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Alan H Feiveson

Publications and source records attributed to Alan H Feiveson.

3 recordsLinked to original sources

Month-to-month and year-to-year reproducibility of high frequency QRS ECG signals.

High frequency electrocardiography analyzing the entire QRS complex in the frequency range of 150 to 250 Hz may prove useful in the detection of coronary artery disease, yet the long-term stability of these waveforms has not been fully characterized. Therefore, we prospectively investigated the reproducibility of the root mean squared voltage, kurtosis, and the presence versus absence of reduced amplitude zones in signal averaged 12-lead high frequency QRS recordings acquired in the supine position one month apart in 16 subjects and one year apart in 27 subjects. Reproducibility of root mean squared voltage and kurtosis was excellent over these time intervals in the limb leads, and acceptable in the precordial leads using both the V-lead and CR-lead derivations. The relative error of root mean squared voltage was 12% month-to-month and 16% year-to-year in the serial recordings when averaged over all 12 leads. Reduced amplitude zones were also reproducible up to a rate of 87% and 81%, respectively, for the month-to-month and year-to-year recordings. We conclude that 12-lead high frequency QRS electrocardiograms are sufficiently reproducible for clinical use.

Adult↗

Real-time 12-lead high-frequency QRS electrocardiography for enhanced detection of myocardial ischemia and coronary artery disease.

Several studies have shown that diminution of the high-frequency (HF; 150-250 Hz) components present within the central portion of the QRS complex of an electrocardiogram (ECG) is a more sensitive indicator for the presence of myocardial ischemia than are changes in the ST segments of the conventional low-frequency ECG. However, until now, no device has been capable of displaying, in real time on a beat-to-beat basis, changes in these HF QRS ECG components in a continuously monitored patient. Although several software programs have been designed to acquire the HF components over the entire QRS interval, such programs have involved laborious off-line calculations and postprocessing, limiting their clinical utility. We describe a personal computer-based ECG software program developed recently at the National Aeronautics and Space Administration (NASA) that acquires, analyzes, and displays HF QRS components in each of the 12 conventional ECG leads in real time. The system also updates these signals and their related derived parameters in real time on a beat-to-beat basis for any chosen monitoring period and simultaneously displays the diagnostic information from the conventional (low-frequency) 12-lead ECG. The real-time NASA HF QRS ECG software is being evaluated currently in multiple clinical settings in North America. We describe its potential usefulness in the diagnosis of myocardial ischemia and coronary artery disease.

Adult↗

A statistical model for interpreting computerized dynamic posturography data.

Computerized dynamic posturography (CDP) is widely used for assessment of altered balance control. CDP trials are quantified using the equilibrium score (ES), which ranges from zero to 100, as a decreasing function of peak sway angle. The problem of how best to model and analyze ESs from a controlled study is considered. The ES often exhibits a skewed distribution in repeated trials, which can lead to incorrect inference when applying standard regression or analysis of variance models. Furthermore, CDP trials are terminated when a patient loses balance. In these situations, the ES is not observable, but is assigned the lowest possible score--zero. As a result, the response variable has a mixed discrete-continuous distribution, further compromising inference obtained by standard statistical methods. Here, we develop alternative methodology for analyzing ESs under a stochastic model extending the ES to a continuous latent random variable that always exists, but is unobserved in the event of a fall. Loss of balance occurs conditionally, with probability depending on the realized latent ES. After fitting the model by a form of quasi-maximum-likelihood, one may perform statistical inference to assess the effects of explanatory variables. An example is provided, using data from the NIH/NIA Baltimore Longitudinal Study on Aging.

Adult↗