Design and Comparative Performance of a Robust Lung Auscultation System for Noisy Clinical Settings.

Chest auscultation is a widely used clinical tool for respiratory disease detection. The stethoscope has undergone a number of transformative enhancements since its invention, including the introduction of electronic systems in the last two decades. Nevertheless, stethoscopes remain riddled with a number of issues that limit their signal quality and diagnostic capability, rendering both traditional and electronic stethoscopes unusable in noisy or non-traditional environments (e.

Electronic Stethoscope Filtering Mimics the Perceived Sound Characteristics of Acoustic Stethoscope.

Electronic stethoscopes offer several advantages over conventional acoustic stethoscopes, including noise reduction, increased amplification, and ability to store and transmit sounds. However, the acoustical characteristics of electronic and acoustic stethoscopes can differ significantly, introducing a barrier for clinicians to transition to electronic stethoscopes. This work proposes a method to process lung sounds recorded by an electronic stethoscope, such that the sounds are perceived to have been captured by an acoustic stethoscope.

Digital auscultation in PERCH: Associations with chest radiography and pneumonia mortality in children.

Background: Whether digitally recorded lung sounds are associated with radiographic pneumonia or clinical outcomes among children in low-income and middle-income countries is unknown. We sought to address these knowledge gaps.

Methods: We enrolled 1 to 59monthold children hospitalized with pneumonia at eight African and Asian Pneumonia Etiology Research for Child Health sites in six countries, recorded digital stethoscope lung sounds, obtained chest radiographs, and collected clinical outcomes.

Listening panel agreement and characteristics of lung sounds digitally recorded from children aged 1-59 months enrolled in the Pneumonia Etiology Research for Child Health (PERCH) case-control study.

Introduction: Paediatric lung sound recordings can be systematically assessed, but methodological feasibility and validity is unknown, especially from developing countries. We examined the performance of acoustically interpreting recorded paediatric lung sounds and compared sound characteristics between cases and controls.

Methods: Pneumonia Etiology Research for Child Health staff in six African and Asian sites recorded lung sounds with a digital stethoscope in cases and controls.

Computerized Lung Sound Screening for Pediatric Auscultation in Noisy Field Environments.

Goal: Chest auscultations offer a non-invasive and low-cost tool for monitoring lung disease. However, they present many shortcomings, including inter-listener variability, subjectivity, and vulnerability to noise and distortions. This work proposes a computer-aided approach to process lung signals acquired in the field under adverse noisy conditions, by improving the signal quality and offering automated identification of abnormal auscultations indicative of respiratory pathologies.

Adaptive Noise Suppression of Pediatric Lung Auscultations With Real Applications to Noisy Clinical Settings in Developing Countries.

Goal: Chest auscultation constitutes a portable low-cost tool widely used for respiratory disease detection. Though it offers a powerful means of pulmonary examination, it remains riddled with a number of issues that limit its diagnostic capability. Particularly, patient agitation (especially in children), background chatter, and other environmental noises often contaminate the auscultation, hence affecting the clarity of the lung sound itself.

Developing a reference of normal lung sounds in healthy Peruvian children.

Purpose: Lung auscultation has long been a standard of care for the diagnosis of respiratory diseases. Recent advances in electronic auscultation and signal processing have yet to find clinical acceptance; however, computerized lung sound analysis may be ideal for pediatric populations in settings, where skilled healthcare providers are commonly unavailable. We described features of normal lung sounds in young children using a novel signal processing approach to lay a foundation for identifying pathologic respiratory sounds.

Characterization of noise contaminations in lung sound recordings.

Lung sound auscultation in non-ideal or busy clinical settings is challenged by contaminations of environmental noise. Digital pulmonary measurements are inevitably degraded, impeding the physician's work or any further processing of the acquired signals. The task is even harder when the patient population includes young children.

A multiresolution analysis for detection of abnormal lung sounds.

Automated analysis and detection of abnormal lung sound patterns has great potential for improving access to standardized diagnosis of pulmonary diseases, especially in low-resource settings. In the current study, we develop signal processing tools for analysis of paediatric auscultations recorded under non-ideal noisy conditions. The proposed model is based on a biomimetic multi-resolution analysis of the spectro-temporal modulation details in lung sounds.

Decision support in heart failure through processing of electro- and echocardiograms.

Objective: Signal and imaging investigations are currently key components in the diagnosis, prognosis and follow up of heart diseases. Nowadays, the need for more efficient, cost-effective and personalised care has led to a renaissance of clinical decision support systems (CDSSs). The purpose of this paper is to present an effective way of achieving a high-level integration of signal and image processing methods in the general process of care, by means of a clinical decision support system, and to discuss the advantages of such an approach.

The morphological classification of heartbeats as dominant and non-dominant in ECG signals.

Surface electrocardiography (ECG) is the art of analyzing the heart's electrical activity by applying electrodes to certain positions on the body and measuring potentials at the body surface resulting from this electrical activity. Usually, significant clinical information can be obtained from analysis of the dominant beat morphology. In this respect, identification of the dominant beats and their averaging can be very helpful, allowing clinicians to carry out the measurement of amplitudes and intervals on a beat much cleaner from noise than a generic beat selected from the entire ECG recording.