Diagnostic Accuracy of Computerized Bowel Sound Analysis with Non-Invasive Devices for Irritable Bowel Syndrome:A Systematic Review and Meta-Analysis

Objective To assess the diagnostic accuracy of bowel sound analysis for irritable bowel syndrome(IBS)with a systematic review and meta-analysis.Methods We searched MEDLINE,Embase,the Cochrane Library,Web of Science,and IEEE Xplore databases until September 2023.Cross-sectional and case-control studies on diagnostic accuracy of bowel sound analysis for IBS were identified.We estimated the pooled sensitivity,specificity,positive likelihood ratio,negative likeli-hood ratio,and diagnostic odds ratio with a 95% confidence interval(CI),and plotted a summary receiver operat-ing characteristic curve and evaluated the area under the curve.Results Four studies were included.The pooled diagnostic sensitivity,specificity,positive likelihood ratio,nega-tive likelihood ratio,and diagnostic odds ratio were 0.94(95%CI,0.87‒0.97),0.89(95%CI,0.81‒0.94),8.43(95%CI,4.81‒14.78),0.07(95%CI,0.03‒0.15),and 118.86(95%CI,44.18‒319.75),respectively,with an area under the curve of 0.97(95%CI,0.95‒0.98).Conclusions Computerized bowel sound analysis is a promising tool for IBS.However,limited high-quality data make the results'validity and applicability questionable.There is a need for more diagnostic test accuracy studies and better wearable devices for monitoring and analysis of IBS.

Deep learning-based lung sound analysis for intelligent stethoscope

Auscultation is crucial for the diagnosis of respiratory system diseases.However,traditional stethoscopes have inherent limitations,such as inter-listener variability and subjectivity,and they cannot record respiratory sounds for offline/retrospective diagnosis or remote prescriptions in telemedicine.The emergence of digital stethoscopes has overcome these limitations by allowing physicians to store and share respiratory sounds for consultation and education.On this basis,machine learning,particularly deep learning,enables the fully-automatic analysis of lung sounds that may pave the way for intelligent stethoscopes.This review thus aims to provide a comprehensive overview of deep learning algorithms used for lung sound analysis to emphasize the significance of artificial intelligence(AI)in this field.We focus on each component of deep learning-based lung sound analysis systems,including the task categories,public datasets,denoising methods,and,most importantly,existing deep learning methods,i.e.,the state-of-the-art approaches to convert lung sounds into two-dimensional(2D)spectrograms and use convolutional neural networks for the end-to-end recognition of respiratory diseases or abnormal lung sounds.Additionally,this review highlights current challenges in this field,including the variety of devices,noise sensitivity,and poor interpretability of deep models.To address the poor reproducibility and variety of deep learning in this field,this review also provides a scalable and flexible open-source framework that aims to standardize the algorithmic workflow and provide a solid basis for replication and future extension:https://github.com/contactless-healthcare/Deep-Learning-for-Lung-Sound-Analysis.

Spectral analysis of bowel sounds in intestinal obstruction using an electronic stethoscope

AIM: To determine the value of bowel sounds analysis using an electronic stethoscope to support a clinical diagnosis of intestinal obstruction. METHODS: Subjects were patients who presented with a diagnosis of possible intestinal obstruction based on symptoms, signs, and radiological findings. A 3MTH Littmann Model 4100 electronic stethoscope was used in this study. With the patients lying supine, six 8-second recordings of bowel sounds were taken from each patient from the lower abdomen. The recordings were analysed for sound duration, soundto-sound interval, dominant frequency, and peak frequency. Clinical and radiological data were reviewed and the patients were classified as having either acute, subacute, or no bowel obstruction. Comparison of bowel sound characteristics was made between these subgroups of patients. In the presence of an obstruction, the site of obstruction was identified and bowel calibre was also measured to correlate with bowel sounds. RESULTS: A total of 71 patients were studied during the period July 2009 to January 2011. Forty patientshad acute bowel obstruction (27 small bowel obstruction and 13 large bowel obstruction), 11 had subacute bowel obstruction (eight in the small bowel and three in large bowel) and 20 had no bowel obstruction (diagnoses of other conditions were made). Twenty-five patients received surgical intervention (35.2%) during the same admission for acute abdominal conditions. A total of 426 recordings were made and 420 recordings were used for analysis. There was no significant difference in sound-to-sound interval, dominant frequency, and peak frequency among patients with acute bowel obstruction, subacute bowel obstruction, and no bowel obstruction. In acute large bowel obstruction, the sound duration was significantly longer (median 0.81 s vs 0.55 s, P = 0.021) and the dominant frequency was significantly higher (median 440 Hz vs 288 Hz, P = 0.003) when compared to acute small bowel obstruction. No significant difference was seen between acute large bowel obstruction and large bowel pseudoobstruction. For patients with small bowel obstruction, the sound-to-sound interval was significantly longer in those who subsequently underwent surgery compared with those treated non-operatively (median 1.29 s vs 0.63 s, P < 0.001). There was no correlation between bowel calibre and bowel sound characteristics in both acute small bowel obstruction and acute large bowel obstruction. CONCLUSION: Auscultation of bowel sounds is nonspecific for diagnosing bowel obstruction. Differences in sound characteristics between large bowel and small bowel obstruction may help determine the likely site of obstruction.

Characteristics analyzing and parametric modeling of the arc sound in CO_2 GMAW for on-line quality monitoring

For on-line monitoring of welding quality, the characteristics of the arc sound signals in short circuit CO2 GMAW were analyzed in the time and frequency domains. The arc sound presents a series of ringing-like oscillations that occur at the end of short circuit i. e. the moment of arc re-ignition, and distributes mainly in the frequency band below 10 kHz. A concept of the arc tone channel and its equivalent electrical model were suggested, which is considered a time-dependent distributed parametric system of which the transmission properties depend upon the geometric and physical characteristics of the arc and surroundings, and is excited by the sound source results from the change of arc energy so that results in arc sound. The linear prediction coding （ LPC ） model is an estimation of the tone channel. The radial basis function （ RBF ） neural networks were built for on-line pattern recognition of the gas-lack in welding, in which the input vectors were formed with the LPC coefficients. The test results proved that the LPC model of arc sound and the RBF networks are feasible in on-line quality monitoring.

Time-shared channel identification for adaptive noise cancellation in breath sound extraction

Noise artifacts are one of the key obstacles in applying continuous monitoring and computer-assisted analysis of lung sounds. Traditional adaptive noise cancellation (ANC) methodologies work reasonably well when signal and noise are stationary and independent. Clinical lung sound auscultation encounters an acoustic environment in which breath sounds are not stationary and often correlate with noise. Consequendy, capability of ANC becomes significantly compromised. This paper introduces a new methodology for extracting authentic lung sounds from noise-corrupted measurements. Unlike traditional noise cancellation methods that rely on either frequency band separation or signal/noise independence to achieve noise reduction, this methodology combines the traditional noise canceling methods with the unique feature of time-split stages in breathing sounds. By employing a multi-sensor system, the method first employs a high-pass filter to eliminate the off-band noise, and then performs time-shared blind identification and noise cancellation with recursion from breathing cycle to cycle. Since no frequency separation or signal/noise independence is required, this method potentially has a robust and reliable capability of noise reduction, complementing the traditional methods.

Error analysis and calibration for underwater sound intensity measuring system

Based on measuring the cross-spectrum density of sound pressure between two hydrophones, the facility for underwater sound intensity measurement is investigated and designed. According to the principle of two-hydrophone method for intensity measurement, the error analysis is carried out. Given the method of sound intensity measurement calibration for this underwater sound intensity measurement facility, the uncertainty of intensity measurement by this facility is evaluated. It is shown that the analysis and evaluation are agreeable to the experimental results.

Theoretical analysis for sound wave scattering by parallel cylindrical tubes in boilers

Although the sonic soot cleaning techniques have been applied in boilers in power plants, petrochemical works and general industries world wide, most of the correlated basic problems have not been well solved yet. By using Helmholtz integral equation, sound wave scattered by heat-exchanger tubes is numerically calculated. Sound field distribution characteristics on the tube surfaces and around the tube group is obtained. The results can be applied to the development of sonic soot cleaning techniques in boilers.

Modeling and acoustic analysis of irregular sound enclosure by using Chebyshev-variational method

A modeling method for irregular sound enclosures was proposed based on the Chebyshev-variational theory. A rectangular space was first assumed to bound the irregular sound space and the sound pressure in the rectangular space expressed as a triple-Chebyshev series. Next, a coordinate transformation was performed and the Lagrangian functional of the irregular sound space obtained. Finally, the Lagrangian functional was solved under the Ritz method framework, and the enclosure＇s acoustic characteristic equation deduced and the eigenpairs obtained. The accuracy of the present method was validated according to agreement between the present results and finite element results for an enclosure with a curved surface.Furthermore, the acoustic characteristics of a trapezoidal enclosure and an enclosure with an inner groove were investigated. The results showed that the mode shapes of the trapezoidal sound space changed with increased inclination angle and the natural frequencies, except the first order, of the sound space with a rectangular inner groove decreased with increased groove depth.

Time-domain analysis for vibration and sound radiation of submerged spherical shell excited by force

The vibration and sound radiation of a submerged spherical shell are studied in the time-domain by Laplace transform method, where a CW pulse force acts at the apex of the shell. The numerical results for the case of long pulse show that the different vibrational modes and the resonant or beat radiated sound are excited for different carrier-frequencies, but litle sound is radiated for some vibrational modes. For the case of short pulse the waveforms of the pulse become widened and deformed, when the pulse propagates between apexes of the shell. Then, the Doubly Asymptotic Approximations (DAA2) and Kirchhoff's Retarded Potential Formulate (KRPF)are used to solve the same problem. It is shown that the results of DAA2 and KRPF method have a good agreement with the results of Laplace transform method.

The analysis of heart sounds by using bispectral technique

An advanced signal processing technique, higher-order spectra, is proposed to in vestigate the nonlinear coupling phenomena of the heart sounds. To extract more higher-order information of the heart sounds, a non-Gaussian AR model is selected for parametric bispectral estimation in analyzing several kinds of heart sounds. The non-Gaussian AR model of the sound signals is llsed to detect quadratic nonlinear interactions and to classify two patterns of heart sounds in terms of the parametric bispectral estimate. The bispectral cross-correlation is employed to the order determination of the model. Several real heart sound data are imple mented to show that the quadratic nonlinearity exist in both normal and clinical heart sounds.It was found that bispectral techniques are effective and useful tools in analyzing heart sounds and other acoustical signals

Numerical analysis of 3-D sound propagation in lined ducts with circumferential mode sound sources at inlet

Numerical analysis of three-dimensional sound propagation in soft-soft or soft-hard circular ducts with circumferential and axial modes of sound sources at the inlet has been carried out. In this paper , the numerical method and the samples are offered and the effects of circumferential and axial modes on numerical results are discussed in detail .

Experimental analysis of considering the sound pressure distribution pattern at the ear canal entrance as an unrevealed head-related localization clue

By analyzing the differences between binaural recording and real listening, it was deduced that there were some unrevealed auditory localization clues, and the sound pressure distribution pattern at the entrance of ear canal was probably a clue. It was proved through the listening test that the unrevealed auditory localization clues really exist with the reduction to absurdity. And the effective frequency bands of the unrevealed localization clues were in- duced and summed. The result of finite element based simulations showed that the pressure distribution at the entrance of ear canal was non-uniform, and the pattern was related to the direction of sound source. And it was proved that the sound pressure distribution pattern at the entrance of the ear canal carried the sound source direction information and could be used as an unrevealed localization clue. The frequency bands in which the sound pressure distribution patterns had significant differences between front and back sound source directions were roughly matched with the effective frequency bands of unrevealed localization clues obtained from the listening tests. To some extent, it supports the pattern could be a kind of unrevealed auditory hypothesis that the sound pressure distribution localization clues.

Near field acoustic solution of a rotating point source in frequency domain

On the basis of the frequency domain acoustic solation of sources in arbitrary motion, in this paper an approximate acoustic solution of a rotating point source in near field is given, which is the superposition of the well-Known far field solution and three near field modification items on the condition that the rotating radius is acoustically compact compared with the field sound wavelength. Accordingly the near field Green function in free space is obtained. The characteristic directionality of the sound field induced by source rotating is discussed, and the influences of source position, source frequency and rotating frequency are studied in detail.