Assessing aortic stenosis using sample entropy of the phonocardiographic signal in dogs.

In aortic valve stenosis (AS), heart murmurs arise as an effect of turbulent blood flow distal to the obstructed valves. With increasing AS severity, the flow becomes more unstable, and the ensuing murmur becomes more complex. We hypothesize that these hemodynamic flow changes can be quantified based on the complexity of the phonocardiographic (PCG) signal. In this study, sample entropy (SampEn) was investigated as a measure of complexity using a dog model. Twenty-seven boxer dogs with various degrees of AS were examined with Doppler echocardiography, and the peak aortic flow velocity ( V(max)) was used as a reference of AS severity. SampEn correlated to V(max) with R = 0.70 using logarithmic regression. In a separate analysis, significant differences were found between physiologic murmurs and murmurs caused by AS ( p << 0.05), and the area under a receiver operating characteristic curve was calculated to 0.96. Comparison with previously presented PCG measures for AS assessment showed improved performance when using SampEn, especially for differentiation between physiological murmurs and murmurs caused by mild AS. Studies in patients will be needed to properly assess the technique in humans.

Time-frequency and complexity analyses for differentiation of physiologic murmurs from heart murmurs caused by aortic stenosis in Boxers.

OBJECTIVE: To investigate whether time-frequency and complexity analyses of heart murmurs can be used to differentiate physiologic murmurs from murmurs caused by aortic stenosis (AS) in Boxers. ANIMALS: 27 Boxers with murmurs. PROCEDURES: Dogs were evaluated via auscultation and echocardiography. Analyses of time-frequency properties (TFPs; ie, maximal murmur frequency and duration of murmur frequency > 200 Hz) and correlation dimension (T(2)) of murmurs were performed on phonocardiographic sound data. Time-frequency property and T(2) analyses of low-intensity murmurs in 16 dogs without AS were performed at 7 weeks and 12 months of age. Additionally, TFP and T(2) analyses were performed on data obtained from 11 adult AS-affected dogs with murmurs. RESULTS: In dogs with low-intensity murmurs, TFP or T(2) values at 7 weeks and 12 months did not differ significantly. For differentiation of physiologic murmurs from murmurs caused by mild AS, duration of murmur frequency > 200 Hz was useful and the combination assessment of duration of frequency > 200 Hz and T(2) of the murmur had a sensitivity of 94% and a specificity of 82%. Maximal murmur frequency did not differentiate dogs with AS from those without AS. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggested that assessment of the duration of murmur frequency > 200 Hz can be used to distinguish physiologic heart murmurs from murmurs caused by mild AS in Boxers. Combination of this analysis with T(2) analysis may be a useful complementary method for diagnostic assessment of cardiovascular function in dogs.

Detection of the third heart sound using a tailored wavelet approach: method verification.

Heart sounds can be considered as mechanical fingerprints of myocardial function. The third heart sound normally occurs in children but disappears with maturation. The sound can also appear in patients with heart failure. The sound is characterised by its low-amplitude and low-frequency content, which makes it difficult to identify by the traditional use of the stethoscope. A wavelet-based method has recently been developed for detection of the third heart sound. This study investigated if the third heart sound could be identified in patients with heart failure using this detection method. The method was also compared with auscultation using conventional phonocardiography and with characterisation of the patients with echocardiography. In the first study, 87% of the third heart sounds were detected using the wavelet method, 12% were missed, and 6% were false positive. In study 2, the wavelet-detection method identified 87% of the patients using the third heart sound, and regular phonocardiography identified two (25%) of the subjects.

An improved bioacoustic method for monitoring of respiration.

Reliable monitoring of respiration plays an important role in a broad spectrum of applications. Today, there are several methods for monitoring respiration, but none of them has proved to be satisfactory in all respects. We have recently developed a bioacoustic method that can accurately time respiration from tracheal sounds. The aim of this study is to tailor this bioacoustic method for monitoring purposes by introducing dedicated signal processing. The method was developed on a material of ten patients and then tested in another ten patients treated in an intensive care unit. By studying the differences in the variation of the spectral content between the different phases of respiration, the described method can distinguish between inspiration and expiration and can extract respiration frequency, and respiration pause periods. The system detected 98% of the inspirations and 99% of the expirations. This method for respiration monitoring has the advantage of being simple, robust and the sensor does not need to be placed closed to the face. A commercial heart microphone was used and we anticipate that further improvement in performance can be achieved trough optimization of sensor design.

Detection of the third heart sound using a tailored wavelet approach.

The third heart sound is normally heard during auscultation of younger individuals but disappears with increasing age. However, this sound can appear in patients with heart failure and is thus of potential diagnostic use in these patients. Auscultation of the heart involves a high degree of subjectivity. Furthermore, the third heart sound has low amplitude and a low-frequency content compared with the first and second heart sounds, which makes it difficult for the human ear to detect this sound. It is our belief that it would be of great help to the physician to receive computer-based support through an intelligent stethoscope, to determine whether a third heart sound is present or not. A precise, accurate and low-cost instrument of this kind would potentially provide objective means for the detection of early heart failure, and could even be used in primary health care. In the first step, phonocardiograms from ten children, all known to have a third heart sound, were analysed, to provide knowledge about the sound features without interference from pathological sounds. Using this knowledge, a tailored wavelet analysis procedure was developed to identify the third heart sound automatically, a technique that was shown to be superior to Fourier transform techniques. In the second step, the method was applied to phonocardiograms from heart patients known to have heart failure. The features of the third heart sound in children and of that in patients were shown to be similar. This resulted in a method for the automatic detection of third heart sounds. The method was able to detect third heart sounds effectively (90%), with a low false detection rate (3.7%), which supports its clinical use. The detection rate was almost equal in both the children and patient groups. The method is therefore capable of detecting, not only distinct and clearly visible/audible third heart sounds found in children, but also third heart sounds in phonocardiograms from patients suffering from heart failure.

A bioacoustic method for timing of the different phases of the breathing cycle and monitoring of breathing frequency.

It is well known that the flow of air through the trachea during respiration causes vibrations in the tissue near the trachea, which propagate to the surface of the body and can be picked up by a microphone placed on the throat over the trachea. Since the vibrations are a direct result of the airflow, accurate timing of inspiration and expiration is possible. This paper presents a signal analysis solution for automated monitoring of breathing and calculation of the breathing frequency. The signal analysis approach uses tracheal sound variables in the time and frequency domains, as well as the characteristics of the disturbances that can be used to discriminate tracheal sound from noise. One problem associated with the bioacoustic method is its sensitivity for acoustic disturbances, because the microphone tends to pick up all vibrations, independent of their origin. A signal processing method was developed that makes the bioacoustic method clinically useful in a broad variety of situations, for example in intensive care and during certain heart examinations, where information about both the precise timing and the phases of breathing is crucial.

Validation and characterization of the computerized laryngeal analyzer (CLA) technique.

The aim of this study was to investigate the response characteristics of the Computerized Laryngeal Analyzer (CLA) and the validity of the noninvasive CLA method to detect swallowing-induced laryngeal elevation correctly. Two healthy adults and two experimental models were used in the study. The CLA technique identified all swallowing events but was unable to discriminate between swallowing and other movements of the tongue or the neck. The computer program produced a derivated response to a square wave signal. Stepwise bending increments of the sensor displayed a linear amplitude response. The degree of laryngeal elevation could not be estimated with the CLA technique, and it was not possible to draw any reliable conclusions from the recordings as to whether the larynx was moving upward or downward.