1,721,051 research outputs found
TIME DELAY BETWEEN RR AND RT HEART BEAT INTERVALS ASSESSED BY TREND EXTRACTION OF EXERCISE TEST DATA
No full textThe RR and RT time intervals extracted from the electrocardiogram measure respectively the duration of cardiac cycle and repolarization. The series of these intervals recorded during the exercise test are characterized by two trends: A decreasing one during the stress phase and an increasing one during the recovery, separated by a global minimum. We model these series as a sum of a deterministic trend and random fluctuations, and estimate the trend using methods of curve extraction: Running mean, polynomial fit, multi scale wavelet decomposition. We estimate the minimum location from the trend. Data analysis performed on a group of 20 healthy subjects provides evidence that the minimum of the RR series precedes the minimum of the RT series, with a time delay of about 19 seconds
Diagnosis of wide QRS tachyarrhythmias: poor atrial echogram specificity in cases of atrioventricular association.
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Analysis of extrema of heartbeat time series in exercise test.
No full textThe heartbeat time series of the electrocardiogram recorded during exercise test clearly reflects the physiological control mechanism of the autonomic nervous system on heart rate. This series shows both decreasing and increasing trends and variability of the variance. We analyse the series of intervals between two consecutive extrema, i.e. the durations of accelerations or decelerations of heart rate. We compute the distribution of the length of these intervals and their mean in a model of stationary independent variables, where they are independent of the variables' distribution. We use the mean length as discriminant statistics to compare stress and recovery phases. Data analysis performed over the heartbeat series of 14 healthy subjects shows significant difference between stress and recovery
Modeling trend and time-varying variance of heart beat RR intervals during stress test
No full textThe heart beat RR intervals extracted from the electrocardiogram recorded during the stress test show a non stationary profile consisting of a decreasing trend during the exercise phase, an increasing trend during the recovery and a global minimum (acme). In addition this time series exhibits a time-varying variance. We decompose the series into a deterministic trend and random fluctuation. The trend is obtained as an exponential fit of the data; the fluctuation is modeled as a mean reverting process driven by the trend, in which the random innovation has a time-varying variance. Data analysis, performed on ambulatory recorded electrocardiograms of 10 healthy subjects, shows that the model describes correctly the data series on a scale of at least 300 beats. © 2011 World Scientific Publishing Company
Trend extraction in functional data of amplitudes of R and T waves in exercise electrocardiogram
No full textThe amplitudes of R and T waves of the electrocardiogram recorded during the
exercise test show both large inter- and intra-individual variability in response to
stress. We analyze a dataset of 65 normal subjects undergoing ambulatory test. We
model the dataset of R and T series in the framework of functional data, assuming
that the individual series are realizations of a non stationary process, centered at the
population trend. We test the time variability of this trend computing a simultaneous
confidence band and the zero crossing of its derivative. The analysis
shows that the amplitudes of the R and T waves have opposite responses to stress,
consisting respectively in a bump and a dip at the early recovery stage.
Our findings support the existence of a relationship between R and T wave
amplitudes and respectively diastolic and systolic ventricular volumes
Study of supplemental oral l-Arginine in Hypertensives treated with enalapril + hydrochlorothiazide
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