 2015, IEEE Journal of Biomedical and Health Informatics.

[6]  Gert Cauwenberghs,et al.  Wireless non-contact cardiac and neural monitoring , 2010, Wireless Health.

[7]  Wilhelm Stork,et al.  Signal Quality Assessment for Capacitive ECG Monitoring Systems using Body-sensor-impedance , 2011, BIOSIGNALS.

[8]  Yue Zhang,et al.  An algorithm for evaluating the ECG signal quality in 12 lead ECG monitoring system , 2015, 2015 6th IEEE International Conference on Software Engineering and Service Science (ICSESS).

[9]  Julien Penders,et al.  Robust beat detector for ambulatory cardiac monitoring , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[10]  Hagen Malberg,et al.  Cascaded output selection for processing of capacitive electrocardiograms by means of independent component analysis , 2013, 2013 Workshop on Sensor Data Fusion: Trends, Solutions, Applications (SDF).

[11]  Steffen Leonhardt,et al.  Motion Artifact Quantification and Sensor Fusion for Unobtrusive Health Monitoring , 2017, Sensors.

[12]  T. Young,et al.  Increased prevalence of sleep-disordered breathing in adults. , 2013, American journal of epidemiology.

[13]  Kwang Suk Park,et al.  Heart Rate Variability Monitoring during Sleep Based on Capacitively Coupled Textile Electrodes on a Bed , 2015, Sensors.

[14]  Ying Bai,et al.  An ultra-wearable, wireless, low power ECG monitoring system , 2006, 2006 IEEE Biomedical Circuits and Systems Conference.

[15]  I. Jekova,et al.  QRS Template Matching for Recognition of Ventricular Ectopic Beats , 2007, Annals of Biomedical Engineering.

[16]  Yong Gyu Lim,et al.  ECG Recording on a Bed During Sleep Without Direct Skin-Contact , 2007, IEEE Transactions on Biomedical Engineering.

[17]  J. Basilakis,et al.  ECG quality measures in telecare monitoring , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[18]  Wilhelm Stork,et al.  Reliable motion artifact detection for ECG monitoring systems with dry electrodes , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[19]  Hlaing Minn,et al.  Apnea MedAssist: Real-time Sleep Apnea Monitor Using Single-Lead ECG , 2011, IEEE Transactions on Information Technology in Biomedicine.

[20]  G D Clifford,et al.  Signal quality indices and data fusion for determining clinical acceptability of electrocardiograms , 2012, Physiological measurement.

[21]  Seung Min Lee,et al.  Wavelet approach to artifact noise removal from Capacitive coupled Electrocardiograph , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[22]  Günter Schreier,et al.  QRS detection based ECG quality assessment , 2012, Physiological measurement.

[23]  J. Y. Wang A new method for evaluating ECG signal quality for multi-lead arrhythmia analysis , 2002, Computers in Cardiology.

[24]  R G Mark,et al.  Robust heart rate estimation from multiple asynchronous noisy sources using signal quality indices and a Kalman filter , 2008, Physiological measurement.

[25]  Sabine Van Huffel,et al.  A Novel Algorithm for the Automatic Detection of Sleep Apnea From Single-Lead ECG , 2015, IEEE Transactions on Biomedical Engineering.

[26]  Yong Gyu Lim,et al.  Capacitive Measurement of ECG for Ubiquitous Healthcare , 2014, Annals of Biomedical Engineering.

[27]  Refet Firat Yazicioglu,et al.  Noncontact ECG Recording System With Real Time Capacitance Measurement for Motion Artifact Reduction , 2014, IEEE Transactions on Biomedical Circuits and Systems.

[28]  Steffen Leonhardt,et al.  ECG on the Road: Robust and Unobtrusive Estimation of Heart Rate , 2011, IEEE Transactions on Biomedical Engineering.

[29]  T Penzel,et al.  A review of signals used in sleep analysis , 2014, Physiological measurement.

[30]  H.L. Chan,et al.  Heartbeat Detection Using Energy Thresholding and Template Match , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[31]  Ronald M. Aarts,et al.  Unobtrusive sleep state measurements in preterm infants - A review. , 2017, Sleep medicine reviews.

[32]  R. Thomas,et al.  An electrocardiogram-based technique to assess cardiopulmonary coupling during sleep. , 2005, Sleep.

[33]  V. Somers,et al.  Sleep-disordered breathing and cardiovascular risk. , 2007, Sleep.

[34]  Martin Maier,et al.  MS-QI: A Modulation Spectrum-Based ECG Quality Index for Telehealth Applications , 2016, IEEE Transactions on Biomedical Engineering.

[35]  Lionel Tarassenko,et al.  Application of independent component analysis in removing artefacts from the electrocardiogram , 2006, Neural Computing & Applications.

[36]  D. Greenblatt,et al.  The International Classification of Sleep Disorders , 1992 .

[37]  E. Wolpert A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects. , 1969 .

[38]  Gerhard Tröster,et al.  Automatic Signal Appraisal for Unobtrusive ECG Measurements , 2010 .

[39]  William P. Marnane,et al.  Assessment of quality of ECG for accurate estimation of Heart Rate Variability in newborns , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[40]  E. Naujokat,et al.  Sleep Monitoring Through a Textile Recording System , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[41]  Stephan Heuer,et al.  Motion Artefacts in Capacitively Coupled ECG Electrodes , 2009 .