Pneumothorax detection using computerised analysis of breath sounds

Diagnosis of COVID-19 via acoustic analysis and artificial intelligence by monitoring breath sounds on smartphones

Scientific evidence shows that acoustic analysis could be an indicator for diagnosing COVID-19. From analyzing recorded breath sounds on smartphones, it is discovered that patients with COVID-19 have different patterns in both the time domain and frequency domain. These patterns are used in this paper to diagnose the infection of COVID-19. Statistics of the sound signals, analysis in the frequency domain, and Mel-Frequency Cepstral Coefficients (MFCCs) are then calculated and applied in two classifiers, k-Nearest Neighbors (kNN) and Convolutional Neural Network (CNN), to diagnose whether a user is contracted with COVID-19 or not. Test results show that, amazingly, an accuracy of over 97% could be achieved with a CNN classifier and more than 85% on kNN with optimized features. Optimization methods for selecting the best features and using various metrics to evaluate the performance are also demonstrated in this paper. Owing to the high accuracy of the CNN model, the CNN model was implemented in an Android app to diagnose COVID-19 with a probability to indicate the confidence level. The initial medical test shows a similar test result between the method proposed in this paper and the lateral flow method, which indicates that the proposed method is feasible and effective. Because of the use of breath sound and tested on the smartphone, this method could be used by everybody regardless of the availability of other medical resources, which could be a powerful tool for society to diagnose COVID-19.

Hemopneumothorax detection through the process of artificial evolution - a feasibility study

BACKGROUND

Tension pneumothorax is one of the leading causes of preventable death on the battlefield. Current prehospital diagnosis relies on a subjective clinical impression complemented by a manual thoracic and respiratory examination. These techniques are not fully applicable in field conditions and on the battlefield, where situational and environmental factors may impair clinical capabilities. We aimed to assemble a device able to sample, analyze, and classify the unique acoustic signatures of pneumothorax and hemothorax.

METHODS

Acoustic data was obtained with simultaneous use of two sensitive digital stethoscopes from the chest wall of an ex-vivo porcine model. Twelve second samples of acoustic data were obtained from the in-house assembled digital stethoscope system during mechanical ventilation. The thoracic cavity was injected with increasing volumes of 200, 400, 600, 800, and 1000 ml of air or saline to simulate pneumothorax and hemothorax, respectively. The data was analyzed using a multi-objective genetic algorithm that was used to develop an optimal mathematical detector through the process of artificial evolution, a cutting-edge approach in the artificial intelligence discipline.

RESULTS

The in-house assembled dual digital stethoscope system and developed genetic algorithm achieved an accuracy, sensitivity and specificity ranging from 64 to 100%, 63 to 100%, and 63 to 100%, respectively, in classifying acoustic signal as associated with pneumothorax or hemothorax at fluid injection levels of 400 ml or more, and regardless of background noise.

CONCLUSIONS

We present a novel, objective device for rapid diagnosis of potentially lethal thoracic injuries. With further optimization, such a device could provide real-time detection and monitoring of pneumothorax and hemothorax in battlefield conditions.

Sound transmission in human thorax through airway insonification: an experimental and computational study with diagnostic applications

Pulmonary diseases and injury lead to structural and functional changes in the lung parenchyma and airways, often resulting in measurable sound transmission changes on the chest wall surface. Additionally, noninvasive imaging of externally driven mechanical wave motion in the chest (e.g., using magnetic resonance elastography) can provide information about lung stiffness and other structural property changes which may be of diagnostic value. In the present study, a comprehensive computational simulation (in silico) model was developed to simulate sound wave propagation in the airways, parenchyma, and chest wall under normal and pathological conditions that create distributed structural (e.g., pneumothoraces) and diffuse material (e.g., fibrosis) changes, as well as a localized structural and material changes as may be seen with a neoplasm. Experiments were carried out in normal subjects to validate the baseline model. Sound waves with frequency content from 50 to 600 Hz were introduced into the airways of three healthy human subjects through the mouth, and transthoracic transmitted waves were measured by scanning laser Doppler vibrometry at the chest wall surface. The computational model predictions of a frequency-dependent decreased sound transmission due to pneumothorax were consistent with experimental measurements reported in previous work. Predictions for the case of fibrosis show that while shear wave motion is altered, changes to compression wave propagation are negligible, and thus, insonification, which primarily drives compression waves, is not ideal to detect the presence of fibrosis. Results from the numerical simulation of a tumor show an increase in the wavelength of propagating waves in the immediate vicinity of the tumor region. Graphical abstract.

Time-Frequency Distribution of Seismocardiographic Signals: A Comparative Study

Accurate estimation of seismocardiographic (SCG) signal features can help successful signal characterization and classification in health and disease. This may lead to new methods for diagnosing and monitoring heart function. Time-frequency distributions (TFD) were often used to estimate the spectrotemporal signal features. In this study, the performance of different TFDs (e.g., short-time Fourier transform (STFT), polynomial chirplet transform (PCT), and continuous wavelet transform (CWT) with different mother functions) was assessed using simulated signals, and then utilized to analyze actual SCGs. The instantaneous frequency (IF) was determined from TFD and the error in estimating IF was calculated for simulated signals. Results suggested that the lowest IF error depended on the TFD and the test signal. STFT had lower error than CWT methods for most test signals. For a simulated SCG, Morlet CWT more accurately estimated IF than other CWTs, but Morlet did not provide noticeable advantages over STFT or PCT. PCT had the most consistently accurate IF estimations and appeared more suited for estimating IF of actual SCG signals. PCT analysis showed that actual SCGs from eight healthy subjects had multiple spectral peaks at 9.20 ± 0.48, 25.84 ± 0.77, 50.71 ± 1.83 Hz (mean ± SEM). These may prove useful features for SCG characterization and classification.

Geometric features of pig airways using computed tomography

Accurate knowledge of the airway geometry is needed when constructing physical models of the airway tree and for numerical modeling of flow or sound propagation in the airways. Human and animal experiments are conducted to validate these models. Many studies documented the geometric details of the human airways. However, information about the geometry of pig airways is scarcer. Earlier studies suggested that the morphology of animal airways can be significantly different from that of humans. The objective of this study is to measure the airway diameter, length and bifurcation angles in domestic pigs using computed tomography. In this study, lungs of six pigs were imaged, then segmentation software tools were used to extract the geometry of the airway lumen. The airway dimensions were measured from the resulting 3‐D models for the first 24 airway generations. Results showed that the size and morphology of the airways of the six pigs were similar. The trachea diameters were found to be comparable to the typical human adult, but the diameter, length and branching angles of other airways were noticeably different from that of humans. For example, pig airways consistently had an early branching from the trachea that feeds the top right lung lobe and precedes the main carina. This branch is absent in the human airways. The results suggested that the pig airways geometry may not be accurately approximated by human airways and this approximation may contribute to increasing the errors in computational models of the pig chest.

Generation of Pig Airways using Rules Developed from the Measurements of Physical Airways

BACKGROUND

A method for generating bronchial tree would be helpful when constructing models of the tree for benchtop experiments as well as for numerical modeling of flow or sound propagation in the airways. Early studies documented the geometric details of the human airways that were used to develop methods for generating human airway tree. However, methods for generating animal airway tree are scarcer. Earlier studies suggested that the morphology of animal airways can be significantly different from that of humans. Hence, using algorithms for the human airways may not be accurate in generating models of animal airway geometry.

OBJECTIVE

The objective of this study is to develop an algorithm for generating pig airway tree based on the geometric details extracted from the physical measurements.

METHODS

In the current study, measured values of branch diameters, lengths and bifurcation angles and rotation of bifurcating planes were used to develop an algorithm that is capable of generating a realistic pig airway tree.

RESULTS

The generation relations between parent and daughter branches were found to follow certain trends. The diameters and the length of different branches were dependent on airway generations while the bifurcation angles were primarily dependent on bifurcation plane rotations. These relations were sufficient to develop rules for generating a model of the pig large airways.

CONCLUSION

The results suggested that the airway tree generated from the algorithm can provide an approximate geometric model of pig airways for computational and benchtop studies.

Pneumothorax effects on pulmonary acoustic transmission

Pneumothorax (PTX) is an abnormal accumulation of air between the lung and the chest wall. It is a relatively common and potentially life-threatening condition encountered in patients who are critically ill or have experienced trauma. Auscultatory signs of PTX include decreased breath sounds during the physical examination. The objective of this exploratory study was to investigate the changes in sound transmission in the thorax due to PTX in humans. Nineteen human subjects who underwent video-assisted thoracic surgery, during which lung collapse is a normal part of the surgery, participated in the study. After subjects were intubated and mechanically ventilated, sounds were introduced into their airways via an endotracheal tube. Sounds were then measured over the chest surface before and after lung collapse. PTX caused small changes in acoustic transmission for frequencies below 400 Hz. A larger decrease in sound transmission was observed from 400 to 600 Hz, possibly due to the stronger acoustic transmission blocking of the pleural air. At frequencies above 1 kHz, the sound waves became weaker and so did their changes with PTX. The study elucidated some of the possible mechanisms of sound propagation changes with PTX. Sound transmission measurement was able to distinguish between baseline and PTX states in this small patient group. Future studies are needed to evaluate this technique in a wider population.

Experimental and Computational Studies of Sound Transmission in a Branching Airway Network Embedded in a Compliant Viscoelastic Medium

Breath sounds are often used to aid in the diagnosis of pulmonary disease. Mechanical and numerical models could be used to enhance our understanding of relevant sound transmission phenomena. Sound transmission in an airway mimicking phantom was investigated using a mechanical model with a branching airway network embedded in a compliant viscoelastic medium. The Horsfield self-consistent model for the bronchial tree was adopted to topologically couple the individual airway segments into the branching airway network. The acoustics of the bifurcating airway segments were measured by microphones and calculated analytically. Airway phantom surface motion was measured using scanning laser Doppler vibrometry. Finite element simulations of sound transmission in the airway phantom were performed. Good agreement was achieved between experiments and simulations. The validated computational approach can provide insight into sound transmission simulations in real lungs.

A comprehensive computational model of sound transmission through the porcine lung

A comprehensive computational simulation model of sound transmission through the porcine lung is introduced and experimentally evaluated. This "subject-specific" model utilizes parenchymal and major airway geometry derived from x-ray CT images. The lung parenchyma is modeled as a poroviscoelastic material using Biot theory. A finite element (FE) mesh of the lung that includes airway detail is created and used in comsol FE software to simulate the vibroacoustic response of the lung to sound input at the trachea. The FE simulation model is validated by comparing simulation results to experimental measurements using scanning laser Doppler vibrometry on the surface of an excised, preserved lung. The FE model can also be used to calculate and visualize vibroacoustic pressure and motion inside the lung and its airways caused by the acoustic input. The effect of diffuse lung fibrosis and of a local tumor on the lung acoustic response is simulated and visualized using the FE model. In the future, this type of visualization can be compared and matched with experimentally obtained elastographic images to better quantify regional lung material properties to noninvasively diagnose and stage disease and response to treatment.

Sound transmission in the chest under surface excitation: an experimental and computational study with diagnostic applications

Chest physical examination often includes performing chest percussion, which involves introducing sound stimulus to the chest wall and detecting an audible change. This approach relies on observations that underlying acoustic transmission, coupling, and resonance patterns can be altered by chest structure changes due to pathologies. More accurate detection and quantification of these acoustic alterations may provide further useful diagnostic information. To elucidate the physical processes involved, a realistic computer model of sound transmission in the chest is helpful. In the present study, a computational model was developed and validated by comparing its predictions with results from animal and human experiments which involved applying acoustic excitation to the anterior chest, while detecting skin vibrations at the posterior chest. To investigate the effect of pathology on sound transmission, the computational model was used to simulate the effects of pneumothorax on sounds introduced at the anterior chest and detected at the posterior. Model predictions and experimental results showed similar trends. The model also predicted wave patterns inside the chest, which may be used to assess results of elastography measurements. Future animal and human tests may expand the predictive power of the model to include acoustic behavior for a wider range of pulmonary conditions.

Highly sensitive monitoring of chest wall dynamics and acoustics provides diverse valuable information for evaluating ventilation and diagnosing pneumothorax

Current practice of monitoring lung ventilation in neonatal intensive care units, utilizing endotracheal tube pressure and flow, end-tidal CO2, arterial O2 saturation from pulse oximetry, and hemodynamic indexes, fails to account for asymmetric pathologies and to allow for early detection of deteriorating ventilation. This study investigated the utility of bilateral measurements of chest wall dynamics and sounds, in providing early detection of changes in the mechanics and distribution of lung ventilation. Nine healthy New Zealand rabbits were ventilated at a constant pressure, while miniature accelerometers were attached to each side of the chest. Slowly progressing pneumothorax was induced by injecting 1 ml/min air into the pleural space on either side of the chest. The end of the experiment ( tPTX) was defined when arterial O2 saturation from pulse oximetry dropped <90% or when vigorous spontaneous breathing began, since it represents the time of clinical detection using common methods. Consistent and significant changes were observed in 15 of the chest dynamics parameters. The most meaningful temporal changes were noted for features extracted from subsonic dynamics (<10 Hz), e.g., tidal amplitude, energy, and autoregressive poles. Features from the high-frequency band (10–200 Hz), e.g., energy and entropy, exhibited smaller but significant changes. At 70% tPTX, identification of asymmetric ventilation was attained for all animals. Side identification of the pneumothorax was achieved at 50% tPTX, within a 95% confidence interval. Diagnosis was, on average, 34.1 ± 18.8 min before tPTX. In conclusion, bilateral monitoring of the chest dynamics and acoustics provide novel information that is sensitive to asymmetric changes in ventilation, enabling early detection and localization of pneumothorax.

Advantages and limitations of using matrix pencil method for the modal analysis of medical percussion signals

Although clinical percussion remains one of the most widespread traditional noninvasive methods for diagnosing pulmonary disease, the available analysis of physical characteristics of the percussion sound using modern signal processing techniques is still quite limited. The majority of existing literature on the subject reports either time-domain or spectral analysis methods. However, Fourier analysis, which represents the signal as a sum of infinite periodic harmonics, is not naturally suited for decomposition of short and aperiodic percussion signals. Broadening of the spectral peaks due to damping leads to their overlapping and masking of the lower amplitude peaks, which could be important for the fine-level signal classification. In this study, an attempt is made to automatically decompose percussion signals into a sum of exponentially damped harmonics, which in this case form a more natural basis than Fourier harmonics and thus allow for a more robust representation of the signal in the parametric space. The damped harmonic decomposition of percussion signals recorded on healthy volunteers in clinical setting is performed using the matrix pencil method, which proves to be quite robust in the presence of noise and well suited for the task.

Transient decrease in PaCO(2) and asymmetric chest wall dynamics in early progressing pneumothorax

PURPOSE

Diagnosis of pneumothorax (PTX) in newborn infants has been reported as late. To explore diagnostic indices for early detection of progressing PTX, and offer explanations for delayed diagnoses.

METHODS

Progressing PTX was created in rabbits (2.3 ± 0.5 kg, n = 7) by injecting 1 ml/min of air into the pleural space. Hemodynamic parameters, tidal volume, EtCO(2), SpO(2), blood gas analyses and chest wall tidal displacements (TDi) on both sides of the chest were recorded.

RESULTS

(Mean ± SD): A decrease in SpO(2) below 90 % was detected only after 46.6 ± 11.3 min in six experiments. In contrary to the expected gradual increase of CO(2), there was a prolonged transient decrease of 14.2 ± 4.5 % in EtCO(2) (p < 0.01), and a similar decrease in PaCO(2) (p < 0.025). EtCO(2) returned back to baseline only after 55.2 ± 24.7 min, and continued to rise thereafter. The decrease in CO(2) was a mirror image of the 14.6 ± 5.3 % increase in tidal volume. The analysis of endotracheal flow and pressure dynamics revealed a paradoxical transient increase in the apparent compliance. Significant decrease in mean arterial blood pressure was observed after 46.2 ± 40.1 min. TDi provided the most sensitive and earliest sign of PTX, decreasing on the PTX side after 16.1 ± 7.2 min. The TDi progressively decreased faster and lower on the PTX side, thus enabling detection of asymmetric ventilation.

CONCLUSIONS

The counterintuitive transient prolonged decrease in CO(2) without changes in SpO(2) may explain the delay in diagnosis of PTX encountered in the clinical environment. An earlier indication of asymmetrically decreased ventilation on the affected side was achieved by monitoring the TDi.

A physical approach to the automated classification of clinical percussion sounds

Chest percussion is a traditional technique used for the physical examination of pulmonary injuries and diseases. It is a method of tapping body parts with fingers or small instruments to evaluate the size, consistency, borders, and presence of fluid/air in the lungs and abdomen. Percussion has been successfully used for the diagnosis of such potentially lethal conditions as traumatic and tension pneumothorax. This technique, however, has certain shortcomings, including limitations of the human ear and the subjectivity of the administrator, that lead to overall low sensitivity. Automation of the method by using a standardized percussion source and computerized classification of digitized signals would remove the subjective factor and other limitations of the technique. It would also enable rapid on-site diagnostics of pulmonary traumas when thorough clinical examination is impossible. This paper lays the groundwork for an objective signal classification approach based on a general physical model of a damped harmonic oscillator. Using this concept, critical parameters that effectively subdivide percussion signals into three main groups, historically known as "tympanic," "resonant," and "dull," are identified, opening the possibility for automated diagnostics of air/liquid inclusions in the thorax and abdomen. The key role of damping in forming the character of the percussion signal is investigated using a 3D thorax phantom. The contribution of the abdominal component into the complex multimode spectrum of chest percussion signals is demonstrated.

Identification of pneumothorax in very preterm infants

OBJECTIVE

To compare respiratory and other morbidities between very preterm infants with and without a pneumothorax and to determine whether infants at higher risk of pneumothorax can be identified early in their course.

STUDY DESIGN

Preterm infants at 23 to 28 weeks' gestation with pneumothorax were compared with matched control subjects. Demographic and clinical data from birth through the first 72 hours were compared.

RESULTS

Sixty-two (9.2%) of 675 infants had pneumothorax. There were no significant differences in the baseline maternal and infant characteristics. Mortality was significantly higher in the pneumothorax group (43%) versus control subjects (13%). There was no significant difference in continuous positive airway pressure or surfactant treatment or rates of intraventricular hemorrhage or bronchopulmonary dysplasia. Infants treated with early continuous positive airway pressure in the delivery room typically had pneumothorax on day 2 of life. Those who had pneumothorax had higher inspired fraction of oxygen before its diagnosis and over the first 12 hours of life than did control subjects.

CONCLUSIONS

Pneumothorax is associated with increased mortality and with severity of lung disease in the first day of life. It may be possible to identify babies at highest risk of pneumothorax on the basis of inspired fraction of oxygen in the first 12 hours of life.

A numerical model to study auscultation sounds under pneumothorax conditions

A 2D viscoelastic finite-difference time-domain (FDTD) is used to simulate sound propagation of lung sounds in the human thorax. Specifically, the model is employed to study the effects of pneumothorax on the sounds reaching the thoracic surface. By simulating varying degrees of severity of the disease, the model assists in determining the key frequency bands that contain the most information to aid in diagnosis. The work thus lends itself for development of advanced auscultatory techniques for detection of pneumothorax using noninvasive acoustic sensors.

Experimental and Computational Models for Simulating Sound Propagation Within the Lungs

An acoustic boundary element model is used to simulate sound propagation in the lung parenchyma and surrounding chest wall. It is validated theoretically and numerically and then compared with experimental studies on lung-chest phantom models that simulate the lung pathology of pneumothorax. Studies quantify the effect of the simulated lung pathology on the resulting acoustic field measured at the phantom chest surface. This work is relevant to the development of advanced auscultatory techniques for lung, vascular, and cardiac sounds within the torso that utilize multiple noninvasive sensors to create acoustic images of the sound generation and transmission to identify certain pathologies.

Boundary element model for simulating sound propagation and source localization within the lungs

An acoustic boundary element (BE) model is used to simulate sound propagation in the lung parenchyma. It is computationally validated and then compared with experimental studies on lung phantom models. Parametric studies quantify the effect of different model parameters on the resulting acoustic field within the lung phantoms. The BE model is then coupled with a source localization algorithm to predict the position of an acoustic source within the phantom. Experimental studies validate the BE-based source localization algorithm and show that the same algorithm does not perform as well if the BE simulation is replaced with a free field assumption that neglects reflections and standing wave patterns created within the finite-size lung phantom. The BE model and source localization procedure are then applied to actual lung geometry taken from the National Library of Medicine's Visible Human Project. These numerical studies are in agreement with the studies on simpler geometry in that use of a BE model in place of the free field assumption alters the predicted acoustic field and source localization results. This work is relevant to the development of advanced auscultatory techniques that utilize multiple noninvasive sensors to construct acoustic images of sound generation and transmission to identify pathologies.

Identification of endotracheal tube malpositions using computerized analysis of breath sounds via electronic stethoscopes

Endotracheal tube (ETT) malpositioning into a mainstem bronchus or the esophagus may result in significant hypoxemia. Current methods to determine correct ETT position include auscultation, radiography, and bronchoscopy, although the current acceptable standard procedure for proper endotracheal (versus esophageal) intubation is detection of end-tidal carbon dioxide (ETco(2)) by capnography, capnometry, or colorimetric ETco(2) devices. Unfortunately, capnography may be unavailable or unreliable in nonhospital/emergency settings or in low cardiac output states, and it does not detect endobronchial intubation. The purpose of this study was to quantify and assess breath sound characteristics using electronic stethoscopes placed over each hemithorax and epigastrium to determine their ability to detect ETT malposition. We recorded breath sounds in 19 healthy, non-obese adults before general surgical procedures. After intubation of the trachea, the ETT was bronchoscopically positioned 3 cm above the carina, after which 3 breaths of 500 mL were given and breath sounds were recorded. A second ETT was placed in the esophagus and the same series of breaths and recordings were performed. Finally, the tracheal ETT was advanced into the right mainstem bronchus and breath sounds were recorded. Using computerized analysis, breath sounds were digitized and filtered to remove selected frequencies, and acoustic signals and energy ratios were obtained for all 3 positions. Total energy ratios using band-pass filtering of the acoustic signals accurately identified all esophageal and endobronchial intubation (P < 0.001). These preliminary results suggest that this technique, when incorporated into a 3-component, electronic stethoscope-type device, may be an accurate, portable mechanism to reliably detect ETT malposition in adults when ETco(2) may be unavailable or unreliable.

Breath sound changes associated with malpositioned endotracheal tubes

Endotracheal tubes (ETTs) are used to establish airway access in patients with ventilatory failure and during general anaesthesia. Tube malpositioning can compromise respiratory function and can be associated with increased morbidity and mortality. Clinical assessment of ETT position normally involves chest auscultation, which is highly skill-dependent and can be misleading. The objective of this pilot study was to investigate breath sound changes associated with ETT malpositioning. Breath sounds were acquired in six human subjects over each hemithorax and over the epigastrium for tracheal, bronchial and oesophageal intubations. When the ETT was in the oesophagus, the acoustic energy ratio between epigastrium and chest surface increased in all subjects (p < 0.04). In addition, ETT placement in the right mainstem bronchus decreased the acoustic energy ratio between the left and right hemithoraxes in all subjects (p < 0.04). A baseline measurement of this energy ratio was needed for bronchial intubation identification. However, using this ratio after bandpass filtering (200-500 Hz) did not require a baseline value, which would increase the utility of this method for initial ETT placement. These results suggest that computerised analysis of breath sounds may be useful for assessment of ETT positioning. More studies are needed to test the feasibility of this approach further.

Computerised analysis of auscultatory sounds associated with vascular patency of haemodialysis access

Vascular access for renal dialysis is a lifeline for about 120 000 individuals in the United States. Stethoscope auscultation of vascular sounds has some utility in the assessment of access patency, yet can be highly skill-dependent. The objective of the study was to identify acoustic parameters that are related to changes in vascular access patency. The underlying hypothesis is that stenoses of haemodialysis access vessels or grafts cause vascular sound changes that are detectable using computerised data acquisition and analysis. Eleven patients participated in the study. Their vascular sounds were recorded before and after angiography, which was accompanied by angioplasty in most patients. The sounds were acquired using two electronic stethoscopes and then digitised and analysed on a personal computer. Vessel stenosis changes were found to be associated with changes in acoustic amplitude and/or spectral energy distribution. Certain acoustic parameters correlated well (correlation coefficient = 0.98, p < 0.0001) with the change in the degree of stenosis, suggesting that stenosis severity may be predictable from these parameters. Parameters also appeared to be sensitive to modest diameter changes (> 20%), (p < 0.005, Wilcoxon rank sum test). These results suggest that computerised analysis of vascular sounds may be useful in vessel patency surveillance. Further testing using longitudinal studies may be warranted.

Surface response of a viscoelastic medium to subsurface acoustic sources with application to medical diagnosis

The response at the surface of an isotropic viscoelastic medium to buried fundamental acoustic sources is studied theoretically, computationally and experimentally. Finite and infinitesimal monopole and dipole sources within the low audible frequency range (40-400 Hz) are considered. Analytical and numerical integral solutions that account for compression, shear and surface wave response to the buried sources are formulated and compared with numerical finite element simulations and experimental studies on finite dimension phantom models. It is found that at low audible frequencies, compression and shear wave propagation from point sources can both be significant, with shear wave effects becoming less significant as frequency increases. Additionally, it is shown that simple closed-form analytical approximations based on an infinite medium model agree well with numerically obtained "exact" half-space solutions for the frequency range and material of interest in this study. The focus here is on developing a better understanding of how biological soft tissue affects the transmission of vibro-acoustic energy from biological acoustic sources below the skin surface, whose typical spectral content is in the low audible frequency range. Examples include sound radiated from pulmonary, gastro-intestinal and cardiovascular system functions, such as breath sounds, bowel sounds and vascular bruits, respectively.