The influence of cardiac arrhythmias on the detection of heartbeats in the photoplethysmogram: benchmarking open-source algorithms.

Objective.Cardiac arrhythmias are a leading cause of mortality worldwide. Wearable devices based on photoplethysmography give the opportunity to screen large populations, hence allowing for an earlier detection of pathological rhythms that might reduce the risks of complications and medical costs. While most of beat detection algorithms have been evaluated on normal sinus rhythm or atrial fibrillation recordings, the performance of these algorithms in patients with other cardiac arrhythmias, such as ventricular tachycardia or bigeminy, remain unknown to date.Approach. ThePPG-beatsopen-source framework, developed by Charlton and colleagues, evaluates the performance of the beat detectors namedQPPG,MSPTDandABDamong others. We applied thePPG-beatsframework on two newly acquired datasets, one containing seven different types of cardiac arrhythmia in hospital settings, and another dataset including two cardiac arrhythmias in ambulatory settings.Main Results. In a clinical setting, theQPPGbeat detector performed best on atrial fibrillation (with a medianF1score of 94.4%), atrial flutter (95.2%), atrial tachycardia (87.0%), sinus rhythm (97.7%), ventricular tachycardia (83.9%) and was ranked 2nd for bigeminy (75.7%) behindABDdetector (76.1%). In an ambulatory setting, theMSPTDbeat detector performed best on normal sinus rhythm (94.6%), and theQPPGdetector on atrial fibrillation (91.6%) and bigeminy (80.0%).Significance. Overall, the PPG beat detectorsQPPG,MSPTDandABDconsistently achieved higher performances than other detectors. However, the detection of beats from wrist-PPG signals is compromised in presence of bigeminy or ventricular tachycardia.

A single-beat algorithm to discriminate farfield from nearfield bipolar voltage electrograms from the pulmonary veins.

BACKGROUND: Superimposition of farfield (FF) and nearfield (NF) bipolar voltage electrograms (BVE) complicates the confirmation of pulmonary vein (PV) isolation after catheter ablation of atrial fibrillation. Our aim was to develop an automatic algorithm based on a single-beat analysis to discriminate PV NF from atrial FF BVE from a circular mapping catheter during the cryoballoon PV isolation. METHODS: During freezing cycles in cryoablation PVI, local NF and distant FF signals were recorded, identified and labelled. BVEs were classified using four different machine learning algorithms based on four frequency domain (high-frequency power (PHF), low-frequency power (PLF), relative high power band, PHF ratio of neighbouring electrodes) and two time domain features (amplitude (Vmax), slew rate). The algorithm-based classification was compared to the true identification gained during the PVI and to a classification by cardiac electrophysiologists. RESULTS: We included 335 BVEs from 57 consecutive patients. Using a single feature, PHF with a cut-off at 150 Hz showed the best overall accuracy for classification (79.4%). By combining PHF with Vmax, overall accuracy was improved to 82.7% with a specificity of 89% and a sensitivity of 77%. The overall accuracy was highest for the right inferior PV (96.6%) and lowest for the left superior PV (76.9%). The algorithm showed comparable accuracy to the classification by the EP specialists. CONCLUSIONS: An automated farfield-nearfield discrimination based on two simple features from a single-beat BVE is feasible with a high specificity and comparable accuracy to the assessment by experienced cardiac electrophysiologists.

Novel spatiotemporal processing tools for body-surface potential map signals for the prediction of catheter ablation outcome in persistent atrial fibrillation.

Background: Signal processing tools are required to efficiently analyze data collected in body-surface-potential map (BSPM) recordings. A limited number of such tools exist for studying persistent atrial fibrillation (persAF). We propose two novel, spatiotemporal indices for processing BSPM data and test their clinical applicability through a comparison with the recently proposed non-dipolar component index (NDI) for prediction of single-procedure catheter ablation (CA) success rate in persAF patients. Methods: BSPM recordings were obtained with a 252-lead vest in 13 persAF patients (8 men, 63 ± 8 years, 11 ± 13 months sustained AF duration) before undergoing CA. Each recording was divided into seven 1-min segments of high signal quality. Spatiotemporal ventricular activity (VA) cancellation was applied to each segment to isolate atrial activity (AA). The two novel indices, called error-ratio, normalized root-mean-square error (ERNRMSE) and error-ratio, mean-absolute error (ERABSE), were calculated. These indices quantify the capacity of a subset of BSPM vest electrodes to accurately represent the AA, and AA dominant frequency (DF), respectively, on all BSPM electrodes over time, compared to the optimal principal component analysis (PCA) representation. The NDI, quantifying the fraction of energy retained after removal of the three largest PCs, was also calculated. The two novel indices and the NDI were statistically compared between patient groups based on single-procedure clinical CA outcome. Finally, their predictive power for univariate CA outcome classification was assessed using receiver operating characteristic (ROC) analysis with cross-validation for a logistic regression classifier. Results: Patient clinical outcomes were recorded 6 months following procedures, and those who had an arrhythmia recurrence at least 2 months post-CA were defined as having a negative outcome. Clinical outcome information was available for 11 patients, 6 with arrhythmia recurrence. Therefore, a total of 77 1-min AA-BSPM segments were available for analysis. Significant differences were found in the values of the novel indices and NDI between patients with arrhythmia recurrence post-ablation and those without. ROC analysis showed the best CA outcome predictive performance for ERNRMSE (AUC = 0.77 ± 0.08, sensitivity = 76.2%, specificity = 84.8%). Conclusion: Significant association was found between the novel indices and CA success or failure. The novel index ERNRMSE additionally shows good predictive power for single-procedure CA outcome.

Correlation between conduction velocity and frequency analysis in patients with atrial fibrillation using high-density charge mapping.

Spectral analysis of atrial signals has been used to identify regions of interest in atrial fibrillation (AF). However, the relationship to the atrial substrate is unclear. In this study, we compare regions with dominant frequency (DF), simultaneously determined in the left atrium (LA) by a novel noncontact mapping system using unipolar charge density signals, to the zones of slow conduction (SZ) during AF.In 19 AF patients the conduction during AF was assessed by a validated algorithm and SZ compared to the DF and the DF ratio between the DF peak and the area under the total spectrum (DFR). The results were compared in five different regions of the LA. The reproducibility of SZ location at different time measurements was higher than for DF or DFR. The SZs are mainly confined at the anterior and posterior wall of the LA. There was no statistically significant correlation between SZ and DF or DFR across the atrium.

Evaluation and optimization of novel extraction algorithms for the automatic detection of atrial activations recorded within the pulmonary veins during atrial fibrillation.

BACKGROUND AND OBJECTIVE: The automated detection of atrial activations (AAs) recorded from intracardiac electrograms (IEGMs) during atrial fibrillation (AF) is challenging considering their various amplitudes, morphologies and cycle length. Activation time estimation is further complicated by the constant changes in the IEGM active zones in complex and/or fractionated signals. We propose a new method which provides reliable automatic extraction of intracardiac AAs recorded within the pulmonary veins during AF and an accurate estimation of their local activation times. METHODS: First, two recently developed algorithms were evaluated and optimized on 118 recordings of pulmonary vein IEGM taken from 35 patients undergoing ablation of persistent AF. The adaptive mathematical morphology algorithm (AMM) uses an adaptive structuring element to extract AAs based on their morphological features. The relative-energy algorithm (Rel-En) uses short- and long-term energies to enhance and detect the AAs in the IEGM signals. Second, following the AA extraction, the signal amplitude was weighted using statistics of the AA sequences in order to reduce over- and undersensing of the algorithms. The detection capacity of our algorithms was compared with manually annotated activations and with two previously developed algorithms based on the Teager-Kaiser energy operator and the AF cycle length iteration, respectively. Finally, a method based on the barycenter was developed to reduce artificial variations in the activation annotations of complex IEGM signals. RESULTS: The best detection was achieved using Rel-En, yielding a false negative rate of 0.76% and a false positive rate of only 0.12% (total error rate 0.88%) against expert annotation. The post-processing further reduced the total error rate of the Rel-En algorithm by 70% (yielding to a final total error rate of 0.28%). CONCLUSION: The proposed method shows reliable detection and robust temporal annotation of AAs recorded within pulmonary veins in AF. The method has low computational cost and high robustness for automatic detection of AAs, which makes it a suitable approach for online use in a procedural context.

RMSSD Is More Sensitive to Artifacts Than Frequency-Domain Parameters: Implication in Athletes' Monitoring.

Easy-to-use and accurate heart rate variability (HRV) assessments are essential in athletes' follow-up, but artifacts may lead to erroneous analysis. Artifact detection and correction are the purpose of extensive literature and implemented in dedicated analysis programs. However, the effects of number and/or magnitude of artifacts on various time- or frequency-domain parameters remain unclear. The purpose of this study was to assess the effects of artifacts on HRV parameters. Root mean square of the successive differences (RMSSD), standard deviation of the normal to normal inter beat intervals (SDNN), power in the low- (LF) and high-frequency band (HF) were computed from two 4-min RR recordings in 178 participants in both supine and standing positions, respectively. RRs were modified by (1) randomly adding or subtracting 10, 30, 50 or 100 ms to the successive RRs; (2) a single artifact was manually inserted; (3) artifacts were automatically corrected from signal naturally containing artifacts. Finally, RR recordings were analyzed before and after automatic detection-correction of artifacts. Modifying each RR by 10, 30, 50 and 100 ms randomly did not significantly change HRV parameters (range -6%, +6%, supine). In contrast, by adding a single artifact, RMSSD increased by 413% and 269%, SDNN by 54% and 47% in supine and standing positions, respectively. LF and HF changed only between -3% and +8% (supine and standing) in the artifact condition. When more than 0.9% of the signal contained artifacts, RMSSD was significantly biased, whilst when more than 1.4% of the signal contained artifacts LF and HF were significantly biased. RMSSD and SDNN were more sensitive to a single artifact than LF and HF. This indicates that, when using RMSSD only, a single artifact may induce erroneous interpretation of HRV. Therefore, we recommend using both time- and frequency-domain parameters to minimize the errors in the diagnoses of health status or fatigue in athletes.

Dynamics of Intraprocedural Dominant Frequency Identifies Ablation Outcome in Persistent Atrial Fibrillation.

Background: The role of dominant frequency (DF) in tracking the efficiency of a stepwise catheter ablation (step-CA) in persistent atrial fibrillation (peAF) remains poorly studied. We hypothesized that the DF time-course during step-CA displays divergent patterns between patients in whom a step-CA successfully restores long-term sinus rhythm (SR) and those with recurrence. Methods: This study involved 40 consecutive patients who underwent a step-CA for peAF (sustained duration 19 ± 11 months). Dominant frequency was computed on electrograms recorded from the right and left atrial appendages (RAA; LAA) and the coronary sinus before and during the step-CA synchronously to the 12-lead ECG. Dominant frequency was defined as the highest peak within the power spectrum. Results: Persistent atrial fibrillation was terminated by a step-CA in 28 patients [left-terminated (LT)], whereas 12 patients remaining in AF after ablation [not left-terminated (NLT)] were cardioverted. Over a mean follow-up of 34 ± 14 months, all NLT patients had a recurrence. Among the 28 LT patients, 20 had a recurrence, while 8 remained in SR throughout follow-up. The RAA and V1 DF had the best predictive values of the procedural failure to terminate AF (area under the curve; AUC 0.84, p < 0.05). A decision tree model including a decrease in LAA DF ≥ 6.61% during the first 20 min following pulmonary vein isolation (PVI) and a baseline RAA DF <5.6 Hz predicted long-term SR restoration with a sensitivity of 83% and a specificity of 93% (p < 0.05). Conclusion: This study found that high baseline DF values are predictive of unfavorable ablation outcomes. The reduction of the LAA DF at early ablation steps following PVI is associated with procedural AF termination and long-term SR maintenance.

Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running.

Recent advances in wearable technologies integrating multi-modal sensors have enabled the in-field monitoring of several physiological metrics. In sport applications, wearable devices have been widely used to improve performance while minimizing the risk of injuries and illness. The objective of this project is to estimate breathing rate (BR) from respiratory sinus arrhythmia (RSA) using heart rate (HR) recorded with a chest belt during physical activities, yielding additional physiological insight without the need of an additional sensor. Thirty-one healthy adults performed a run at increasing speed until exhaustion on an instrumented treadmill. RR intervals were measured using the Polar H10 HR monitoring system attached to a chest belt. A metabolic measurement system was used as a reference to evaluate the accuracy of the BR estimation. The evaluation of the algorithms consisted of exploring two pre-processing methods (band-pass filters and relative RR intervals transformation) with different instantaneous frequency tracking algorithms (short-term Fourier transform, single frequency tracking, harmonic frequency tracking and peak detection). The two most accurate BR estimations were achieved by combining band-pass filters with short-term Fourier transform, and relative RR intervals transformation with harmonic frequency tracking, showing 5.5% and 7.6% errors, respectively. These two methods were found to provide reasonably accurate BR estimation over a wide range of breathing frequency. Future challenges consist in applying/validating our approaches during in-field endurance running in the context of fatigue assessment.

Association of Heart Rate Variability With Silent Brain Infarcts in Patients With Atrial Fibrillation.

Purpose: Silent brain infarcts (SBI) are frequently detected in patients with atrial fibrillation (AF), but it is unknown whether SBI are linked to autonomic dysfunction. We aimed to explore the association of autonomic dysfunction with SBI in AF patients. Methods: 1,358 AF patients without prior stroke or TIA underwent brain MRI and 5-min resting ECG. We divided our cohort into AF patients who presented in sinus rhythm (SR-group, n = 816) or AF (AF-group, n = 542). HRV triangular index (HRVI), standard deviation of normal-to-normal intervals, mean heart rate, root mean square root of successive differences of normal-to-normal intervals, 5-min total power and power in the low frequency, high frequency and very low frequency range were calculated. Primary outcome was presence of SBI in the SR group, defined as large non-cortical or cortical infarcts. Secondary outcomes were SBI volumes and topography. Results: Mean age was 72 ± 9 years, 27% were female. SBI were detected in 10.5% of the SR group and in 19.9% of the AF group (p < 0.001). HRVI <15 was the only HRV parameter associated with the presence of SBI after adjustment for clinical covariates in the SR group [odds ratio (OR) 1.67; 95% confidence interval (CI): 1.03-2.70; p = 0.037]. HRVI <15 was associated with larger brain infarct volumes [ß (95% CI) -0.47 (-0.84; -0.09), p = 0.016] in the SR group and was more frequently observed in patients with right- than left-hemispheric SBI (p = 0.017). Conclusion: Impaired HRVI is associated with SBI in AF patients. AF patients with autonomic dysfunction might undergo systematic brain MRI screening to initiate intensified medical treatment. Clinical Trials Gov Identifier: NCT02105844.

ECG-Based Indices to Characterize Persistent Atrial Fibrillation Before and During Stepwise Catheter Ablation.

Background: Consistently successful patient outcomes following catheter ablation (CA) for treatment of persistent atrial fibrillation (pers-AF) remain elusive. We propose an electrocardiogram (ECG) analysis designed to (1) refine selection of patients most likely to benefit from ablation, and (2) examine the temporal evolution of AF organization indices that could act as clinical indicators of ongoing ablation effectiveness and completeness. Method: Twelve-lead ECG was continuously recorded in 40 patients (61 ± 8 years) during stepwise CA (step-CA) procedures for treatment of pers-AF (sustained duration 19 ± 11 months). Following standard pre-processing, ECG signals were divided into 10-s epochs and labeled according to their temporal placement: pre-PVI (baseline), dur-PVI (during pulmonary vein isolation), and post-PVI (during complex-fractionated atrial electrograms and linear ablation). Instantaneous frequency (IF), adaptive organization index (AOI), sample entropy (SampEn) and f-wave amplitude (FWA) measures were calculated and analyzed during each of the three temporal steps. Temporal evolution of these measures was assessed using a statistical test for mean value transitions, as an indicator of changes in AF organization. Results were then compared between: (i) patients grouped according to step-CA outcome; (ii) patients grouped according to type of arrhythmia recurrence following the procedure, if applicable; (iii) within the same patient group during the three different temporal steps. Results: Stepwise CA patient outcomes were as follows: (1) left-atrium (LA) terminated, not recurring (LTN, n = 8), (2) LA terminated, recurring (LTR, n = 20), and (3) not LA terminated, all recurring at follow-up (NLT, n = 12). Among the LTR and NLT patients, recurrence occurred as AF in seven patients and atrial tachycardia or atrial flutter (AT/AFL) in the remaining 25 patients. The ECG measures indicated the lowest level of organization in the NLT group for all ablation steps. The highest organization was observed in the LTN group, while the LTR group displayed an intermediate level of organization. Regarding time evolution of ECG measures in dur-PVI and post-PVI recordings, stepwise ablation led to increases in AF organization in most patients, with no significant differences between the LTN, LTR, and NLT groups. The median decrease in IF and increase in AOI were significantly greater in AT/AFL recurring patients than in AF recurring patients; however, changes in the SampEn and FWA parameters were not significantly different between types of recurrence. Conclusion: Noninvasive ECG measures, though unable to predict arrhythmia recurrence following ablation, show the lowest levels of AF organization in patients that do not respond well to step-CA. Increasing AF organization in post-PVI may be associated with organized arrhythmia recurrence after a single ablation procedure.

Challenging the Limitations of Atrial Fibrillation Detection in the Presence of Other Cardiac Arrythmias.

Atrial fibrillation (AF) affects millions of people worldwide and needs to be diagnosed in its early stage to provide proper treatment. However, the numerous wearable devices available today are not yet able to discriminate AF episodes from other cardiac arrhythmias and merely detect normal vs abnormal rhythms.In this study we investigated the performance of a traditional classifier - designed to distinguish AF and sinus rhythm (SR) using inter-beat intervals (IBI) - when confronted with other - non-AF - arrhythmias. This classifier was challenged with data of 37 patients wearing an optical heart rate monitor device during catheter ablation procedures. We first analyzed the classification performance of pure AF vs SR and then gradually introduced non-AF arrhythmias in the time windows used for classification.We obtained a high classification performance (accuracy, sensitivity and specificity of 0.979, 1.000 and 0.966) for purely AF and SR. In contrast, when increasing the maximal possible number of non-AF arrhythmias to 50%, the performance decreased to an accuracy, sensitivity and specificity of 0.886, 0.998 and 0.853. While sinus tachycardia led to false positives the classification was not impaired by the presence of extrasystoles, bigeminy, bradycardia, frequent ectopic beats or atrial flutter.Our study quantifies to what extent a traditional IBI-based classifier is not sufficient to distinguish AF from other arrhythmias. Future work should concentrate on acquiring datasets with a high diversity of arrhythmias and employing new classification features.

Heart Rate Variability Triangular Index as a Predictor of Cardiovascular Mortality in Patients With Atrial Fibrillation.

Background Impaired heart rate variability (HRV) is associated with increased mortality in sinus rhythm. However, HRV has not been systematically assessed in patients with atrial fibrillation (AF). We hypothesized that parameters of HRV may be predictive of cardiovascular death in patients with AF. Methods and Results From the multicenter prospective Swiss-AF (Swiss Atrial Fibrillation) Cohort Study, we enrolled 1922 patients who were in sinus rhythm or AF. Resting ECG recordings of 5-minute duration were obtained at baseline. Standard parameters of HRV (HRV triangular index, SD of the normal-to-normal intervals, square root of the mean squared differences of successive normal-to-normal intervals and mean heart rate) were calculated. During follow-up, an end point committee adjudicated each cause of death. During a mean follow-up time of 2.6±1.0 years, 143 (7.4%) patients died; 92 deaths were attributable to cardiovascular reasons. In a Cox regression model including multiple covariates (age, sex, body mass index, smoking status, history of diabetes mellitus, history of hypertension, history of stroke/transient ischemic attack, history of myocardial infarction, antiarrhythmic drugs including ß blockers, oral anticoagulation), a decreased HRV index ≤ median (14.29), but not other HRV parameters, was associated with an increase in the risk of cardiovascular death (hazard ratio, 1.7; 95% CI, 1.1-2.6; P=0.01) and all-cause death (hazard ratio, 1.42; 95% CI, 1.02-1.98; P=0.04). Conclusions The HRV index measured in a single 5-minute ECG recording in a cohort of patients with AF is an independent predictor of cardiovascular mortality. HRV analysis in patients with AF might be a valuable tool for further risk stratification to guide patient management. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT02105844.

Severe and uniform bi-atrial remodeling measured by dominant frequency analysis in persistent atrial fibrillation unresponsive to ablation.

BACKGROUND: High values of ECG and intracardiac dominant frequency (DF) are indicative of significant atrial remodeling in persistent atrial fibrillation (peAF). We hypothesized that patients with peAF unresponsive to ablation display higher ECG and intracardiac DFs than those remaining in sinus rhythm (SR) on the long term. METHODS: Forty consecutive patients underwent stepwise ablation for peAF (sustained duration 19 ± 11 months). Electrograms were recorded before ablation at 13 left atrium (LA) sites and at the right atrial appendage (RAA) and coronary sinus (CS) synchronously to the ECG. DF was defined as the highest peak within the power spectrum. RESULTS: peAF was terminated within the LA in 28 patients (left-terminated [LT]), whereas 12 patients remaining in AF after ablation (not left-terminated [NLT]) were cardioverted. Over a mean follow-up of 34 ± 14 months, all 12 NLT patients had a recurrence. Of the LT patients, 71% had a recurrence (20/28, LT_Rec), while 29% remained in SR throughout the follow-up (8/28, LT_SR). DF values and correlations between pairs of LA appendage (LAA), RAA, and CS DFs showed distinctive patterns among the subgroups. The NLT subgroup displayed the highest ECG and intracardiac DFs, with strong intragroup homogeneity between pairs of CS and LAA DFs, and to a lesser extent between pairs of CS and RAA DFs. Conversely, the LT_SR subgroup showed the lowest DFs, with significant intragroup heterogeneity between pairs of CS and both LAA and RAA DFs. CONCLUSIONS: Patients with peAF unresponsive to ablation show high surface and intracardiac DFs indicative of severe and uniform bi-atrial remodeling.

REWARD: Design, Optimization, and Evaluation of a Real-Time Relative-Energy Wearable R-Peak Detection Algorithm.

Wearable devices are an unobtrusive, cost-effective means of continuous ambulatory monitoring of chronic cardiovascular diseases. However, on these resource-constrained systems, electrocardiogram (ECG) processing algorithms must consume minimal power and memory, yet robustly provide accurate physiological information. This work presents REWARD, the Relative-Energy-based WeArable R-Peak Detection algorithm, which is a novel ECG R-peak detection mechanism based on a nonlinear filtering method called Relative-Energy (Rel-En). REWARD is designed and optimized for real-time execution on wearable systems. Then, this novel algorithm is compared against three state-of-the-art real-time R-peak detection algorithms in terms of accuracy, memory footprint, and energy consumption. The Physionet QT and NST Databases were employed to evaluate the algorithms' accuracy and robustness to noise, respectively. Then, a 32-bit ARM Cortex-M3-based microcontroller was used to measure the energy usage, computational burden, and memory footprint of the four algorithms. REWARD consumed at least 63% less energy and 32% less RAM than the other algorithms while obtaining comparable accuracy results. Therefore, REWARD would be a suitable choice of R-peak detection mechanism for wearable devices that perform more complex ECG analysis, whose algorithms require additional energy and memory resources.

AltitudeOmics: Spontaneous Baroreflex Sensitivity During Acclimatization to 5,260 m: A Comparison of Methods.

INTRODUCTION: Baroreflex sensitivity (BRS) is essential to ensure rapid adjustment to variations in blood pressure (BP). Spontaneous baroreflex function can be assessed using continuous recordings of blood pressure. The goal of this study was to compare four methods for BRS quantification [the sequence, Bernardi's (BER), frequency and transfer function methods] to identify the most consistent method across an extreme range of conditions: rest and exercise, in normoxia, hypoxia, hypocapnia, and hypercapnia. METHODS: Using intra-radial artery BP in young healthy participants, BRS was calculated and compared using the four methods in normoxia, acute and chronic hypoxia (terrestrial altitude of 5,260 m) in hypocapnia (hyperventilation), hypercapnia (rebreathing) and during ramp exercise to exhaustion. RESULTS: The sequence and BER methods for BRS estimation showed good agreement during the resting and exercise protocols, whilst the ultra- and very-low frequency bands of the frequency and transfer function methods were more discrepant. Removing respiratory frequency from the blood pressure traces affected primarily the sequence and BER methods and occasionally the frequency and transfer function methods. DISCUSSION/CONCLUSION: The sequence and BER methods contained more respiratory related information than the frequency and transfer function methods, indicating that the former two methods predominantly rely on respiratory effects of BRS. BER method is recommended because it is the easiest to compute and even though it tends to overestimate BRS compared to the sequence method, it is consistent with the other methods, whilst its interquartile range is the smallest.

Can one detect atrial fibrillation using a wrist-type photoplethysmographic device?

This study aims at evaluating the potential of a wrist-type photoplethysmographic (PPG) device to discriminate between atrial fibrillation (AF) and other types of rhythm. Data from 17 patients undergoing catheter ablation of various arrhythmias were processed. ECGs were used as ground truth and annotated for the following types of rhythm: sinus rhythm (SR), AF, and ventricular arrhythmias (VA). A total of 381/1370/415 10-s epochs were obtained for the three categories, respectively. After pre-processing and removal of segments corresponding to motion artifacts, two different types of feature were derived from the PPG signals: the interbeat interval-based features and the wave-based features, consisting of complexity/organization measures that were computed either from the PPG waveform itself or from its power spectral density. Decision trees were used to assess the discriminative capacity of the proposed features. Three classification schemes were investigated: AF against SR, AF against VA, and AF against (SR&VA). The best results were achieved by combining all features. Accuracies of 98.1/95.9/95.0 %, specificities of 92.4/88.7/92.8 %, and sensitivities of 99.7/98.1/96.2 % were obtained for the three aforementioned classification schemes, respectively. Graphical Abstract Atrial fibrillation detection using PPG signals.

AltitudeOmics: Baroreflex Sensitivity During Acclimatization to 5,260 m.

Introduction: Baroreflex sensitivity (BRS) is essential to ensure rapid adjustment to variations in blood pressure (BP). Little is known concerning the adaptive responses of BRS during acclimatization to high altitude at rest and during exercise. Methods: Twenty-one healthy sea-level residents were tested near sea level (SL, 130 m), the 1st (ALT1) and 16th day (ALT16) at 5,260 m using radial artery catheterization. BRS was calculated using the sequence method (direct interpretation of causal link between BP and heartrate). At rest, subjects breathed a hyperoxic mixture (250 mmHg O2, end tidal) to isolate the preponderance of CO2 chemoreceptors. End-tidal CO2 varied from 20 to 50 mmHg to assess peripheral chemoreflex. Rebreathing provoked incremental increase in CO2, increasing BP to assess baroreflex. During incremental cycling exercise to exhaustion, subjects breathed room air. Results: Resting BRS decreased in ALT1 which was exacerbated in ALT16. This decrease in ALT1 was reversible upon additional inspired CO2, but not in ALT16. BRS decrease during exercise was greater and occurred at lower workloads in ALT1 compared to SL. At ALT16, this decrease returned toward SL values. Discussion/Conclusion: This study is the first to report attenuated BRS in acute hypoxia, exacerbated in chronic hypoxia. In ALT1, hypocapnia triggered BRS reduction whilst in ALT16 resetting of chemoreceptor triggered BRS reduction. The exercise BRS resetting was impaired in ALT1 but normalized in ALT16. These BRS decreases indicate decreased control of BP and may explain deteriorations of cardiovascular status during exposure to high altitude.

The Effect of Lower-Body Positive Pressure on the Cardiorespiratory Response at Rest and during Submaximal Running Exercise.

Anti-gravity treadmills facilitate locomotion by lower-body positive pressure (LBPP). Effects on cardiorespiratory regulation are unknown. Healthy men (30 ± 8 y, 178.3 ± 5.7 cm, 70.3 ± 8.0 kg; mean ± SD) stood upright (n = 10) or ran (n = 9) at 9, 11, 13, and 15 km.h-1 (5 min stages) with LBPP (0, 15, 40 mmHg). Cardiac output (CO), stroke volume (SV), heart rate (HR), blood pressure (BP), peripheral resistance (PR), and oxygen uptake (VO2) were monitored continuously. During standing, LBPP increased SV [by +29 ± 13 (+41%) and +42 ± 15 (+60%) ml, at 15 and 40 mmHg, respectively (p < 0.05)] and decreased HR [by -15 ± 6 (-20%) and -22 ± 9 (-29%) bpm (p < 0.05)] resulting in a transitory increase in CO [by +1.6 ± 1.0 (+32%) and +2.0 ± 1.0 (+39%) l.min-1 (p < 0.05)] within the first seconds of LBPP. This was accompanied by a transitory decrease in end-tidal PO2 [by -5 ± 3 (-5%) and -10 ± 4 (-10%) mmHg (p < 0.05)] and increase in VO2 [by +66 ± 53 (+26%) and +116 ± 64 (+46%) ml.min-1 (p < 0.05)], suggesting increased venous return and pulmonary blood flow. The application of LBPP increased baroreflex sensitivity (BRS) [by +1.8 ± 1.6 (+18%) and +4.6 ± 3.7 (+47%) at 15 and 40 mmHg LBPP, respectively P < 0.05]. After reaching steady-state exercise CO vs. VO2 relationships remained linear with similar slope and intercept for each participant (mean R2 = 0.84 ± 0.13) while MAP remained unchanged. It follows that (1) LBPP affects cardiorespiratory integration at the onset of exercise; (2) at a given LBPP, once reaching steady-state exercise, the cardiorespiratory load is reduced proportionally to the lower metabolic demand resulting from the body weight support; (3) the balance between cardiovascular response, oxygen delivery to the exercising muscles and blood pressure regulation is maintained at exercise steady-state; and (4) changes in baroreflex sensitivity may be involved in the regulation of cardiovascular parameters during LBPP.

Overload blunts baroreflex only in overreached athletes.

OBJECTIVES: Heart rate variability (HRV) is commonly used to diagnose overreaching and monitor athletes' responses to training. Baroreflex sensitivity (BRS) is modified by changes in training load and might be another means to detect overreaching. The goal of this study was to assess BRS and HRV changes in two groups of athletes responding either negatively (FOR) or positively (AF) to similar training overload. DESIGN: Fifteen athletes performed 2-week baseline (BSL) training followed by 3-week overload (+45%; OVL) and 2-week recovery (-20%; RCV). METHODS: HRV, training load and subjective fatigue were measured daily via questionnaires. BRS, salivary cortisol and testosterone, and submaximal exercise and maximal 3-km run performances were measured at the end of each period. RESULTS: Based on their performance change during OVL, 8 athletes were diagnosed as FOR and 7 as AF. Subjective fatigue was increased in FOR athletes during OVL. BRS increased in AF but not in FOR athletes during RCV. At the end of RCV, cortisol and testosterone were higher than BSL in both groups. CONCLUSIONS: Three weeks of similar training overload can induce either performance enhancement or overreaching. The changes in submaximal exercise and maximal performances and in subjective fatigue were the fastest-responding parameters that distinguished the two groups of athletes during OVL. Training overload blunted the increase in BRS in FOR only. Most of the differences in BRS were observed during the recovery period. BRS appears to be a more sensitive parameter than HRV for early monitoring of responses to training.

Concealed abnormal atrial phenotype in patients with Brugada syndrome and no history of atrial fibrillation.

OBJECTIVES: The electrocardiogram (ECG) of patients with BrS in sinus rhythm might reflect intrinsic atrial electrical abnormalities independent from any previous atrial fibrillation (AF). Aim of this study is to investigate the presence of P-wave abnormalities in patients with BrS and no history of AF, and to compare them with those displayed by patients with documented paroxysmal AF and by healthy subjects. METHODS: Continuous 5-min 16-lead ECG recordings in sinus rhythm were obtained from 72 participants: 32 patients with a type 1 Brugada ECG, 20 patients with a history of paroxysmal AF and 20 age-matched healthy subjects. Different ECG-based features were computed on the P-wave first principal component representing the predominant morphology across leads and containing the maximal information on atrial depolarization: duration, full width half maximum (FWHM), area under the curve and number of peaks in the wave. RESULTS: Patients with BrS and no history of AF (mean age: 53±12years; males: 28 pts., spontaneous type 1 ECG: 20 pts., SCN5A mutation: 10 pts) presented with longer P-wave duration, higher FWHM and wider area under the curve in comparison with the other two groups. Although P-wave features were abnormal in BrS patients, no significant difference was found between patients with spontaneous type 1 ECG and ajmaline-induced type 1 ECG, symptomatic and asymptomatic ones, and between patients with a pathogenic SCNA5 mutation and patients without a known gene mutation. CONCLUSIONS: Patients with BrS without previous occurrence of AF present with a concealed abnormal atrial phenotype. In these patients atrial electrical abnormalities can be detected even in the absence of an overt ECG ventricular phenotype, symptoms and a SCN5A mutation.