Statistical analysis of the sequence of heartbeats can provide information about the state of health of the heart. We used a variety of statistical measures to identify the form of the point process that describes the human heartbeat. These measures are based on both interevent intervals and counts, and include the interevent-interval histogram, interval-based periodogram, rescaled range analysis, the event-number histogram, Fano-factor, Allan Factor, and generalized-rate-based periodogram. All of these measures have been applied to data from both normal and heart-failure patients, and various surrogate versions thereof. The results show that almost all of the interevent-interval and the long-term counting statistics differ in statistically significant ways for the two classes of data. Several measures reveal 1/f-type fluctuations (long-duration power-law correlation). The analysis that we have conducted suggests the use of a conveniently calculated, quantitative index, based on the Allan factor, that indicates whether a particular patient does or does not suffer from heart failure. The Allan factor turns out to be particularly useful because it is easily calculated and is jointly responsive to both short-term and long-term characteristics of the heartbeat time series. A phase-space reconstruction based on the generalized heart rate is used to obtain a putative attractor's capacity dimension. Though the dependence of this dimension on the embedding dimension is consistent with that of a low-dimensional dynamical system (with a larger apparent dimension for normal subjects), surrogate-data analysis shows that identical behavior emerges from temporal correlation in a stochastic process. We present simulated results for a purely stochastic integrate-and-fire model, comprising a fractal-Gaussian-noise kernel, in which the sequence of heartbeats is determined by level crossings of fractional Brownian motion. This model characterizes the statistical behavior of the human electrocardiogram remarkably well, properly accounting for the behavior of all of the measures studied, over all time scales.

BackgroundPatients with a myocardial bridge (MB) and no significant obstructive coronary artery disease (CAD) may experience angina presumably from ischemia, but noninvasive assessment has been limited and the underlying mechanism poorly understood. This study seeks to correlate a novel exercise echocardiography (EE) finding for MBs with invasive structural and hemodynamic measurements.Methods and ResultsEighteen patients with angina and an EE pattern of focal end‐systolic to early‐diastolic buckling in the septum with apical sparing were prospectively enrolled for invasive assessment. This included coronary angiography, left anterior descending artery (LAD) intravascular ultrasound (IVUS), and intracoronary pressure and Doppler measurements at rest and during dobutamine stress. All patients were found to have an LAD MB on IVUS. The ratios of diastolic intracoronary pressure divided by aortic pressure at rest (Pd/Pa) and during dobutamine stress (diastolic fractional flow reserve [dFFR]) and peak Doppler flow velocity recordings at rest and with stress were successfully performed in 14 patients. All had abnormal dFFR (≤0.75) at stress within the bridge, distally or in both positions, and on average showed a more than doubling in peak Doppler flow velocity inside the MB at stress. Seventy‐five percent of patients had normalization of dFFR distal to the MB, with partial pressure recovery and a decrease in peak Doppler flow velocity.ConclusionsA distinctive septal wall motion abnormality with apical sparing on EE is associated with a documented MB by IVUS and a decreased dFFR. We posit that the septal wall motion abnormality on EE is due to dynamic ischemia local to the compressed segment of the LAD from the increase in velocity and decrease in perfusion pressure, consistent with the Venturi effect.

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Despite a long history of research, the development of synthetic tactual aids to support the communication of speech has proven to be a difficult task. The current paper describes a new tactile speech device based on the presentation of phonemic-based tactile codes. The device consists of 24 tactors under independent control for stimulation at the forearm. Using properties that include frequency and waveform of stimulation, amplitude, spatial location, and movement characteristics, unique tactile codes were designed for 39 consonant and vowel phonemes of the English language. The strategy for mapping the phonemes to tactile symbols is described, and properties of the individual phonemic codes are provided. Results are reported for an exploratory study of the ability of ten young adults to identify the tactile symbols. The participants were trained to identify sets of consonants and vowels, before being tested on the full set of 39 tactile codes. The results indicate a mean recognition rate of 86% correct within one to four hours of training across participants. Thus, these results support the viability of a phonemic-based approach for conveying speech information through the tactile sense.