Journal articles: 'ECG-derived respiratory'

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Kontaxis, Spyridon, Jesus Lazaro, Valentina D. A. Corino, Frida Sandberg, Raquel Bailon, Pablo Laguna, and Leif Sornmo. "ECG-Derived Respiratory Rate in Atrial Fibrillation." IEEE Transactions on Biomedical Engineering 67, no. 3 (March 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-channel Holter ECGs to the annotations (860 CSA, 480 MSA) of simultaneously registered polysomnograms. Results: Multivariate combination of the EDR from different ECG leads improved the detection accuracy significantly. When all eight leads were considered, an average instantaneous vertical line length above 5 correctly identified 1126 of the 1340 events (sensitivity 84%) with a total number of 1881 positive detections. Conclusions: We conclude that recurrence plot analysis is a promising tool for detection and delineation of CSA epochs from EDR signals with high time resolution. Moreover, the approach is likewise applicable to directly measured respiratory signals.

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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 (December 25, 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 tested on the data to estimate RR in both the time and frequency domain. Results reveal that: (1) The location of the ECG electrodes between auscultation sites does not impact the estimation of RR, (2) baseline wander and amplitude modulation algorithms outperformed the frequency modulation and band-pass filter algorithms, (3) using frequency domain features to estimate RR can provide more accurate RR except when using the band-pass filter algorithm. These results pave the way for ECG-based RR estimation in miniaturised integrated cardiac screening device.

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Klum, Michael, Mike Urban, Timo Tigges, Alexandru-Gabriel Pielmus, Aarne Feldheiser, Theresa Schmitt, and Reinhold Orglmeister. "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 (April 4, 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 thereof are sparse. We employed our recently presented, multimodal patch stethoscope to estimate Einthoven electrocardiogram (ECG) Lead I and II from a single 55 mm ECG lead. Using the stethoscope and ECG subsystems, the pre-ejection period (PEP) and left ventricular ejection time (LVET) were estimated. ECG-derived respiration techniques were used in conjunction with a novel, phonocardiogram-derived respiration approach to extract respiratory parameters. Medical-grade references were the SOMNOmedics SOMNO HDTM and Osypka ICON-CoreTM. In a study including 10 healthy subjects, we analyzed the performances in the supine, lateral, and prone position. Einthoven I and II estimations yielded correlations exceeding 0.97. LVET and PEP estimation errors were 10% and 21%, respectively. Respiratory rates were estimated with mean absolute errors below 1.2 bpm, and the respiratory signal yielded a correlation of 0.66. We conclude that the estimation of ECG, PEP, LVET, and respiratory parameters is feasible using a wearable, multimodal acquisition device and encourage further research in multimodal signal fusion for respiratory signal estimation.

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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 (September 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 achieved the best agreement between respiration rates derived from directly and indirectly measured respiratory signals.

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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 (September 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 method is presented to estimate the respiratory signal from a single-lead ECG. The 4th order central moments was used to estimate the EDR signal exploiting the change of the R-wave slopes induced by respiration. This method was compared with two approaches by analyzing the Fantasia database from www.physionet.org. Furthermore, the ECG signals of 24 healthy subjects placed in an 3 T MR-scanner were acquired.

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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 (August 7, 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 addition, VT2 was assessed both by the deflection point of ECG-derived respiration and high frequency product. Results showed no statistically significant differences between VT2, and the threshold as determined with high frequency product and ECG-derived respiration (F(2,28)=0.83, p=0.45, η2=0.05). A significant intraclass correlation was observed for ECG-derived respiration (r=0.94) and high frequency product (r=0.95) with VT2. Similarly, Bland Altman analysis showed a considerable agreement between VT2 vs. ECG-derived respiration (mean difference of −0.06 km·h−1, 95% CL: ±0.40) and VT2 vs. high frequency product (mean difference of 0.02 km·h−1, 95% CL: ±0.38). This study suggests that, high frequency product and ECG-derived respiration are indeed reliable heart rate variability indices determining VT2 in a field shuttle run test

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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 (August 1, 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 to determine the optimized respirophasic modulation of the amplitude of the ECG-derived respiratory signal. Instantaneous measurement of respiratory modulation showed an absolute error of 72.55, 147.46, 85.68, 116.62, and 50.89 ml for body surface, CS, LV, RV, and RV-CS leads, respectively. Minute TV estimation demonstrated a more accurate estimation with an absolute error of 69.56, 153.39, 79.33, 122.16, and 48.41 ml for body surface, CS, LV, RV, and RV-CS leads, respectively. The RV-CS and body surface leads provided the most accurate estimations that were within 7 and 10% of the true TV, respectively. Finally, the absolute error of the bipolar RV-CS lead was significantly lower than any other lead configuration ( P < 0.0001). In conclusion, we have demonstrated that ECG-derived respiratory modulation provides an accurate estimation of the TV using intracardiac or body surface signals, without the need for additional hardware.

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Gilfriche, Pierre, Laurent M. Arsac, Yannick Daviaux, Jaime Diaz-Pineda, Brice Miard, Olivier Morellec, and Jean-Marc André. "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 (September 1, 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 was obtained with ECG-derived respiration (EDR) and was used for variable frequency complex demodulation (VFCDM) of R-R intervals to extract RSA. The ability to detect cognitive stress in 27 subjects (athletes and nonathletes) was taken as a quality criterion to compare our method to other HRV analyses: Root mean square of successive differences, Fourier transform, wavelet transform, and scaling exponent. Three computer-based tasks from MATB-II were used to induce cognitive stress. Sympathovagal index (HFnu) computed with our method better discriminates cognitive tasks from baseline, as indicated by P values and receiver operating characteristic curves. Here, transient decreases in respiratory frequency have shown to bias classical HRV indices, while only EDR-VFCDM consistently exhibits the expected decrease in the HFnu index with cognitive stress in both groups and all cognitive tasks. We conclude that EDR-VFCDM is robust against atypical respiratory profiles, which seems relevant to assess variations in mental demand. Given the variety of individual respiratory profiles reported especially in highly trained athletes and patients with chronic respiratory conditions, EDR-VFCDM could better perform in a wide range of applications.

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Schumann, Andy, Marcus Schmidt, Marco Herbsleb, Charlotte Semm, Georg Rose, Holger Gabriel, and Karl-Jürgen Bär. "Deriving respiration from high resolution 12-channel-ECG during cycling exercise." Current Directions in Biomedical Engineering 2, no. 1 (September 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 activity. The analysis of the different test stages revealed an increase of BR errors while subjects were effortful cycling compared to rest. During incremental cycling exercise test the mean absolute error per subjects was 3.4/min. Compared to the results reported in other studies at rest in supine position, this seems adequately accurate. In conclusion, our results indicate that EDR using higher order central moments is suited for monitoring BR during physical activity.

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Lu, Xinyue, Christine Azevedo Coste, Marie-Cécile Nierat, Serge Renaux, Thomas Similowski, and David Guiraud. "Respiratory Monitoring Based on Tracheal Sounds: Continuous Time-Frequency Processing of the Phonospirogram Combined with Phonocardiogram-Derived Respiration." Sensors 21, no. 1 (December 25, 2020): 99. http://dx.doi.org/10.3390/s21010099.

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Patients with central respiratory paralysis can benefit from diaphragm pacing to restore respiratory function. However, it would be important to develop a continuous respiratory monitoring method to alert on apnea occurrence, in order to improve the efficiency and safety of the pacing system. In this study, we present a preliminary validation of an acoustic apnea detection method on healthy subjects data. Thirteen healthy participants performed one session of two 2-min recordings, including a voluntary respiratory pause. The recordings were post-processed by combining temporal and frequency detection domains, and a new method was proposed—Phonocardiogram-Derived Respiration (PDR). The detection results were compared to synchronized pneumotachograph, electrocardiogram (ECG), and abdominal strap (plethysmograph) signals. The proposed method reached an apnea detection rate of 92.3%, with 99.36% specificity, 85.27% sensitivity, and 91.49% accuracy. PDR method showed a good correlation of 0.77 with ECG-Derived Respiration (EDR). The comparison of R-R intervals and S-S intervals also indicated a good correlation of 0.89. The performance of this respiratory detection algorithm meets the minimal requirements to make it usable in a real situation. Noises from the participant by speaking or from the environment had little influence on the detection result, as well as body position. The high correlation between PDR and EDR indicates the feasibility of monitoring respiration with PDR.

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Tu, Yue Wen, Xiao Min Yu, Hang Chen, and Shu Ming Ye. "A Novel Method for the Detection of Sleep Apnea Syndrome Based on Single-Lead ECG Signal." Applied Mechanics and Materials 239-240 (December 2012): 1079–83. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.1079.

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The diagnosis of sleep apnea syndrome (SAS) has important clinical significance for the prevention of hypertension, coronary heart disease, arrhythmias, stroke and other diseases. In this paper, a novel method for the detection of SAS based on single-lead Electrocardiogram (ECG) signal was proposed. Firstly, the R-peak points of ECG recordings were pre-detected to calculate RR interval series and ECG-derived respiratory signal (EDR). Then 40 time- and spectral-domain features were extracted and normalized. Finally, support vector machine (SVM) was employed to these features as a classifier to detect SAS events. The performance of the presented method was evaluated using the MIT-BIH Apnea-ECG database, results show that an accuracy of 95% in train sets and an accuracy of 88% in test sets are achievable.

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Cysarz, Dirk, Roland Zerm, Henrik Bettermann, Matthias Frühwirth, Maximilian Moser, and Matthias Kröz. "Comparison of Respiratory Rates Derived from Heart Rate Variability, ECG Amplitude, and Nasal/Oral Airflow." Annals of Biomedical Engineering 36, no. 12 (October 15, 2008): 2085–94. http://dx.doi.org/10.1007/s10439-008-9580-2.

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Shi, B., S. A. Harding, and P. D. Larsen. "ECG Derived Predictors of Ventricular Tachyarrhythmias in Implantable Cardioverter Defibrillator Patients." Heart, Lung and Circulation 20, no. 6 (June 2011): 408–9. http://dx.doi.org/10.1016/j.hlc.2011.03.087.

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Weiss, Eric H., Omid Sayadi, Priya Ramaswamy, Faisal M. Merchant, Naveen Sajja, Lori Foley, Shawna Laferriere, and Antonis A. Armoundas. "An optimized method for the estimation of the respiratory rate from electrocardiographic signals: implications for estimating minute ventilation." American Journal of Physiology-Heart and Circulatory Physiology 307, no. 3 (August 1, 2014): H437—H447. http://dx.doi.org/10.1152/ajpheart.00039.2014.

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It is well-known that respiratory activity influences electrocardiographic (ECG) morphology. In this article we present a new algorithm for the extraction of respiratory rate from either intracardiac or body surface electrograms. The algorithm optimizes selection of ECG leads for respiratory analysis, as validated in a swine model. The algorithm estimates the respiratory rate from any two ECG leads by finding the power spectral peak of the derived ratio of the estimated root-mean-squared amplitude of the QRS complexes on a beat-by-beat basis across a 32-beat window and automatically selects the lead combination with the highest power spectral signal-to-noise ratio. In 12 mechanically ventilated swine, we collected intracardiac electrograms from catheters in the right ventricle, coronary sinus, left ventricle, and epicardial surface, as well as body surface electrograms, while the ventilation rate was varied between 7 and 13 breaths/min at tidal volumes of 500 and 750 ml. We found excellent agreement between the estimated and true respiratory rate for right ventricular ( R2 = 0.97), coronary sinus ( R2 = 0.96), left ventricular ( R2 = 0.96), and epicardial ( R2 = 0.97) intracardiac leads referenced to surface lead ECGII. When applied to intracardiac right ventricular-coronary sinus bipolar leads, the algorithm exhibited an accuracy of 99.1% ( R2 = 0.97). When applied to 12-lead body surface ECGs collected in 4 swine, the algorithm exhibited an accuracy of 100% ( R2 = 0.93). In conclusion, the proposed algorithm provides an accurate estimation of the respiratory rate using either intracardiac or body surface signals without the need for additional hardware.

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Rizwan, Md Fahim, Rayed Farhad, and Md Hasan Imam. "Support Vector Machine based Stress Detection System to manage COVID-19 pandemic related stress from ECG signal." AIUB Journal of Science and Engineering (AJSE) 20, no. 1 (April 15, 2021): 8–16. http://dx.doi.org/10.53799/ajse.v20i1.112.

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This study represents a detailed investigation of induced stress detection in humans using Support Vector Machine algorithms. Proper detection of stress can prevent many psychological and physiological problems like the occurrence of major depression disorder (MDD), stress-induced cardiac rhythm abnormalities, or arrhythmia. Stress induced due to COVID -19 pandemic can make the situation worse for the cardiac patients and cause different abnormalities in the normal people due to lockdown condition. Therefore, an ECG based technique is proposed in this paper where the ECG can be recorded for the available handheld/portable devices which are now common to many countries where people can take ECG by their own in their houses and get preliminary information about their cardiac health. From ECG, we can derive RR interval, QT interval, and EDR (ECG derived Respiration) for developing the model for stress detection also. To validate the proposed model, an open-access database named "drivedb” available at Physionet (physionet.org) was used as the training dataset. After verifying several SVM models by changing the ECG length, features, and SVM Kernel type, the results showed an acceptable level of accuracy for Fine Gaussian SVM (i.e. 98.3% for 1 min ECG and 93.6 % for 5 min long ECG) with Gaussian Kernel while using all available features (RR, QT, and EDR). This finding emphasizes the importance of including ventricular polarization and respiratory information in stress detection and the possibility of stress detection from short length data(i.e. form 1 min ECG data), which will be very useful to detect stress through portable ECG devices in locked down condition to analyze mental health condition without visiting the specialist doctor at hospital. This technique also alarms the cardiac patients form being stressed too much which might cause severe arrhythmogenesis.

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Jafari Tadi, Mojtaba, Tero Koivisto, Mikko Pänkäälä, and Ari Paasio. "Accelerometer-Based Method for Extracting Respiratory and Cardiac Gating Information for Dual Gating during Nuclear Medicine Imaging." International Journal of Biomedical Imaging 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/690124.

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Both respiratory and cardiac motions reduce the quality and consistency of medical imaging specifically in nuclear medicine imaging. Motion artifacts can be eliminated by gating the image acquisition based on the respiratory phase and cardiac contractions throughout the medical imaging procedure. Electrocardiography (ECG), 3-axis accelerometer, and respiration belt data were processed and analyzed from ten healthy volunteers. Seismocardiography (SCG) is a noninvasive accelerometer-based method that measures accelerations caused by respiration and myocardial movements. This study was conducted to investigate the feasibility of the accelerometer-based method in dual gating technique. The SCG provides accelerometer-derived respiratory (ADR) data and accurate information about quiescent phases within the cardiac cycle. The correct information about the status of ventricles and atria helps us to create an improved estimate for quiescent phases within a cardiac cycle. The correlation of ADR signals with the reference respiration belt was investigated using Pearson correlation. High linear correlation was observed between accelerometer-based measurement and reference measurement methods (ECG and Respiration belt). Above all, due to the simplicity of the proposed method, the technique has high potential to be applied in dual gating in clinical cardiac positron emission tomography (PET) to obtain motion-free images in the future.

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Joshi, Rohan, Deedee Kommers, Laurien Oosterwijk, Loe Feijs, Carola van Pul, and Peter Andriessen. "Predicting Neonatal Sepsis Using Features of Heart Rate Variability, Respiratory Characteristics, and ECG-Derived Estimates of Infant Motion." IEEE Journal of Biomedical and Health Informatics 24, no. 3 (March 2020): 681–92. http://dx.doi.org/10.1109/jbhi.2019.2927463.

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Wang, Tao, Changhua Lu, Guohao Shen, and Feng Hong. "Sleep apnea detection from a single-lead ECG signal with automatic feature-extraction through a modified LeNet-5 convolutional neural network." PeerJ 7 (September 20, 2019): e7731. http://dx.doi.org/10.7717/peerj.7731.

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Sleep apnea (SA) is the most common respiratory sleep disorder, leading to some serious neurological and cardiovascular diseases if left untreated. The diagnosis of SA is traditionally made using Polysomnography (PSG). However, this method requires many electrodes and wires, as well as an expert to monitor the test. Several researchers have proposed instead using a single channel signal for SA diagnosis. Among these options, the ECG signal is one of the most physiologically relevant signals of SA occurrence, and one that can be easily recorded using a wearable device. However, existing ECG signal-based methods mainly use features (i.e. frequency domain, time domain, and other nonlinear features) acquired from ECG and its derived signals in order to construct the model. This requires researchers to have rich experience in ECG, which is not common. A convolutional neural network (CNN) is a kind of deep neural network that can automatically learn effective feature representation from training data and has been successfully applied in many fields. Meanwhile, most studies have not considered the impact of adjacent segments on SA detection. Therefore, in this study, we propose a modified LeNet-5 convolutional neural network with adjacent segments for SA detection. Our experimental results show that our proposed method is useful for SA detection, and achieves better or comparable results when compared with traditional machine learning methods.

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Abreu, Rodolfo, Sandro Nunes, Alberto Leal, and Patrícia Figueiredo. "Physiological noise correction using ECG-derived respiratory signals for enhanced mapping of spontaneous neuronal activity with simultaneous EEG-fMRI." NeuroImage 154 (July 2017): 115–27. http://dx.doi.org/10.1016/j.neuroimage.2016.08.008.

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Lu, Guo Hua, Fang Fang, Xi Jing Jing, Xiao Yu, and Jian Qi Wang. "A Contact-Free Monitor of Human’S Vital Signs." Applied Mechanics and Materials 138-139 (November 2011): 1063–66. http://dx.doi.org/10.4028/www.scientific.net/amm.138-139.1063.

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Heart rates and breathing rates are widely used to assess the health state of human in clinic. Tranditional method uses eletrodes or sensors touching the body to measure electrocardiography (ECG) and respiratory signals.A vital signs monitor via a micorwave sensor was disscused to contact-free measurement of the heart rate and breathing rate. Comparison of vital signs derived from the microwave sensor and tranditional contact monitor demonstrated that there were no significant differences between each other, which suggested the contact-free vital signs monitor may prove a practical alternative method to measure heart rate and breathing rate.

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Adeel, Muhammad, Erol Nargileci, Ahmed Abdulbaki, and Craig McPherson. "A PROPOSED NEW ECG-DERIVED SCORING INDEX TO DIAGNOSE MASSIVE OR SUBMASSIVE PULMONARY EMBOLISM." Chest 156, no. 4 (October 2019): A376. http://dx.doi.org/10.1016/j.chest.2019.08.415.

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Tinoco, Adelita, David W. Mortara, Xiao Hu, Cass Piper Sandoval, and Michele M. Pelter. "ECG derived Cheyne–Stokes respiration and periodic breathing are associated with cardiorespiratory arrest in intensive care unit patients." Heart & Lung 48, no. 2 (March 2019): 114–20. http://dx.doi.org/10.1016/j.hrtlng.2018.09.003.

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Pinheiro, E., O. Postolache, and P. Girão. "Contactless Impedance Cardiography Using Embedded Sensors." Measurement Science Review 13, no. 3 (June 1, 2013): 157–64. http://dx.doi.org/10.2478/msr-2013-0025.

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Impedance cardiography is a technique developed with the intent of monitoring cardiac output. By inspecting a few properties of the obtained signal (impedance cardiogram (ICG), the left ventricular ejection time can be derived with certainty, and an estimate of cardiac output is available. This signal is nowadays used in non-invasive monitoring, requiring the placement of electrodes over the subject’s skin, either ECG-type or in the form of encircling bands. The work here reported describes the implementation steps and the results obtained when embedding the ICG circuitry in a wheelchair’s backrest. The subject is seated normally, is normally dressed, and is completely unaware that monitoring is taking place. That means that the variation of tenths of ohm produced due to the cardiac cycle has to be detected with electrodes having substantial coupling impedance. Contactless ICG with embedded sensors was developed and tested on fourteen healthy subjects. The signal was always acquired, although respiratory activity is also important, constituting a noteworthy innovation in the area.

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Cooke, William H., Gilbert Moralez, Chelsea R. Barrera, and Paul Cox. "Digital infrared thermographic imaging for remote assessment of traumatic injury." Journal of Applied Physiology 111, no. 6 (December 2011): 1813–18. http://dx.doi.org/10.1152/japplphysiol.00726.2011.

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The purpose of this study was to test the hypotheses that digital infrared thermographic imaging (DITI) during simulated uncontrolled hemorrhage will reveal 1) respiratory rate and 2) changes of skin temperature that track reductions of stroke volume. In 45 healthy volunteers (25 men and 20 women), we recorded the ECG, finger photoplethysmographic arterial pressure, respiratory rate (pneumobelt and DITI of the nose), cardiac output (inert rebreathing), and skin temperature of the forehead during lower body negative pressure (LBNP) at three continuous decompression rates; slow (−3 mmHg/min), medium (−6 mmHg/min), and fast (−12 mmHg/min) to an ending pressure of −60 mmHg. Respiratory rates calculated from the pneumobelt (14.7 ± 0.9 breaths/min) and DITI (14.9 ± 1.2 breaths/min) were not different ( P = 0.21). LBNP induced an average stroke volume reduction of 1.3 ml/mmHg regardless of decompression speed. Maximal reductions of stroke volume and forehead temperature were −100 ± 12 ml and −0.32 ± 0.12°C (slow), −86 ± 12 ml and −0.74 ± 0.27°C (medium), and −78 ± 5 ml and −0.17 ± 0.02°C (fast). Changes of forehead temperature as a function of changes of stroke volume were best described by a quadratic fit to the data (slow R2 = 0.95; medium R2 = 0.89; and fast R2 = 0.99).Our results suggest that a thermographic camera may prove useful for the remote assessment of traumatically injured patients. Life sign detection may be determined by verifying respiratory rate. Determining the magnitude and rate of hemorrhage may also be possible based on future algorithms derived from associations between skin temperature and stroke volume.

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Koteska, Bojana, Anastas Mishev, and Ljupco Pejov. "Quantitative Measurement of Scientific Software Quality: Definition of a Novel Quality Model." International Journal of Software Engineering and Knowledge Engineering 28, no. 03 (March 2018): 407–25. http://dx.doi.org/10.1142/s0218194018500146.

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This paper presents a novel quality model, which provides a quantitative assessment of the attributes evaluated at each stage of development of scientific applications. This model is defined by selecting a set of attributes and metrics that affect the quality of applications. It is based on the established quality standards. The practical application and verification of the quality model is confirmed by two case studies. The first is an application for solving one-dimensional and two-dimensional Schrödinger equations, using the discrete variables representation method. The second is an application for calculating an ECG-derived heart rate and respiratory rate. The first application follows a development model for scientific applications, which includes some software engineering practices. The second application does not use a specific development model, rather, it is developed ad hoc. The quality of the applications is evaluated through comparative analyses using the proposed model. Based on software quality metrics, the results of this study indicate that the application for solving one-dimensional and two-dimensional Schrödinger equations produces more desirable results.

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Buchhorn, Reiner. "An Algorithm to Predict Life-Threatening Complications using Heart Rate Variability and the Circadian Heart Rate Difference with a Special Interest on Covid-19, Sudep Children with Congenital Heart Disease and Obesity." Journal of Biomedical Engineering and Medical Imaging 7, no. 4 (August 1, 2020): 01–10. http://dx.doi.org/10.14738/jbemi.74.8589.

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Corona virus disease (COVID-19) has been declared as a pandemic by the WHO with a global mortality rate of about 3.4%. More recently the neuroinvasive potential of SARS-CoV2 was emphasized as a potential cause for respiratory failure. Such pathophysiology has been investigated in sudden unexplained death in epilepsy (SUDEP) including functional neuroimaging that demonstrates alterations to networks involved in central autonomic and respiratory control located in the brainstem. For risk stratification in these patients, one method may be heart rate and heart rate variability (HRV) monitoring. Method: For a better understanding, we compare HRV monitoring in two cases; 1.) Twenty Holter ECGs of a boy with generalized tonic-clonic seizures up to his dead at the age of 10.5 years with special interest on an acute respiratory failure at the age of 5.4 years. 2.) Thirty one Holter ECGs of a 58-year old pediatric cardiologist who survived an infection with COVID-19. During his disease 24-hour Holter electrocardiography (ECG) was performed continuously over 10 days. Moreover, 24-hour Holter ECGs from the last 10 years were available. The derived algorithm that depends on the global heart rate variability and circadian heart rate difference was proofed in 151 healthy children, 26 children with a fatal outcome or transplantation, 151 patients with operated congenital heart disease, 130 obese children and healthy adult data from literature. Results: In both cases we observe a decline of the global heart rate variability SDNN together with a loss of the circadian heart rate difference. The derived algorithm differentiate healthy children from children with a fatal outcome. The algorithm identify 7.3% of 151 patients with operated congenital heart disease and 5.4% of children with obesity as candidates for COVID-19 complications. Conclusions: A sudden decline of HRV together with a loss of the circadian heart rate difference may indicate a life-threatening complication in critical illness.

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Walters, T., A. Teh, S. Spence, K. Halloran, P. Kistler, J. Morton, and J. Kalman. "A Study of the Atrial Fibrillatory Cycle Length Derived From the 12-Lead ECG: Longer Cycle Length Activity is Associated With More Advanced Electroanatomic Remodelling." Heart, Lung and Circulation 22 (January 2013): S104. http://dx.doi.org/10.1016/j.hlc.2013.05.248.

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Sheinkopf, Stephen J., A. Rebecca Neal-Beevers, Todd P. Levine, Cynthia Miller-Loncar, and Barry Lester. "Parasympathetic Response Profiles Related to Social Functioning in Young Children with Autistic Disorder." Autism Research and Treatment 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/868396.

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Psychophysiology studies of heart rate and heart rate variability can be employed to study regulatory processes in children with autism. The objective of this study was to test for differences in respiratory sinus arrhythmia (RSA; a measure of heart rate variability) and to examine the relationship between physiologic responses and measures of social behavior. Participants included 2- to 6-year-old children with Autistic Disorder and children without autism. Heart rate and RSA were derived from ECG recordings made during a baseline period and then a stranger approach paradigm. Social and adaptive behavior was assessed by parent report. Groups did not differ in mean heart rate or RSA at baseline or in response to social challenge. However, children with autism were more likely to show a physiologic response to intrusive portions of the stranger approach than to less intrusive portions of this procedure. Nonautistic children were equally likely to respond to intrusive and less intrusive social events. Within the autistic group, physiologic response to the intrusive stranger approach corresponded to higher ratings of social adaptive behaviors. These results suggest that physiologic responses to social challenge may help understand differences in social behavioral outcomes in children with autism.

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Hopf, Hans-Bernd, Andreas Skyschally, Gerd Heusch, and Jurgen Peters. "Low-frequency Spectral Power of Heart Rate Variability Is Not a Specific Marker of Cardiac Sympathetic Modulation." Anesthesiology 82, no. 3 (March 1, 1995): 609–19. http://dx.doi.org/10.1097/00000542-199503000-00002.

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Background Heart rate variability in the frequency domain has been proposed to reflect cardiac autonomic control. Therefore, measurement of heart rate variability may be useful to assess the effect of epidural anesthesia on cardiac autonomic tone. Accordingly, the effects of preganglionic cardiac sympathetic blockade by segmental epidural anesthesia were evaluated in humans on spectral power of heart rate variability. Specifically, the hypothesis that cardiac sympathetic blockade attenuates low-frequency spectral power, assumed to reflect cardiac sympathetic modulation, was tested. Methods Ten subjects were studied while supine and during a 15-min 40 degrees head-up tilt both before and after cardiac sympathetic blockade by segmental thoracic epidural anesthesia (sensory block: C6-T6). ECG, arterial pressure, and respiratory excursion (Whitney gauge) were recorded, and a fast-Fourier-transformation was applied to 512-s data segments of heart rate derived from the digitized ECG at the end of each intervention. Results With cardiac sympathetic blockade alone and the subjects supine, both low-frequency (LF, 0.06-0.15 Hz) and high-frequency (HF, 0.15-0.80 Hz) spectral power remained unchanged. During tilt, epidural anesthesia attenuated the evoked increase in heart rate (+11.min-1 +/- 7 SD vs. +6 +/- 7, P = 0.024). However, while during tilt cardiac sympathetic blockade significantly decreased the LF/HF ratio (3.68 +/- 2.52 vs. 2.83 +/- 2.15, P = 0.041 vs. tilt before sympathetic blockade), a presumed marker of sympathovagal interaction, absolute and fractional LF and HF power did not change. Conclusions Although preganglionic cardiac sympathetic blockade reduced the LF/HF ratio during tilt, it did not alter spectral power in the LF band during rest or tilt. Accordingly, low-frequency spectral power is unlikely to specifically reflect cardiac sympathetic modulation in humans.

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Long, Xi, Pedro Fonseca, Reinder Haakma, Ronald M. Aarts, and Jerome Foussier. "Spectral Boundary Adaptation on Heart Rate Variability for Sleep and Wake Classification." International Journal on Artificial Intelligence Tools 23, no. 03 (May 28, 2014): 1460002. http://dx.doi.org/10.1142/s0218213014600021.

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A method of adapting the boundaries when extracting the spectral features from heart rate variability (HRV) for sleep and wake classification is described. HRV series can be derived from electrocardiogram (ECG) signals obtained from single-night polysomnography (PSG) recordings. Conventionally, the HRV spectral features are extracted from the spectrum of an HRV series with fixed boundaries specifying bands of very low frequency (VLF), low frequency (LF), and high frequency (HF). However, because they are fixed, they may fail to accurately reflect certain aspects of autonomic nervous activity which in turn may limit their discriminative power, e.g. in sleep and wake classification. This is in part related to the fact that the sympathetic tone (partially reflected in the LF band) and the respiratory activity (modulated in the HF band) vary over time. In order to minimize the impact of these variations, we adapt the HRV spectral boundaries using time-frequency analysis. Experiments were conducted on a data set acquired from two groups with 15 healthy and 15 insomnia subjects each. Results show that adapting the HRV spectral features significantly increased their discriminative power when classifying sleep and wake. Additionally, this method also provided a significant improvement of the overall classification performance when used in combination with other HRV non-spectral features. Furthermore, compared with the use of actigraphy, the classification performed better when combining it with the HRV features.

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Andreozzi, Emilio, Jessica Centracchio, Vincenzo Punzo, Daniele Esposito, Caitlin Polley, Gaetano D. Gargiulo, and Paolo Bifulco. "Respiration Monitoring via Forcecardiography Sensors." Sensors 21, no. 12 (June 9, 2021): 3996. http://dx.doi.org/10.3390/s21123996.

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In the last few decades, a number of wearable systems for respiration monitoring that help to significantly reduce patients’ discomfort and improve the reliability of measurements have been presented. A recent research trend in biosignal acquisition is focusing on the development of monolithic sensors for monitoring multiple vital signs, which could improve the simultaneous recording of different physiological data. This study presents a performance analysis of respiration monitoring performed via forcecardiography (FCG) sensors, as compared to ECG-derived respiration (EDR) and electroresistive respiration band (ERB), which was assumed as the reference. FCG is a novel technique that records the cardiac-induced vibrations of the chest wall via specific force sensors, which provide seismocardiogram-like information, along with a novel component that seems to be related to the ventricular volume variations. Simultaneous acquisitions were obtained from seven healthy subjects at rest, during both quiet breathing and forced respiration at higher and lower rates. The raw FCG sensor signals featured a large, low-frequency, respiratory component (R-FCG), in addition to the common FCG signal. Statistical analyses of R-FCG, EDR and ERB signals showed that FCG sensors ensure a more sensitive and precise detection of respiratory acts than EDR (sensitivity: 100% vs. 95.8%, positive predictive value: 98.9% vs. 92.5%), as well as a superior accuracy and precision in interbreath interval measurement (linear regression slopes and intercepts: 0.99, 0.026 s (R2 = 0.98) vs. 0.98, 0.11 s (R2 = 0.88), Bland–Altman limits of agreement: ±0.61 s vs. ±1.5 s). This study represents a first proof of concept for the simultaneous recording of respiration signals and forcecardiograms with a single, local, small, unobtrusive, cheap sensor. This would extend the scope of FCG to monitoring multiple vital signs, as well as to the analysis of cardiorespiratory interactions, also paving the way for the continuous, long-term monitoring of patients with heart and pulmonary diseases.

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de Vries, Jantina, Alessandro Rossi, Ruben De Francisco, Soukaina Adnane, Hartmut Schneider, and Daniela Andries. "402 A wireless patch-based polysomnography system for sleep studies: effect of the 2016 AASM rules on AHI in normal individuals." Sleep 44, Supplement_2 (May 1, 2021): A160. http://dx.doi.org/10.1093/sleep/zsab072.401.

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Abstract Introduction Current home sleep test (HST) devices are limited by an absence of EEG, or by being too cumbersome to use. We developed a wireless PSG system (Onera Health, NL) consisting of four disposable patches to record EEG, EOG, EMG, SaO2, ECG, bioimpedance derived respiratory airflow and effort, airflow via nasal cannula, snoring sounds, body position, actigraphy, and leg movements. Signals are stored on reusable electronic modules attached to each patch. Methods We measured PSG hook-up time in 15 healthy laypersons (6 male, 9 female, age 18-to-70 yrs, BMI 29.7±5.2 kg/m2). We also enrolled 6 additional asymptomatic healthy volunteers (2 male, 4 female, age 27-to-33 yrs, BMI 24.3±5.7 kg/m2) with history of occasional snoring, on which we scored the apnea-hypopnea index (AHI) using data from our patch-based PSG system recorded at home. We evaluated scoring using the 2016 AASM rules for hypopneas in comparison to the 2007 AASM rules requiring a greater than 3% fall in SaO2 for obstructive hypopneas. Results Mean hook-up time for applying all four patches and electronic modules was 4:42 ± 1:20 min. Mean home sleep efficiency was 89.5 SE 1.9% with an average REM% of 20 SE 6.7%. When comparing the 2016 vs 2007 AASM rules for scoring hypopneas, the AHI increased more than threefold during NREM (9.0 SE 2.0/h vs 2.7 SE 0.8/h; p<0.03) and minimally during REM (11.7 SE 2.3/h and 7.1/h SE 1.8/h; p<0.01), implying an overall increase in the AHI from 3.7 SE 0.8/h to 9.9 SE 1.9/h; p<0.02. One subject changed AHI category from normal to mild (3.6 to 14.4/h), another from mild to moderate (12.7 to 26.3/h) using the 2016 AASM rules. Conclusion Our wireless patch-based PSG system is an easy solution for sleep studies at home or in the sleep lab, lowering the burden to conduct large scale epidemiologic sleep studies. The presence of standard EEG signals allows to determine NREM and REM statistics, respiratory and non-respiratory arousal indices, AHI and RERA’s by sleep stages. Preliminary study results show that using cortical arousal criteria for hypopneas, the AHI increase is more pronounced in NREM compared to REM sleep. Support (if any):

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Hagey, Anne, Jeffrey E. Lancet, Varghese Palath, Andrew H. Wei, Martin Lackmann, Jorge E. Cortes, Andrew Boyd, et al. "A Recombinant Antibody to EphA3 for the Treatment of Hematologic Malignancies: Research Update and Interim Phase 1 Study Results." Blood 118, no. 21 (November 18, 2011): 4893. http://dx.doi.org/10.1182/blood.v118.21.4893.4893.

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Abstract Abstract 4893 EphA3 is a receptor tyrosine kinase important in fetal development but apparently not in healthy adults. It is expressed in hematologic malignancies including AML, CML, MDS, MPN and Multiple Myeloma and in a range of solid tumors in particular in the stromal and vascular tissue. KB004 is a high-affinity non-fucosylated, recombinant antibody to EphA3 that triggers apoptosis and has potent antibody-dependent cellular cytotoxicity (ADCC) activity against EphA3+ cells. Direct apoptosis of EphA3+ leukemic cells ex vivo was demonstrated at antibody concentrations of 10μg/mL or greater. Expression on a CD34+ CD38− CD123+ cell population in primary AML patient bone marrow, and inhibition of long-term culture initiating cells by KB004, indicates that EphA3 may be present on leukemic stem cells (Palath et al 2010). EphA3 expression in bone marrow biopsies from AML patients was characterized by immunohistochemistry (IHC). EphA3 was detected on tumor cells by IHC in 4/10 samples analyzed. EphA3 was also present on the vasculature in AML bone marrow (6/10 samples) but not in similar tissues in bone marrow biopsies (n=2) from non-leukemic individuals. This suggests tumor vasculature as a potential further therapeutic target for KB004 in AML in addition to targeting leukemia cells directly. We are further characterizing the expression level of EphA3 in different hematologic malignancies, tumor microenvironment, and at various stages of disease progression from primary human samples. The Cynomolgus macaque was selected as a relevant species for toxicity testing since KB004 binds with equivalent affinity to human and Cynomolgus EphA3 and CD16. IHC studies demonstrated the absence of cellular expression of EphA3 in normal human or Cynomolgus monkey tissues. KB004 administered to Cynomolgus monkeys (n=44) twice weekly for 13 weeks at doses up to 100 mg/kg was well tolerated and there were no clinical or pathology adverse findings. Cardiovascular, respiratory and central nervous system functions were measured in primates after KB004 dosing 5 times over 15 days to reach steady-state exposure at doses of 10mg/kg (n=4) or 100 mg/kg (n=4). There were no KB004-related effects on body weight, food consumption, mean arterial pressure, heart rate, body temperature, neurological parameters, respiration rate, oxygen saturation, or blood gas parameters, or changes in serum concentrations of Troponin I. Qualitative evaluation of the electrocardiogram (ECG) did not reveal any electrocardiographic abnormalities and there were no effects on measured ECG intervals (i.e., duration of the QT and RR intervals, derived QTc values). The effect of KB004 on wound healing was tested in a primate incisional wound healing model in the Cynomolgus monkey. No statistically significant differences in healing were detected between control and KB004 (2×10 or 2×100mg/kg) treated animals (n=24). A Phase I clinical study has been initiated in subjects with hematologic malignancies including AML, CML, ALL, MDS and MPN. Subjects are being assessed for EphA3 protein expression at study entry and at various time points throughout the treatment period. Study objectives are to determine a maximum tolerated dose, examine the safety and tolerability profile of KB004, obtain pharmacokinetic data, describe the immunogenicity profile, and explore cell subpopulations and pharmacodynamic effects of treatments with KB004. This is an open-label, repeat administration study of weekly IV dosing of up to 17 cycles (3 doses per 21-day cycle). Dosing levels are scheduled for 20 mg (∼0.3 mg/kg), 70 mg (∼1 mg/kg), 200 mg (∼3 mg/kg) and 700 mg (∼10 mg/kg). Therapeutic antibody levels (target level 10μg/mL) are predicted to be achieved from the first dose cohort for a portion of the dosing interval. The higher doses should provide blood levels in excess of 10 μg/mL for the entire one-week dosing interval. The first cohort (n=3) has been successfully completed, and a subject with AML remains on study having received 8 doses to date. Recruitment of the next dose cohort is ongoing. Pharmacokinetic data and tumor expression profiles will be presented. Disclosures: Hagey: KaloBios Pharmaceuticals, Inc.: Employment, Equity Ownership. Lancet:KaloBios Pharmaceuticals, Inc.: Research Funding. Palath:KaloBios Pharmaceuticals, Inc.: Employment, Equity Ownership. Wei:KaloBios Pharmaceuticals, Inc.: Research Funding. Lackmann:KaloBios Pharmaceuticals, Inc.: Research Funding. Cortes:KaloBios Pharmaceuticals, Inc.: Research Funding. Boyd:KaloBios Pharmaceuticals, Inc.: Research Funding. Shochat:KaloBios Pharmaceuticals, Inc.: Employment, Equity Ownership. Yarranton:KaloBios Pharmaceuticals, Inc.: Employment, Equity Ownership. Bebbington:KaloBios Pharmaceuticals, Inc.: Employment, Equity Ownership. Leff:KaloBios Pharmaceuticals, Inc.: Employment, Equity Ownership.

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Dutta, Disha N., Reshmi Das, and Saurabh Pal. "Automated Real-Time Processing of Single Lead Electrocardiogram for Simultaneous Heart Rate and Respiratory Rate Monitoring." Journal of Medical Devices 11, no. 2 (May 3, 2017). http://dx.doi.org/10.1115/1.4035982.

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In this article, the design and development of a real-time heart rate (HR) and respiratory rate (RR) monitoring device is reported. The proposed device is designed to impose minimum data acquisition hazards on the subject. In standard bedside monitors, HR and RR are derived from electrocardiogram (ECG) and respiration signals, respectively, and different electrodes are required for capturing the 12-lead ECG and respiration via a chest belt, which is cumbersome for patients and healthcare providers. Respiration signal has an impact on ECG due to anatomical proximity of the heart and lung, and ECG is modulated by respiration, a phenomenon known as respiratory sinus arrhythmia (RSA). In the proposed method, the ECG signal is acquired using clip electrodes at the wrists and the respiration signal is extracted from the ECG using an Arduino Uno microcontroller-based real-time processing of ECG. RR is then derived from ECG-derived respiration (EDR). The prototype is tested on healthy subjects and compared to measurements taken using a standard MP45 data acquisition device associated with a Biopac Student Lab (BSL). A mean percentage error of 5.54 ± 8.48% was observed under normal breathing conditions and an error of −3.41 ± 3.27% was observed for a single subject tested under a variety of breathing conditions, such as resting, stair-climbing, and paced breathing. The proposed algorithm can also be used in combination with standard ECG monitoring systems to measure HR and RR, without any data acquisition hazard to the subject.

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Hidalgo-Muñoz, Antonio, Adolphe Béquet, Mathis Astier-Juvenon, Guillaume Pépin, Alexandra Fort, Christophe Jallais, Hélène Tattegrain, and Catherine Gabaude. "Determination of cognitive workload variation in driving from ECG derived respiratory signal and heart rate." Frontiers in Human Neuroscience 12 (2018). http://dx.doi.org/10.3389/conf.fnhum.2018.227.00058.

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Sinnecker, Daniel, Petra Barthel, Alexander Müller, Karl-Ludwig Laugwitz, and Georg Schmidt. "Abstract 17230: Respiratory Sinus Arrhythmia Quantified from Standard ECG for Risk Stratification of Post-Infarction Patients." Circulation 130, suppl_2 (November 25, 2014). http://dx.doi.org/10.1161/circ.130.suppl_2.17230.

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Objectives: Respiratory sinus arrhythmia (RSA) reflects modulation of the sinoatrial node discharge frequency by the autonomic nervous system. Impaired autonomic function is associated with adverse outcome in cardiac patients. We developed a method for calculating RSA from standard ECG recordings and investigated its association with mortality in survivors of acute myocardial infarction. Methods: Consecutive patients (n=941, mean age 61 years, 19% female) presenting with acute myocardial infarction and sinus rhythm were enrolled between May 2000 and March 2005 and followed up until August 2010. The main study outcome was 5-year all-cause mortality. Patients underwent 30-minute ECG recordings. Auxiliary respiratory muscle activity derived from high pass-filtered ECG signal was used to define respiratory phase. The influence of expiration on RR intervals (RRI) was assessed by bivariate phase-rectified signal averaging (PRSA), and RSA PRSA was quantified by Haar wavelet analysis. RSA PRSA ≤0 was defined as abnormal. Results: During the follow-up, 72 patients died. Five-year mortality rates in patients with normal and abnormal RSA PRSA were 4% and 14%, respectively. Under univariable analysis, RSA PRSA was a significant predictor of death (p<0.001), as were GRACE score (p<0.001), LVEF (p<0.001), and the presence of diabetes mellitus (p<0.001). Under multivariable analysis, RSA PRSA , GRACE score, LVEF, and diabetes mellitus were independently and significantly associated with outcome. Conclusions: Respiratory sinus arrhythmia, quantified by bivariate PRSA from standard ECG recordings, is an independent predictor of mortality risk in post-infarction patients.

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Kellerová, E., V. Szathmáry, G. Kozmann, K. Haraszti, and Z. Tarjányi. "Spontaneous variability and reactive postural beat-to-beat changes of integral ECG body surface potential maps." Physiological Research, 2010, 887–96. http://dx.doi.org/10.33549/10.33549/physiolres.931907.

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There is virtually no information on spontaneous variability of ECG body surface potential maps (BSPMs) and on dynamics of their reactive changes in healthy subjects. This study evaluated quantitatively the depolarization (QRS) and repolarization (QRST) parameters derived from the respective integral BSPMs, constructed beat-to-beat, from continual body surface ECG records in 9 healthy men resting supine, during head-up tilting and sitting. Spontaneous variability of the BSPMs parameters, both at rest and during postural reactions, was characterized by significant respiratory and low frequency oscillations, more pronounced when related to repolarization. Head-up tilting and sitting-up evoked significant decrease in the QRST-BSPM amplitudes, widening of the angle α and reduction of nondipolarity indexes, compared to the respective supine values. All these changes were gradual, characterized by transition phenomena and prolonged after-effects. Tilting back to horizontal restored the resting supine values. The postural effects on depolarization were individually more variable and in the average showed a minimal QRS-BSPM amplitude increase. Beat-to-beat analysis of a train of ECG BSPMs provided the first evidence of spontaneous, non-random, respiratory and low frequency oscillations of the ventricular repolarization pattern, and the first insight into the dynamics of body posture associated changes in ventricular recovery.

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McCullough, Stephen, Parag Goyal, Udhay Krishnan, Adam Vohra, Jennifer Huang, Lisa Zhang, Justin Choi, Monika M. Safford, and Peter M. Okin. "Abstract 16821: An ECG Derived Risk Score Predicts In-Hospital Death in Patients With COVID-19." Circulation 142, Suppl_3 (November 17, 2020). http://dx.doi.org/10.1161/circ.142.suppl_3.16821.

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Introduction: COVID-19 is a respiratory syndrome with high rates of mortality, and findings from the ECG on hospital presentation have been shown to increase the odds of death. We thus hypothesized that findings from the presenting ECG could discriminate the risk of death in high risk subgroups, and sought to create an ECG risk score for death in COVID-19. Methods: We performed a retrospective cohort study in patients with COVID-19 who had an ECG at or near hospital admission. Clinical characteristics were manually abstracted from the electronic health record; ECG data were digitally extracted from the first ECG in each patient, and Bazett-corrected QT interval and ST segment deviation at the M-point (STm, in μV) were quantified in all 12 leads. Our primary outcome was death. Results: 710 patients who presented to a large teaching hospital with COVID-19 underwent an ECG. The mean age was 63 ± 16 years, 37% were women, 62% of patients were non-white, and 56% had hypertension; 78 (11%) died. In a multivariable logistic regression that included age, ECG, and clinical characteristics, the presence of one or more atrial premature contractions (OR=3.56, 95% CI 1.80-7.02, p<0.001), a right bundle branch block or intraventricular block (OR=2.73, 95% CI 1.41-5.32, p=0.003), maximal STm in V5 or V6 (STmV5V6) ≤ -50 μV (OR=3.01, 95% CI 1.41-6.41, p=0.004), STmV2 <0 μV (OR=3.41, 95% CI 1.88-6.18, p<0.001), and QTc ≥480 ms (OR=2.84, 95% CI 1.52-5.29, p=0.001) predicted death. When each variable was assigned a point value of 1, in additive fashion an ECG score=1 or ≥2 similarly predicted death (OR=4.49, 95% CI 2.17-9.25, p<0.001 and OR=11.23, 95% CI 5.27-23.93, p<0.001, respectively), and discriminated risk within high risk age groups (<60, 70-80, >80, Figure ). Conclusions: A simple ECG risk score (including APCs, RBBB/IVB, STmV5V6 ≤ -50 μV, STmV2 <0 μV, and QTc ≥480 ms) on initial hospitalization predicted in hospital death in COVID-19, and further discriminated risk of death in high risk age groups.

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Ebrahimi, Farideh, Seyed Kamaledin Setarehdan, Radek Martinek, and Homer Nazeran. "Comparative Analysis of the Discriminative Capacity of EEG, Two ECG-Derived and Respiratory Signals in Automatic Sleep Staging." Advances in Electrical and Electronic Engineering 15, no. 3 (October 1, 2017). http://dx.doi.org/10.15598/aeee.v15i3.2182.

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Cavallo, Armando Ugo, Emanuele Muscogiuri, Marco Forcina, Antonio Colombo, Flavio Fiore, and Massimiliano Sperandio. "Trans-septal course of anomalous left main coronary artery originating from single right coronary ostium presenting with atrial fibrillation in a severely obese patient: a case report." Egyptian Heart Journal 72, no. 1 (September 21, 2020). http://dx.doi.org/10.1186/s43044-020-00093-x.

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Abstract Background To present a case of anomalous origin of the left coronary artery evaluated with invasive coronary angiography (ICA) and ECG-gated coronary computed tomography (CCT). Case presentation A patient (55 years old, male) with a past medical history of respiratory failure and atrial fibrillation underwent ICA to rule out coronary artery disease. Subsequently, the patient underwent ECG-gated CCT to evaluate a suspected anomalous aortic origin of the left coronary artery, since the interventional cardiologist was not able to properly identify the left coronary artery and its distal branches. CCT showed left coronary artery originating from the right coronary Valsalva sinus, coursing within the interventricular septum and emerging at the middle segment of the interventricular sulcus, where the left anterior descending and circumflex arteries originated. Conclusion The case we presented highlights the value of ECG-gated CCT in the evaluation of coronary anomaly anatomy and thus risk stratification derived by proper coronary anatomy assessment. Although ICA was not helpful in the diagnosis, it also has a pivotal role regarding the therapeutic management of this condition.

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Laczika, Klaus, Oliver P. Graber, Gerhard Tucek, Alfred Lohninger, Nikolaus Fliri, Gertraud Berka-Schmid, Eva K. Masel, and Christoph C. Zielinski. "“Il flauto magico” still works: Mozart’s secret of ventilation." Multidisciplinary Respiratory Medicine 8 (March 19, 2019). http://dx.doi.org/10.4081/mrm.2013.498.

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Background: Synchronisation/coupling between respiratory patterns and musical structure. Methods: Healthy professional musicians and members of the audience were studied during a performance of W.A. Mozart’s Piano Concerto KV 449. Electrocardiogram (ECG)/Heart Rate Variability (HRV) data recording (Schiller: MedilogWAR12, ECG-channels: 3, sampling rate: 4096 Hz, 16 Bit) was carried out and a simultaneous synchronized high definition video/audio recording was made. The breathing-specific data were subsequently extracted using Electrocardiogram-derived respiration (EDR; Software: Schiller medilogWDARWIN) from the HRV data and overlaid at the same time onto the musical score using FINALE 2011 notation software and the GIMP 2.0 graphics programme. The musical score was graphically modified graphically so that the time code of the breathing signals coincided exactly with the notated musical elements. Thus a direct relationship could be produced between the musicians’ breathing activity and the musical texture. In parallel with the medical/technical analysis, a music analysis of the score was conducted with regard to the style and formal shaping of the composition. Results: It was found that there are two archetypes of ideally typical breathing behaviour in professional musicians that either drive the musical creation, performance and experience or are driven by the musical structure itself. These archetypes also give rise to various states of synchronisation and regulation between performers, audience and the musical structure. Conclusions: There are two archetypes of musically-induced breathing which not only represent the identity of music and human physiology but also offer new approaches for multidisciplinary respiratory medicine.

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Petersen, Eike, Herbert Buchner, Marcus Eger, and Philipp Rostalski. "Convolutive blind source separation of surface EMG measurements of the respiratory muscles." Biomedical Engineering / Biomedizinische Technik 62, no. 2 (January 1, 2017). http://dx.doi.org/10.1515/bmt-2016-0092.

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AbstractElectromyography (EMG) has long been used for the assessment of muscle function and activity and has recently been applied to the control of medical ventilation. For this application, the EMG signal is usually recorded invasively by means of electrodes on a nasogastric tube which is placed inside the esophagus in order to minimize noise and crosstalk from other muscles. Replacing these invasive measurements with an EMG signal obtained non-invasively on the body surface is difficult and requires techniques for signal separation in order to reconstruct the contributions of the individual respiratory muscles. In the case of muscles with small cross-sectional areas, or with muscles at large distances from the recording site, solutions to this problem have been proposed previously. The respiratory muscles, however, are large and distributed widely over the upper body volume. In this article, we describe an algorithm for convolutive blind source separation (BSS) that performs well even for large, distributed muscles such as the respiratory muscles, while using only a small number of electrodes. The algorithm is derived as a special case of the TRINICON general framework for BSS. To provide evidence that it shows potential for separating inspiratory, expiratory, and cardiac activities in practical applications, a joint numerical simulation of EMG and ECG activities was performed, and separation success was evaluated in a variety of noise settings. The results are promising.

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Wood, Christopher, Matt Travis Bianchi, Chang-Ho Yun, Chol Shin, and Robert Joseph Thomas. "Multicomponent Analysis of Sleep Using Electrocortical, Respiratory, Autonomic and Hemodynamic Signals Reveals Distinct Features of Stable and Unstable NREM and REM Sleep." Frontiers in Physiology 11 (December 3, 2020). http://dx.doi.org/10.3389/fphys.2020.592978.

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A new concept of non-rapid eye movement (NREM) and rapid eye movement (REM) sleep is proposed, that of multi-component integrative states that define stable and unstable sleep, respectively, NREMS, NREMUS REMS, and REMUS. Three complementary data sets are used: obstructive sleep apnea (20), healthy subjects (11), and high loop gain sleep apnea (50). We use polysomnography (PSG) with beat-to-beat blood pressure monitoring, and electrocardiogram (ECG)-derived cardiopulmonary coupling (CPC) analysis to demonstrate a bimodal, rather than graded, characteristic of NREM sleep. Stable NREM (NREMS) is characterized by high probability of occurrence of the <1 Hz slow oscillation, high delta power, stable breathing, blood pressure dipping, strong sinus arrhythmia and vagal dominance, and high frequency CPC. Conversely, unstable NREM (NREMUS) has the opposite features: a fragmented and discontinuous <1 Hz slow oscillation, non-dipping of blood pressure, unstable respiration, cyclic variation in heart rate, and low frequency CPC. The dimension of NREM stability raises the possibility of a comprehensive integrated multicomponent network model of NREM sleep which captures sleep onset (e.g., ventrolateral preoptic area-based sleep switch) processes, synaptic homeostatic delta power kinetics, and the interaction of global and local sleep processes as reflected in the spatiotemporal evolution of cortical “UP” and “DOWN” states, while incorporating the complex dynamics of autonomic-respiratory-hemodynamic systems during sleep. Bimodality of REM sleep is harder to discern in health. However, individuals with combined obstructive and central sleep apnea allows ready recognition of REMS and REMUS (stable and unstable REM sleep, respectively), especially when there is a discordance of respiratory patterns in relation to conventional stage of sleep.

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Tobaldini, E., G. D. Rodrigues, G. Mantoan, A. Monti, G. Coti Zelati, Ludovico Furlan, P. Tarsia, et al. "Effects of bilateral lung transplantation on cardiac autonomic modulation and cardiorespiratory coupling: a prospective study." Respiratory Research 22, no. 1 (May 21, 2021). http://dx.doi.org/10.1186/s12931-021-01752-6.

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Abstract Background Although cardiac autonomic modulation has been studied in several respiratory diseases, the evidence is limited on lung transplantation, particularly on its acute and chronic effects. Thus, we aimed to evaluate cardiac autonomic modulation before and after bilateral lung transplantation (BLT) through a prospective study on patients enrolled while awaiting transplant. Methods Twenty-two patients on the waiting list for lung transplantation (11 women, age 33 [24–51] years) were enrolled in a prospective study at Ospedale Maggiore Policlinico Hospital in Milan, Italy. To evaluate cardiac autonomic modulation, ten minutes ECG and respiration were recorded at different time points before (T0) and 15 days (T1) and 6 months (T2) after bilateral lung transplantation. As to the analysis of cardiac autonomic modulation, heart rate variability (HRV) was assessed using spectral and symbolic analysis. Entropy-derived measures were used to evaluate complexity of cardiac autonomic modulation. Comparisons of autonomic indices at different time points were performed. Results BLT reduced HRV total power, HRV complexity and vagal modulation, while it increased sympathetic modulation in the acute phase (T1) compared to baseline (T0). The HRV alterations remained stable after 6 months (T2). Conclusion BLT reduced global variability and complexity of cardiac autonomic modulation in acute phases, and these alterations remain stable after 6 months from surgery. After BLT, a sympathetic predominance and a vagal withdrawal could be a characteristic autonomic pattern in this population.

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Zhang, Jie, Yue Wu, Xiao-Yong Peng, Qing-Hui Li, Xin-Ming Xiang, Yu Zhu, Qing-Guang Yan, et al. "The Protective Effect of a Novel Cross-Linked Hemoglobin-Based Oxygen Carrier on Hypoxia Injury of Acute Mountain Sickness in Rabbits and Goats." Frontiers in Physiology 12 (September 27, 2021). http://dx.doi.org/10.3389/fphys.2021.690190.

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Hypoxia is the major cause of acute altitude hypoxia injury in acute mountain sickness (AMS). YQ23 is a kind of novel bovine-derived, cross-linked hemoglobin-based oxygen carrier (HBOC). It has an excellent capacity for carrying and releasing oxygen. Whether YQ23 has a protective effect on the acute altitude hypoxia injury in AMS is unclear. In investigating this mechanism, the hypobaric chamber rabbit model and plain-to-plateau goat model were used. Furthermore, this study measured the effects of YQ23 on the ability of general behavior, general vital signs, Electrocardiograph (ECG), hemodynamics, vital organ injury markers, and blood gases in hypobaric chamber rabbits and plain-to-plateau goats. Our results showed that the ability of general behavior (general behavioral scores, GBS) (GBS: 18 ± 0.0 vs. 14 ± 0.5, p < 0.01) and the general vital signs weakened [Heart rate (HR, beats/min): 253.5 ± 8.7 vs. 301.1 ± 19.8, p < 0.01; Respiratory rate (RR, breaths/min): 86.1 ± 5.2 vs. 101.2 ± 7.2, p < 0.01] after exposure to plateau environment. YQ23 treatment significantly improved the ability of general behavior (GBS: 15.8 ± 0.5 vs. 14.0 ± 0.5, p < 0.01) and general vital signs [HR (beats/min): 237.8 ± 24.6 vs. 301.1 ± 19.8, p < 0.01; RR (breaths/min): 86.9 ± 6.6 vs. 101.2 ± 7.2, p < 0.01]. The level of blood PaO2 (mmHg) (115.3 ± 4.7 vs. 64.2 ± 5.6, p < 0.01) and SaO2(%) (97.7 ± 0.7 vs. 65.8 ± 3.1, p < 0.01) sharply decreased after exposure to plateau, YQ23 treatment significantly improved the blood PaO2 (mmHg) (97.6 ± 3.7 vs. 64.2 ± 5.6, p < 0.01) and SaO2(%) (82.7 ± 5.2 vs. 65.8 ± 3.1, p < 0.01). The cardiac ischemia and injury marker was increased [troponin (TnT, μg/L):0.08 ± 0.01 vs. 0.12 ± 0.02, p < 0.01], as well as the renal [blood urea nitrogen (BUN, mmol/L): 6.0 ± 0.7 vs. 7.3 ± 0.5, p < 0.01] and liver injury marker [alanine aminotransferase (ALT, U/L): 45.8 ± 3.6 vs. 54.6 ± 4.2, p < 0.01] was increased after exposure to a plateau environment. YQ23 treatment markedly alleviated cardiac ischemia [TnT (μg/L):0.10 ± 0.01 vs 0.12 ± 0.02, p < 0.01] and mitigated the vital organ injury. Besides, YQ23 exhibited no adverse effects on hemodynamics, myocardial ischemia, and renal injury. In conclusion, YQ23 effectively alleviates acute altitude hypoxia injury of AMS without aside effects.

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Journal articles on the topic 'ECG-derived respiratory'

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