Do existing measures of Poincaré plot geometry reflect nonlinear features of heart rate variability?

Heart rate variability (HRV) is concerned with the analysis of the intervals between heartbeats. An emerging analysis technique is the Poincaré plot, which takes a sequence of intervals and plots each interval against the following interval. The geometry of this plot has been shown to distinguish between healthy and unhealthy subjects in clinical settings. The Poincaré plot is a valuable HRV analysis technique due to its ability to display nonlinear aspects of the interval sequence. The problem is, how do we quantitatively characterize the plot to capture useful summary descriptors that are independent of existing HRV measures? Researchers have investigated a number of techniques: converting the two-dimensional plot into various one-dimensional views; the fitting of an ellipse to the plot shape; and measuring the correlation coefficient of the plot. We investigate each of these methods in detail and show that they are all measuring linear aspects of the intervals which existing HRV indexes already specify. The fact that these methods appear insensitive to the nonlinear characteristics of the intervals is an important finding because the Poincaré plot is primarily a nonlinear technique. Therefore, further work is needed to determine if better methods of characterizing Poincaré plot geometry can be found.

Distortion properties of the interval spectrum of IPFM generated heartbeats for heart rate variability analysis

The integral pulse frequency modulation (IPFM) model converts a continuous-time signal into a modulated series of event times, often represented as a pulse train. The IPFM process is important to the field of heart rate variability (HRV) as a simple model of the sinus modulation of heart rate. In this paper, we discuss the distortion properties associated with employing the interval spectrum for the recovery of the input signal from an IPFM process's output pulse train. The results state, in particular for HRV, how precisely the interval spectrum can be used to infer the modulation signal responsible for a series of heartbeats. We have developed a detailed analytical approximation of the interval spectrum of an IPFM process with multiple sinusoids as the input signal. Employing this result, we describe the structure and the distortion of the interval spectrum. The distortion properties of the interval spectrum are investigated systematically for a pair of frequency components. The effects of linear and nonlinear distortion of the fundamentals, the overall contribution of harmonic components to the total power, the relative contribution of "folded back" power due to aliasing and the total distortion of the input spectrum are investigated. We also provide detailed comparisons between the interval spectrum and the spectrum of counts (SOC). The spectral distortion is significant enough that caution should be taken when interpreting the interval spectrum, especially for high frequencies or large modulation amplitudes. Nevertheless, the distortion levels are not significantly larger than those of the SOC. Therefore, the spectrum of intervals may be considered a viable technique that suffers more distortion than the SOC.

An examination of the relationship between resting heart rate variability and heart rate reactivity to a mental arithmetic stressor

Resting heart rate variability can be an index of sympathetic or parasympathetic dominance, according to the frequency of the variability studied. Sympathetic dominance of this system has been linked to increased risk of cardiovascular disease (CVD). Similarly, rapid and dramatic increases in heart rate reactivity to a stressor task have also been suggested as indicating increased risk of CVD via atherogenesis. Although both of these variables have been related to the development of cardiovascular disease, and both may be related to increased sympathetic activity or parasympathetic withdrawal, most research studies have tended to focus on either variable independently of the other. In order to investigate whether these two indices of stressor reactivity were related in relatively young and healthy subjects, resting heart rate variability data were collected from 80 volunteers for 20 minutes. In addition, heart rate reactivity data were collected during a 2-minute mental arithmetic stressor, which has been previously shown to induce significant increases in heart rate. After classifying subjects according to whether their heart rate variability data were above or below the mean for their gender, heart rate reactivity data were examined via MANOVA to detect significant differences between subject groups. Females showed significant effects, and males showed nonsignificant trends, but these two sets of data were in different directions, suggesting that gender may be a confounding factor in the relationship between heart rate reactivity and heart rate variability.

Heart rate variability

Heart rate variability (HRV) provides a non-invasive means of quantifying cardiac autonomic activity. It has been shown to be a powerful predictor of arrhythmia related complications in patients surviving the acute phase of myocardial infarction. This article highlights some of the important new clinical applications of this technology and provides a brief description of the technical methods involved in gathering and interpreting the data.

Dental fellowships in developmental disabilities help broaden care of disabled

Continuation of the national trend toward deinstitutionalization and community placement for persons with developmental disabilities, physical handicaps and other medical problems will mean increased demand for dentists trained to care for this segment of the population. The New York State Office of Mental Retardation and Developmental Disabilities now offers dental fellowships in developmental disabilities to help fill the learning gap.