Minimal window duration for accurate HRV recording in athletes

Heart rate variability (HRV) is non-invasive and commonly used for monitoring responses to training loads, fitness, or overreaching in athletes. Yet, the recording duration for aseries of RR-intervals varies from 1 to 15 min in the literature. The aim of the present work was to assess the minimum record duration to obtain reliableHRV results. RR-intervalsfrom 159 orthostatic tests (7 min supine, SU, followed by 6 min standing, ST) were analyzed. Reference windows were 4 min in SU (min 3–7) and 4 min in ST (min 9–13).Those windows were subsequently divided and the analyses were repeated on eight different fractioned windows: the first min (0–1), the second min (1–2), the third min (2–3),the fourth min (3–4), the first 2 min (0–2), the last 2 min (2–4), the first 3 min (0–3), and thelast 3 min (1–4). Correlation and Bland & Altman statistical analyses were systematically performed. The analysis window could be shortened to 0–2 instead of 0–4 for RMSSD only, whereas the 4-min window was necessary for LF and total power. Since there is a need for 1 min of baseline to obtain a steady signal prior the analysis window, we conclude that studies relying on RMSSD may shorten the windows to 3 min (=1+2)in SU or seated position only and to 6 min (=1+2 min SU plus 1+2 min ST) if there is an orthostatic test. Studies relying on time- and frequency-domain parameters need a minimum of 5 min (=1+4) min SU or seated position only but require 10 min (=1+4 minSU plus 1+4 min ST) for the orthostatic tes

Intermittent atrial tachycardia facilitates atrial fibrillation by a shortening of activation recovery interval

Introduction: We recently observed in a chronic ovine model that a shortening of action potential duration (APD) as assessed by the activation recovery interval (ARI) may be a mechanism whereby pacing-induced atrial tachycardia (PIAT) facilitates atrial fibrillation (AF), mediated by a return to 1:1 atrial capture after the effective refractory period has been reached. The aim of the present study is to evaluate the effect of long term intermittent burst pacing on ARI before induction of AF.Methods: We specifically developed a chronic ovine model of PIAT using two pacemakers (PM) each with a right atrial (RA) lead separated by ∼2cm. The 1st PM (Vitatron T70) was used to record a broadband unipolar RA EGM (800 Hz, 0.4 Hz high pass filter). The 2nd was used to deliver PIAT during electrophysiological protocols at decremental pacing CL (400 beats, from 400 to 110ms) and long term intermittent RA burst pacing to promote electrical remodeling (5s of burst followed by 2s of sinus rhythm) until onset of sustained AF. ARI was defined as the time difference between the peak of the atrial repolarization wave and the first atrial depolarization. The mean ARIs of paired sequences (before and after remodeling), each consisting of 20 beats were compared.Results: As shown in the figure, ARIs (n=4 sheep, 46 recordings) decreased post remodeling compared to baseline (86±19 vs 103±12 ms, p<0.05). There was no difference in atrial structure as assessed by light microscopy between control and remodeled sheep.Conclusions: Using standard pacemaker technology, atrial ARIs as a surrogate of APDs were successfully measured in vivo during the electrical remodeling process leading to AF. The facilitation of AF by PIAT mimicking salvos from pulmonary veins is heralded by a significant shortening of ARI

Human-Computer adaptation for EEG based communication

Brain-computer interface (BCI) systems allow the user to interact with a computer by merely thinking. Successful BCI operation depends on the continuous adaptation of the system to the user and on the user motivation. This paper presents a model of continuous adaptation using kernel based dynamic data characterization. Additionally, the adaptive capabilities of the brain are engaged by providing feedback to the user who can modulate her mental activity so as to make the BCI accomplish her intents

Evaluation of Ablation Patterns Using a Biophysical Model of Atrial Fibrillation

Atrial fibrillation (AF) is the most common form of cardiac arrhythmia. Surgical/Radiofrequency (RF) ablation is a therapeutic procedure that consists of creating lines of conduction block to interrupt AF. The present study evaluated 13 different ablation patterns by means of a biophysical model of the human atria. In this model, ablation lines were abruptly applied transmurally during simulated sustained AF, and success rate, time to AF termination and average beat-to-beat interval were documented. The gold standard Cox's Maze III procedure was taken as reference. The effectiveness of twelve less invasive patterns was compared to it. In some of these incomplete lines (entailing a gap) were simulated. Finally, the computer simulations were compared to clinical data. The results show that the model reproduces observations made in vivo: (1) the Maze III is the most efficient ablation procedure; (2) less invasive patterns should include lines in both right and left atrium; (3) incomplete ablation lines between the pulmonary veins and the mitral valve annulus lead to uncommon flutter; (4) computer simulations of incomplete lines are consistent with clinical results of non-transumural RF ablation. Biophysical modeling may therefore be considered as a useful tool for understanding the mechanisms underlying AF therapie

Observer of the human cardiac sympathetic nerve activity using non-causal blind source separation

Nous présentons une méthode pour la reconstruction aveugle de deux variables de contrôle du système cardiovasculaire en utilisant seulement le rythme cardiaque et la tension artérielle. Le modèle de reconstruction est basé sur la séparation aveugle de source dans des mélanges convolutifs. L'algorithme d'apprentissage associé est déduit d'une approche de maximisation d'information. L'efficacité de la méthode a été verifiée en utilisant l'activité musculaire sympathique comme indicateur de l'activité cardiaque sympathique. Des résultats très satisfaisants et prometteurs ont été obtenus sur les signaux de cinq sujets

Extraction of Audio Features Specific to Speech using Information Theory and Differential Evolution

We present a method that exploits an information theoretic framework to extract optimized audio features using the video information. A simple measure of mutual information (MI) between the resulting audio features and the video ones allows to detect the active speaker among different candidates. Our method involves the optimization of an MI-based objective function. No approximation is introduced to solve this optimization problem, neither concerning the estimation of the probability density functions (pdf) of the features, nor the cost function itself. The pdf are estimated from the samples using a non-parametric approach. As far as concern the optimization process itself, three different optimization methods (one local and two globals) are compared in this paper. The Differential Evolution algorithm is shown to be outstanding performant for our problem and is threrefore eventually retains. Two information theoretic optimization criteria are compared and their ability to extract audio features specific to speeh is discussed. As a result, our method achieves a speaker detection rate of 100% on our test sequences, and of 95% on a state-of-the-art sequence

Ventricular and Atrial Activity Estimation Through Sparse ECG Signal Decompositions

This paper explores a novel approach for ventricular and atrial activities estimation in electrocardiogram (ECG) signals, based on sparse source separation. Sparse decompositions of ECG over signal-adapted multi-component dictionaries can lead to natural separation of its components. In this work, dictionaries of functions adapted to ventricular and atrial activities are respectively defined. Then, the weighted orthogonal matching pursuit algorithm is used to unmix the two components of ECG signals. Despite the simplicity of the approach, results are very promising, showing the capacity of the algorithm to generate realistic estimations of atrial and ventricular activities

Sparse Decompositions for Ventricular and Atrial Activity Separation

Atrial Fibrillation (AF) is the most common type of human arrhythmia. Beside its clinical description as absolute arrhythmia, its diagnosis has been assessed for years by visual inspection of the surface electrocardiogram (ECG). Due to the much higher amplitude of the electrical ventricular activity, the analysis of atrial fibrillation requires the previous isolation of the atrial activity component. In this work, an approach to separate atrial and ventricular signal components, decomposing the signal over a redundant multi-component dictionary, is explored. This idea requires a careful dictionary design, taking into account the signal structures and characteristics. Being the dictionary overcomplete, more than one decomposition of a given signal is possible. However, we are interested in sparse solutions. A key point in this work is also, jointly with the dictionary design, to determine the appropriate analysis technique for the best performance of the ECG components separation. Greedy Algorithms, such as Matching Pursuit, or optimization methods, such as Basis Pursuit are studied. To improve our signal separation, the a priori knowledge we have from the ECG signals is also used. Finally, the solution proposed is tested over an ECG database

Search for the exotic Ξ−−(1860)\Xi^{--}(1860) Resonance in 340GeV/c Σ−\Sigma^--Nucleus Interactions

We report on a high statistics search for the $\Xi^{--}(1860)$ resonance in $\Sigma^-$-nucleus collisions at 340GeV/c. No evidence for this resonance is found in our data sample which contains 676000 $\Xi^-$ candidates above background. For the decay channel $\Xi^{--}(1860) \to \Xi^-\pi^-$ and the kinematic range 0.15$<x_F<$0.9 we find a 3$\sigma$ upper limit for the production cross section of 3.1 and 3.5 $\mu$b per nucleon for reactions with carbon and copper, respectively.Comment: 5 pages, 4 figures, modification of ref. 43 and 4