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Relevant bibliographies by topics / ECG-derived respiratory

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Academic literature on the topic 'ECG-derived respiratory'

Author: Grafiati

Published: 28 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "ECG-derived respiratory"

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Kontaxis, Spyridon, Jesus Lazaro, Valentina D. A. Corino, et al. "ECG-Derived Respiratory Rate in Atrial Fibrillation." IEEE Transactions on Biomedical Engineering 67, no. 3 (2020): 905–14. http://dx.doi.org/10.1109/tbme.2019.2923587.

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Dickhaus, H., and C. Maier. "Central Sleep Apnea Detection from ECG-derived Respiratory Signals." Methods of Information in Medicine 49, no. 05 (2010): 462–66. http://dx.doi.org/10.3414/me09-02-0047.

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Summary Objectives: This study examines the suitability of recurrence plot analysis for the problem of central sleep apnea (CSA) detection and delineation from ECG-derived respiratory (EDR) signals. Methods: A parameter describing the average length of vertical line structures in recurrence plots is calculated at a time resolution of 1 s as ‘instantaneous trapping time’. Threshold comparison of this parameter is used to detect ongoing CSA. In data from 26 patients (duration 208 h) we assessed sensitivity for detection of CSA and mixed apnea (MSA) events by comparing the results obtained from 8

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Bao, Xinqi, Aimé Kingwengwe Abdala, and Ernest Nlandu Kamavuako. "Estimation of the Respiratory Rate from Localised ECG at Different Auscultation Sites." Sensors 21, no. 1 (2020): 78. http://dx.doi.org/10.3390/s21010078.

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The respiratory rate (RR) is a vital physiological parameter in prediagnosis and daily monitoring. It can be obtained indirectly from Electrocardiogram (ECG) signals using ECG-derived respiration (EDR) techniques. As part of the study in designing an early cardiac screening system, this work aimed to study whether the accuracy of ECG derived RR depends on the auscultation sites. Experiments were conducted on 12 healthy subjects to obtain simultaneous ECG (at auscultation sites and Lead I as reference) and respiration signals from a microphone close to the nostril. Four EDR algorithms were test

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Klum, Michael, Mike Urban, Timo Tigges, et al. "Wearable Cardiorespiratory Monitoring Employing a Multimodal Digital Patch Stethoscope: Estimation of ECG, PEP, LVET and Respiration Using a 55 mm Single-Lead ECG and Phonocardiogram." Sensors 20, no. 7 (2020): 2033. http://dx.doi.org/10.3390/s20072033.

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Cardiovascular diseases are the main cause of death worldwide, with sleep disordered breathing being a further aggravating factor. Respiratory illnesses are the third leading cause of death amongst the noncommunicable diseases. The current COVID-19 pandemic, however, also highlights the impact of communicable respiratory syndromes. In the clinical routine, prolonged postanesthetic respiratory instability worsens the patient outcome. Even though early and continuous, long-term cardiorespiratory monitoring has been proposed or even proven to be beneficial in several situations, implementations t

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Schrumpf, Fabian, Matthias Sturm, Gerold Bausch, and Mirco Fuchs. "Derivation of the respiratory rate from directly and indirectly measured respiratory signals using autocorrelation." Current Directions in Biomedical Engineering 2, no. 1 (2016): 241–45. http://dx.doi.org/10.1515/cdbme-2016-0054.

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AbstractThe estimation of respiratory rates from contineous respiratory signals is commonly done using either fourier transformation or the zero-crossing method. This paper introduces another method which is based on the autocorrelation function of the respiratory signal. The respiratory signals can be measured either directly using a flow sensor or chest strap or indirectly on the basis of the electrocardiogram (ECG). We compare our method against other established methods on the basis of real-world ECG signals and use a respiration-based breathing frequency as a reference. Our method achieve

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Schmidt, Marcus, Johannes W. Krug, Andy Schumann, Karl-Jürgen Bär, and Georg Rose. "Estimation of a respiratory signal from a single-lead ECG using the 4th order central moments." Current Directions in Biomedical Engineering 1, no. 1 (2015): 61–64. http://dx.doi.org/10.1515/cdbme-2015-0016.

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AbstractFor a variety of clinical applications like magnetic resonance imaging (MRI) the monitoring of vital signs is a common standard in clinical daily routine. Besides the electrocardiogram (ECG), the respiratory activity is an important vital parameter and might reveal pathological changes. Thoracic movement and the resulting impedance change between ECG electrodes enable the estimation of the respiratory signal from the ECG. This ECG-derived respiration (EDR) can be used to calculate the breathing rate without the need for additional devices or monitoring modules. In this paper a new meth

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Stergiopoulos, Dimitrios C., Stylianos N. Kounalakis, Panagiotis G. Miliotis, and Nikolaos D. Geladas. "Second Ventilatory Threshold Assessed by Heart Rate Variability in a Multiple Shuttle Run Test." International Journal of Sports Medicine 42, no. 01 (2020): 48–55. http://dx.doi.org/10.1055/a-1214-6309.

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AbstractMany studies have focused on heart rate variability in association with ventilatory thresholds. The purpose of the current study was to consider the ECG-derived respiration and the high frequency product of heart rate variability as applicable methods to assess the second ventilatory threshold (VT2). Fifteen healthy young soccer players participated in the study. Respiratory gases and ECGs were collected during an incremental laboratory test and in a multistage shuttle run test until exhaustion. VΤ2 was individually calculated using the deflection point of ventilatory equivalents. In a

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Sayadi, Omid, Eric H. Weiss, Faisal M. Merchant, Dheeraj Puppala, and Antonis A. Armoundas. "An optimized method for estimating the tidal volume from intracardiac or body surface electrocardiographic signals: implications for estimating minute ventilation." American Journal of Physiology-Heart and Circulatory Physiology 307, no. 3 (2014): H426—H436. http://dx.doi.org/10.1152/ajpheart.00038.2014.

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The ability to accurately monitor tidal volume (TV) from electrocardiographic (ECG) signals holds significant promise for improving diagnosis treatment across a variety of clinical settings. The objective of this study was to develop a novel method for estimating the TV from ECG signals. In 10 mechanically ventilated swine, we collected intracardiac electrograms from catheters in the coronary sinus (CS), left ventricle (LV), and right ventricle (RV), as well as body surface electrograms, while TV was varied between 0 and 750 ml at respiratory rates of 7–14 breaths/min. We devised an algorithm

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Gilfriche, Pierre, Laurent M. Arsac, Yannick Daviaux, et al. "Highly sensitive index of cardiac autonomic control based on time-varying respiration derived from ECG." American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 315, no. 3 (2018): R469—R478. http://dx.doi.org/10.1152/ajpregu.00057.2018.

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Frequency-domain indices of heart rate variability (HRV) have been used as markers of sympathovagal balance. However, they have been shown to be degraded by interindividual or task-dependent variability, and especially variations in breathing frequency. The study introduces a method to analyze respiration-(vagally) mediated HRV, to better assess subtle variations in sympathovagal balance using ECG recordings. The method enhances HRV analysis by focusing the quantification of respiratory sinus arrhythmia (RSA) gain on the respiratory frequency. To this end, instantaneous respiratory frequency w

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Schumann, Andy, Marcus Schmidt, Marco Herbsleb, et al. "Deriving respiration from high resolution 12-channel-ECG during cycling exercise." Current Directions in Biomedical Engineering 2, no. 1 (2016): 171–74. http://dx.doi.org/10.1515/cdbme-2016-0039.

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AbstractMonitoring of cardiac and respiratory activity, is essential in several clinical interventions like bicycle ergometries. The respiration signal can be derived from the ECG if it is not recorded itself (ECG derived respiration, EDR). In this study, we tried to reconstruct breathing rates (BR) from stress test high resolution 12-channel-ECGs in nine healthy subjects using higher order central moments. A mean absolute error per subjects of 2.9/min and relatively high correlation (rp = 0.85) and concordance coefficient (rc = 0.79) indicated a quite accurate reproduction of respiratory acti

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Dissertations / Theses on the topic "ECG-derived respiratory"

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Janáková, Jaroslava. "Odhad dechové frekvence z elektrokardiogramu a fotopletysmogramu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442594.

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The master thesis deals with the issue of gaining the respiratory rate from ECG and PPG signals, which are not only in clinical practice widely used measurable signals. The theoretical part of the work outlines the issue of obtaining a breath curve from these signals. The practical part of the work is focused on the implementation of five selected methods and their final evaluation and comparison.

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Tiinanen, S. (Suvi). "Methods for assessment of autonomic nervous system activity from cardiorespiratory signals." Doctoral thesis, Oulun yliopisto, 2019. http://urn.fi/urn:isbn:9789526223131.

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Abstract A cardiorespiratory system is highly regulated via the autonomic nervous system (ANS), whose function can be quantified noninvasively by analyzing electrocardiogram (ECG), blood pressure (BP) and respiration signals. Several conditions and illnesses are linked with imbalance of the ANS. This thesis aimed to develop methods for describing the ANS regulation of a cardiovascular system from short-term cardiorespiratory measurements. More specifically, the role of breathing rate and its effects on traditional frequency domain based cardiovascular indexes describing ANS control is addresse

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江政運. "Abnormal Sleep Breath Detection Based on the ECG Derived Respiratory Signal." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/07305267684692481290.

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碩士<br>逢甲大學<br>自動控制工程學系<br>102<br>Abstract The main purpose of this research is to develop a real-time abnormal breathing anomaly system, integrated with the physiological measurements smart clothing for monitoring abnormal breathing during sleep. In order to reduce the abnormal phenomena, physiological measurements will instead be done by smart-shirt measurements, and uses electrocardiograph derived respiratory signal from previous studies in order to achieve the same functionality with breathing bands. This system will be developed using LabVIEW® for analysis, while the signals will be measur

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Huang, Po-Yu, and 黃柏諭. "Parallelized Empirical Mode Decomposition in CUDA and Its Application to ECG-Derived Respiratory." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/wz8x65.

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碩士<br>國立交通大學<br>電機工程學系<br>103<br>ECG-Derived Respiratory (EDR) is a technique to derive respiratory from electrocardiography (ECG), which can help to overcome limitation of traditional respiratory acquisition method. Empirical Mode Decomposition (EMD) is process of adaptive analysis applicable to non-linear and non-stationary data such as ECG, hence it can be used to deal with EDR application. EMD analyzes data by iteratively decomposing data into multiple Intrinsic Mode Functions (IMFs). Traditionally, EMD is computed on all data points in a serial manner, thus making its execution time grows

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Books on the topic "ECG-derived respiratory"

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Johnson, Nicholas J., and Judd E. Hollander. Management of cocaine poisoning. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0324.

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Cocaine is powerful central nervous system (CNS) stimulant derived from the coca plant. It affects the body via a number of mechanisms including blockade of fast sodium channels, increased catecholamine release, inhibition of catecholamine reuptake, and increased concentration of excitatory amino acid concentrations in the CNS. It is rapidly absorbed via the aerodigestive, respiratory, gastrointestinal, and genitourinary mucosa, and also may be injected. When injected intravenously or inhaled, cocaine is rapidly distributed throughout the body and CNS, with peak effects in 3–5 minutes. With na

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Book chapters on the topic "ECG-derived respiratory"

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Sahin, Mesut, Howard Fidel, and Raquel Perez-Castillejos. "Extraction of Respiratory Rate from ECG (ECG-Derived Respiration-EDR)." In Instrumentation Handbook for Biomedical Engineers. CRC Press, 2020. http://dx.doi.org/10.1201/9780429193989-11.

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Conference papers on the topic "ECG-derived respiratory"

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Rajagopalan, Pradeep, and Sabarish Ramachandran. "ECG derived respiratory rate estimation for wearable devices." In 2017 International Conference on Computational Intelligence in Data Science (ICCIDS). IEEE, 2017. http://dx.doi.org/10.1109/iccids.2017.8272664.

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Campolo, M., D. Labate, F. La Foresta, F. C. Morabito, A. Lay-Ekuakille, and P. Vergallo. "ECG-derived respiratory signal using Empirical Mode Decomposition." In 2011 IEEE International Symposium on Medical Measurements and Applications (MeMeA). IEEE, 2011. http://dx.doi.org/10.1109/memea.2011.5966727.

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Birrenkott, Drew A., Marco A. F. Pimentel, Peter J. Watkinson, and David A. Clifton. "Robust estimation of respiratory rate via ECG- and PPG-derived respiratory quality indices." In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2016. http://dx.doi.org/10.1109/embc.2016.7590792.

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Konik, Arda, Joyeeta Mitra Mukherjee, Karen L. Johnson, Eric Helfenbein, Lingxiong Shao, and Michael A. King. "Comparison of ECG derived respiratory signals and pneumatic bellows for respiratory motion tracking." In 2011 IEEE Nuclear Science Symposium and Medical Imaging Conference (2011 NSS/MIC). IEEE, 2011. http://dx.doi.org/10.1109/nssmic.2011.6153746.

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Avci, Cafer, Ibrahim Delibasoglu, and Ahmet Akbas. "Sleep apnea detection using wavelet analysis of ECG derived respiratory signal." In 2012 International Conference on Biomedical Engineering (ICoBE). IEEE, 2012. http://dx.doi.org/10.1109/icobe.2012.6179019.

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Sadr, Nadi, and Philip de Chazal. "Comparing ECG Derived Respiratory Signals and Chest Respiratory Signal for the Detection of Obstructive Sleep Apnoea." In 2016 Computing in Cardiology Conference. Computing in Cardiology, 2016. http://dx.doi.org/10.22489/cinc.2016.296-336.

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Correa, L. S., E. Laciar, V. Mut, A. Torres, and R. Jane. "Sleep apnea detection based on spectral analysis of three ECG - derived respiratory signals." In 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2009. http://dx.doi.org/10.1109/iembs.2009.5334196.

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