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Airflow is the reference signal to assess sleep respiratory disorders, such as sleep apnea. Previous studies estimated airflow using tracheal sounds in short segments with specific airflow rates, while requiring calibration or a few breaths for tuning the relationship between sound energy and airflow. Airflow-sound relationship can change by posture, sleep stage and airflow rate or tidal volume. We investigated the possibility of estimating surrogates of tidal volume without calibration in the adult sleep apnea population using tracheal sounds and movements. Two surrogates of tidal volume: thoracoabdominal range of sum movement and airflow level were estimated. Linear regression was used to estimate thoracoabdominal range of sum movement from sound energy and the range of movements. The sound energy lower envelope was found to correlate with airflow level. The agreement between reference and estimated signals was assessed by repeated-measure correlation analysis. The estimated tidal volumes were used to estimate the airflow signal. Sixty-one participants (30 females, age: 51 ± 16 years, body mass index: 29.5 ± 6.4 kg m-2 , and apnoea-hypopnea index: 20.2 ± 21.2) were included. Reference and estimated thoracoabdominal range of sum movement of whole night data were significantly correlated with the reference signal extracted from polysomnography (r = 0.5 ± 0.06). Similarly, significant correlations (r = 0.3 ± 0.05) were found for airflow level. Significant differences in estimated surrogates of tidal volume were found between normal breathing and apnea/hypopnea. Surrogate of airflow can be extracted from tracheal sounds and movements, which can be used for assessing the severity of sleep apnea and even phenotyping sleep apnea patients based on the estimated airflow shape.

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Background In patients with end-stage kidney disease, sudden cardiac death is more frequent after a long interdialytic interval, within 6 hours after the end of a hemodialysis session. We hypothesized that the occurrence of paroxysmal arrhythmias is associated with changes in heart rate and heart rate variability in different phases of hemodialysis. Methods and Results We conducted a prospective ancillary study of the Predictors of Arrhythmic and Cardiovascular Risk in End Stage Renal Disease cohort. Continuous ECG monitoring was performed using an ECG patch, and short-term heart rate variability was measured for 3 minutes every hour (by root mean square of the successive normal-to-normal intervals, spectral analysis, Poincaré plot, and entropy), up to 300 hours. Out of enrolled participants (n=28; age 54±13 years; 57% men; 96% black; 33% with a history of cardiovascular disease; left ventricular ejection fraction 70±9%), arrhythmias were detected in 13 (46%). Nonsustained ventricular tachycardia occurred more frequently during/posthemodialysis than pre-/between hemodialysis (63% versus 37%, P=0.015). In adjusted for cardiovascular disease time-series analysis, nonsustained ventricular tachycardia was preceded by a sudden heart rate increase (by 11.2 [95% CI 10.1-12.3] beats per minute; P<0.0001). During every-other-day dialysis, root mean square of the successive normal-to-normal intervals had a significant circadian pattern (Mesor 10.6 [ 95% CI 0.9-11.2] ms; amplitude 1.5 [95% CI 1.0-3.1] ms; peak at 02:01 [95% CI 20:22-03:16] am; P<0.0001), which was replaced by a steady worsening on the second day without dialysis (root mean square of the successive normal-to-normal intervals -1.41 [95% CI -1.67 to -1.15] ms/24 h; P<0.0001). Conclusions Sudden increase in heart rate during/posthemodialysis is associated with nonsustained ventricular tachycardia. Every-other-day hemodialysis preserves circadian rhythm, but a second day without dialysis is characterized by parasympathetic withdrawal.

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INTRODUCTION: The subcutaneous implantable cardioverter-defibrillator (S-ICD) is a life-saving device. Recording of a specialized 3-lead electrocardiogram (ECG) is required for S-ICD eligibility assessment. The goals of this study were: (1) evaluate the effect of ECG filtering on S-ICD eligibility, and (2) simplify S-ICD eligibility assessment by development of an S-ICD ineligibility prediction tool, which utilizes the widely available routine 12-lead ECG. METHODS AND RESULTS: Prospective cross-sectional study participants [n = 68; 54% male; 94% white, with wide ranges of age (18-81 y), body mass index (19-53), QRS duration (66-150 ms), and left ventricular ejection fraction (37-77%)] underwent 12-lead supine, 3-lead supine and standing ECG recording. All 3-lead ECG recordings were assessed using the standard S-ICD pre-implantation ECG morphology screening. Backward, stepwise, logistic regression was used to build a model for 12-lead prediction of S-ICD eligibility. Select electrocardiogram waves and complexes: QRS, R-, S, and T-amplitudes on all 12 leads, averaged QT interval, QRS duration, and R/T ratio in the lead with the largest T wave (R/Tmax) were included as predictors. The effect of ECG filtering on ECG morphology was evaluated. A total of 9 participants (13%) failed S-ICD screening prior to filtering. Filtering at 3-40 Hz, similar to the S-ICD default, reduced S-ICD ineligibility to 4%. A regression model that included RII, SII-aVL, TI, II, aVL, aVF, V3-V6, and R/Tmax perfectly predicted S-ICD eligibility, with an Area Under the Receiver Operating Characteristic Curve of 1.0. CONCLUSION: Routine clinical 12-lead ECG can be used to predict S-ICD eligibility. ECG filtering may improve S-ICD eligibility.

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Denervated post-infarct scar is arrhythmogenic. Our aim was to compare QRS frequency content in denervated and innervated left ventricular (LV) scar. In-vivo single lead ECG telemetry device was implanted in 17 heterozygous PTPσ (HET) and 7 lacking PTPσ (KO) transgenic mice. Myocardial infarction (MI) with reperfusion and sham surgery was performed. HET mice developed a denervated scar, whereas KO mice developed innervated scar. The power spectral density was used to assess the QRS frequency content. Denervated as compared to innervated post-MI scar was characterized by the higher relative contribution of 300-500 Hz (14 ± 1 vs. 9 ± 1%; P = 0.001) but reduced relative contribution of 200-300 Hz (86 ± 1 vs. 91 ± 1%; P = 0.001). Norepinephrine concentration in peri-infarct zone correlated with both 1-200 Hz (r = 0.75; P = 0.03) and 200-500 Hz QRS power (r = 0.73; P = 0.04). Sympathetic fiber density within the infarct correlated with 200-300/200-500 Hz QRS power ratio (r = 0.56; P = 0.005). Intracellular sigma peptide injections in post-MI HET mice restored the QRS power.

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The purpose of this study was to develop optimal configuration of adhesive ECG patches placement on the torso, which would provide the best agreement with the Frank orthogonal ECGs. Ten seconds of orthogonal ECG followed by 3-5min of ECGs using patches at 5 different locations simultaneously on the torso were recorded in 50 participants at rest in sitting position. Median beat was generated for each ECG and 3 patch ECGs that best correlate with orthogonal ECGs were selected for each participant. For agreement analysis, spatial QRS-T angle, spatial QRS and T vector characteristics, spatial ventricular gradient, roundness, thickness and planarity of vectorcardiographic (VCG) loops were measured. Key VCG parameters showed high agreement in Bland-Altman analysis (spatial QRS-T angle on 3-patch ECG vs. Frank ECG bias 0.3 (95% limits of agreement [-6.23;5.71 degrees]), Lin's concordance coefficient=0.996). In conclusion, newly developed orthogonal 3-patch ECG can be used for long-term VCG monitoring.

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Vectorcardiography (VCG), developed 100years ago, characterizes clinically important electrophysiological properties of the heart. In this study, VCG QRS loop roundness, planarity, thickness, rotational angle, and dihedral angle were measured in 81 healthy control subjects (39.0±14.2y; 51.8% male; 94% white), and 8 patients with infarct-cardiomyopathy and sustained monomorphic ventricular tachycardia (VT) (68.0±7.8y, 37.5% male). The angle between two consecutive QRS vectors was defined as the rotational angle, while dihedral angle quantified planar alteration over the QRS loop. In VT subjects, planarity index decreased (0.63±0.22 vs. 0.88±0.10; P=0.014), and dihedral angle was significantly more variable (variance of dihedral angle, median (IQR): 897(575-1450) vs. 542(343-773); P=0.029; rMSSD: 47.7±12.7 vs. 35.1±13.1; P=0.027). Abnormal electrophysiological substrate in VT patients is characterized by the appearance of QRS loop folding, likely due to local conduction block. The presence of fragmented QRS complexes on the 12-lead ECG had low sensitivity (31%) for detecting QRS loop folding on the VCG.

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Recently, we developed a novel approach to study the rapid and sudden changes in the direction of ventricular activation called folding phenomenon. In order to better understand this phenomenon, we were interested in studying the variation of the orientation of [Formula: see text] for i=1…N where [Formula: see text] represents the QRS vector at the ith sample point. In this study, we described the orientation of the [Formula: see text] vector and the rotation of its frame of reference in details in 81 healthy participants from the Intercity Digital Electrocardiogram Alliance (IDEAL) study using unit quaternions and Euler angles. We observed that the variance of the elevation of rotation axis u⃗ was significantly higher in men compared to women (1340±421 vs. 1063±381, P=0.003, respectively). Additionally, there was a significant negative correlation between the variance of the azimuth of u⃗ and height (CC=-0.26, P=0.019) while the elevation of u⃗ and height were significantly positively correlated (CC=0.24, P=0.034). Moreover, the elevation of u⃗ had a positive significant correlation with weight and body surface area (CC=0.22, P=0.045 and CC=0.26, P=0.020 respectively).

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In this paper we employed joint symbolic dynamics (JSD) approach to study reproducibility of heart rate variability characteristics measured on 2 randomly selected 10-second segments within 3-minute resting orthogonal ECG in 170 healthy participants. First, the ECG R-peaks were detected using parabolic fitting. Second, the respiratory signal was derived from orthogonal ECG X-lead using QRS slopes. Third, time series of R-R intervals and respiratory phases (calculated using Hilbert transform), were transformed into tertiary symbol vectors based on their successive changes and words of length '3' were formed. Bland-Altman analysis was used to assess the agreement between measured log-transformed JSD characteristics of HRV, and their reproducibility. Traditional HRV measures such as RR' interval changes showed a very high reproducibility. However, agreement between two 10-second JSD indices of HRV was low. Interestingly, a significant decrease in low-high alterations of HRV dynamics measured using JSD was observed when respiratory phase transition intervals were excluded (10s: 4.7±9.4 vs. 24.8±21.0%, p<0.0001; 3min: 9.8±8.1 vs. 24.8±12.3%, p<0.0001).

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Atrial fibrillation (AF) is the most common arrhythmia in adults and is associated with significant morbidity and mortality. Substantial interest has developed in the primary prevention of AF, and thus the identification of individuals at risk for developing AF. The electrocardiogram (ECG) provides a wealth of information, which is of value in predicting incident AF. The PR interval and P wave indices (including P wave duration, P wave terminal force, P wave axis, and other measures of P wave morphology) are discussed with regard to their ability to predict and characterize AF risk in the general population. The predictive value of the QT interval, ECG criteria for left ventricular hypertrophy, and findings of atrial and ventricular ectopy are also discussed. Efforts are underway to develop models that predict AF incidence in the general population; however, at present, little information from the ECG is included in these models. The ECG provides a great deal of information on AF risk and has the potential to contribute substantially to AF risk estimation, but more research is needed.

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The purposes of this study were to characterize and quantify concordance between consecutive atrial and ventricular activation time points through analysis of phases and to explore its association with outcomes in patients with implantable cardioverter-defibrillator (ICD). Patients with structural heart disease and dual-chamber ICDs underwent 5min baseline right ventricular (V) near-field and atrial (A) electrogram (EGM) recording. The cross-dependencies of phase dynamics of the changes in consecutive A (AA') and V (VV') were quantified and the AV phase dependency index was determined. In Cox regression analysis, a high AV phase index (in the highest quartile, >0.259) was significantly associated with higher risk of ventricular tachyarrhythmias (HR 2.84; 95% CI 1.05-7.67; P=0.04). In conclusion, in ICD patients with structural heart disease, high sinus AV phase dependency index on EGM is associated with the risk of ventricular arrhythmia.

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We constructed an intracardiac vectorcardiogram from 3 configurations of intracardiac cardiovertor defibrilator (ICD) electrograms (EGMs). Six distinctive 3 lead combinations were selected out of five leads: can to right ventricular coil (RVC); RVC to superior vena cava coil (SVC); atrial lead tip (A-tip) to right ventricular (RV)-ring; can to RV-ring; RV-tip to RVC, in a patient with dual chamber ICD. Surface spatial QRS-T angle (119.8°) was similar to intracardiac spatial QRS-T angle derived from ICD EGMs combination A (101.3°), B (96.1°), C (92.8°), D (95.2), E (99.0), F (96.2) and median (101.5). Future validation of the novel method is needed.

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BACKGROUND: In heart failure patients with implantable cardioverter defibrillator (ICD) the risk of death from causes other than tachyarrhythmia is substantial. Benefit from ICD is determined by two competing risks: appropriate ICD shock or nonarrhythmic death. The goal of the study was to test predictors of competing outcomes. METHODS: Patients with structural heart disease (N = 234, mean age 58.5 ± 15.1; 71% men, 80% whites, 61% ischemic cardiomyopathy) and primary (75%) or secondary prevention ICD underwent a 5-minute baseline near-field electrogram (NF EGM) recording. VV' alternans triplets were quantified as a percentage of three sinus VV' cycles sequences of "short-long-short" or "long-short-long" order. Appropriate ICD shock for fast ventricular tachycardia (FVT, cycle length ≤240 ms)/ventricular fibrillation (VF) and composite nonarrhythmic death (pump failure death or heart transplant) served as competing outcomes. RESULTS: Over a median follow-up of 2.4 years, 26 patients (4.6% per person-year of follow-up) developed FVT/VF with ICD shock, and 35 (6.3% per person-year of follow-up) had nonarrhythmic death. In competing risk analysis, after adjustment for demographics, left ventricular ejection fraction, New York Heart Association class, cardiomyopathy type, use of class I antiarrhythmics, and diabetes, increased percentage of VV' alternans triplets (>69%) was associated with nonarrhythmic death (subhazard ratio [SHR] 2.09; 95% confidence interval [CI] 1.03-4.23; P = 0.041), rather than with FVT/VF (SHR 1.05; 95% CI 0.45-2.46; P = 0.901). Risk of nonarrhythmic death was especially high in diabetics with VV' alternans triplets in the highest quartile (SHR 3.46; 95% CI 1.41-8.50; P = 0.007). CONCLUSION: In ICD patients with structural heart disease sinus VV' alternans triplets on NF EGM is independently associated with nonarrhythmic death, rather than with FVT/VF.

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Detection of sleep spindles is of major importance in the field of sleep research. However, manual scoring of spindles on prolonged recordings is very laborious and time-consuming. In this paper, we introduce a new algorithm based on synchrosqueezing transform for detection of sleep spindles. Synchrosqueezing is a powerful time-frequency analysis tool that provides precise frequency representation of a multicomponent signal through mode decomposition. Subsequently, the proposed algorithm extracts and compares the basic features of a spindle-like activity with its surrounding, thus adapting to an expert's visual criteria for spindle scoring. The performance of the algorithm was assessed against the spindle scoring of one expert on continuous electroencephalogram sleep recordings from two subjects. Through appropriate choice of synchrosqueezing parameters, our proposed algorithm obtained a maximum sensitivity of 96.5% with 98.1% specificity. Compared to previously published works, our algorithm has shown improved performance by enhancing the quality of sleep spindle detection.

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In this paper we employed a novel approach based on joint symbolic dynamics (JSD) to study interaction between respiratory phase and baroreflex activity. Electrocardiogram (ECG) and blood pressure recordings from six participants with history of heart failure were included in this study. First, the ECG R-peaks and systolic blood pressure indices were detected using parabolic fitting. Second, the respiratory signal was derived from Frank orthogonal ECG leads using QRS slopes and R-wave angles. Third, time series of R-R intervals and systolic blood pressure (SBP) were extracted, and respiratory phases were obtained using the Hilbert transform. Subsequently, each series was transformed into binary symbol vectors based on their successive changes and words of length '2' were formed. Baroreflex patterns were studied using word combinations representing baroreflex activity for specific changes in respiratory phases. Baroreflex activity was significantly higher for alternating low-high/high-low heart rate and SBP during inspiration as compared to continuous increase or decrease in heart rate and SBP ([Formula: see text], wRP=11: 39.1±9.3% vs. [Formula: see text], wRP=11: 6.4±3.9%, p<0.0001).

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AIM: The goal of this study was to compare associations between clinical and ECG predictors of cardiac resynchronization therapy (CRT) response with electrical dyssynchrony. METHODS: Body-surface potentials were recorded using a 120-lead system in 4 patients (age 62 ± 12 y, left ventricular ejection fraction (LVEF) 29 ± 5 %; QRS duration 154 ± 19 ms) with post-myocardial infarction scar and left bundle branch block before CRT implantation. A patient-specific heart-torso model derived from MRI with 291 heart-surface nodes was developed. Electrical dyssynchrony index (EDI) was computed as the standard deviation of activation times on the epicardium while uncoupling index (UI) was measured as the difference between the activation times. RESULTS: QRS duration correlated with mean activation time (r = 0.977; P = 0.023), but did not correlate with EDI or UI. LVEF inversely correlated with activation time at the lowest 20th percentile (r = -0.960; P = 0.040). Sum absolute QRST integral (SAI QRST), measured on orthogonal XYZ ECG, correlated with EDI (r = 0.955; P = 0.045), and characterized late-activated area of the left ventricle. CONCLUSION: SAI QRST is a measure of electrical dyssynchrony on ECG.

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OBJECTIVE: This study aims to investigate the impact of upper airway obstruction (UAO) in children by measuring thoracoabdominal asynchrony (TAA) during periods of sleep apnea/hypopnea and during scored-event-free (SEF) breathing periods. METHODS: Respiratory inductive plethysmographic signals were extracted from polysomnographic data, recorded before and after adenotonsillectomy in 40 children with UAO and 40 healthy, matched children at equivalent time points. Thoracoabdominal asynchrony was computed using a Hilbert transform-based phase difference estimation method in SEF periods during stage 2, stage 4 non-rapid eye movement (NREM), and rapid eye movement (REM) sleep and compared between the groups. RESULTS: At baseline, in the UAO group, TAA during obstructions were significantly higher than TAA during SEF periods in both stage 2 and REM sleep. Compared to controls, children with UAO had a significantly higher TAA during SEF periods in stage 2, stage 4 sleep, and REM sleep. This between-group difference was not significant post adenotonsillectomy. UAO group showed a significant decrease in TAA compared to their baseline during SEF stage 2 and 4 NREM, but not in REM. CONCLUSION: Upper airway obstruction in children is associated with increased TAA during SEF periods, indicative of continuous partial obstruction of the upper airway. Adenotonsillectomy decreased this effect significantly in non-REM sleep as evidenced by reduced asynchrony levels post-surgery. TAA assessment during sleep may therefore provide additional diagnostic information.

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Reliable detection of significant ECG features such as the P-wave, QRS-complex and T-wave are of major clinical importance. In this paper we introduce a new algorithm based on synchrosqueezing wavelet transform for detection of P-waves in long-term ECG recordings. Synchrosqueezing is a powerful time-frequency analysis tool that provides precise frequency representation of a multicomponent signal through mode decomposition. First, we analyzed four wavelet filters with different filter parameters, to identify the best specification for quantification of QRS and P-wave. Second, the algorithm was tested on ECG recording comprising of events with paroxysmal atrioventricular block and validated through visual scanning. Using morlet wavelet with a peak frequency of 5Hz and separation of 0.1Hz, our proposed algorithm was able to detect 95.5% of P-waves. From this study, it appears that synchrosqueezing wavelet transform may provide a powerful robust technique for automated ECG analysis.

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Resistive loading affects the breathing pattern and causes an increase in negative intrathoracic pressure. The aim of this paper was to study the influence inspiratory and expiratory loading on cardio-respiratory interaction. We recorded electrocardiogram (ECG) and respiratory inductance plethysmogram (RIP) in 11 healthy male subjects under normal and resistive loading conditions. The R-R time series were extracted from the ECG and respiratory phases were calculated from the ribcage and abdominal RIP using the Hilbert transform. Both the series were transformed into ternary symbol vectors based on the changes between two successive R-R intervals or respiratory phases, respectively. Subsequently, words of length `3 digits' were formed and the correspondence between words of the two series was determined to quantify cardio-respiratory interaction. Adding inspiratory and expiratory resistive loads resulted in an increase in inspiratory and expiatory time, respectively. Furthermore, we observed a significant increase in cardio-respiratory interaction during inspiratory resistive loading as compared to expiratory resistive loading (ribcage: 22.1±7.2 vs. 12.5±4.3 %, p<;0.0001; abdomen: 18.8±8.5 vs. 12.1±3.1 %, p<;0.05, respectively). Further studies may aid in better understanding the underlying physiological mechanisms and management of patients with breathing disorders.

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Childhood sleep disordered breathing (SDB) is characterized by an increased work of breathing, restless night sleep and excessive daytime sleepiness and has been associated with cognitive impairment, behavioral disturbances and early cardiovascular changes. Compared to normal controls, children with SDB have elevated arousal thresholds and their sleep EEG may elicit cortical activation associated with arousals but often too subtle to be visually scored. The aim of this study was to assess EEG complexity throughout the respiratory cycle based on symbolic dynamics in children with SDB (n=40) and matched healthy controls. EEG amplitude values were symbolized based on the quartiles of their distribution and words of length 3 were formed and classed into 4 types based on their patterns. Children with SDB showed less complex EEG dynamics in non-REM sleep that was unrelated to the respiratory phase. In REM sleep normal children showed a respiratory phase-related reduction in EEG variability during the expiratory phase compared to inspiration, which was not apparent in children with SDB. In conclusion, respiratory cycle related EEG dynamics are altered in children with SDB during REM sleep and indicate changes in cortical activity.

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This study sought to employ a novel approach based on joint symbolic dynamics (JSD) to study the influence of respiratory phase on baroreflex function. We recorded electrocardiograms (ECG), blood pressure and respiration in 10 (5 male/5 female) healthy experienced athletes. For our analysis, time series of R-R intervals and systolic blood pressure were extracted, and respiratory phases were obtained using the Hilbert transform. Based on the changes between successive values, each series was transformed into binary symbol vectors, and words of length '2' were formed. From parallel analysis of the symbolic dynamics in the three time series, the relationship between respiratory phases and baroreflex function was quantified. We analysed baroreflex patterns via different word combinations for specific respiratory phases and observed that baroreflex patterns occurred at similar frequency during expiration, inspiration and phase transitions (25.0±14.4% vs. 33.4±19.5%, expiration-inspiration: 25.0±12.6% and inspiration-expiration: 22.1±17.4%, respectively). From this study, it appears that JSD provides a novel and efficient technique for the combined analysis of interactions between respiration, heart rate and blood pressure.

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