ReviewIEEE reviews in biomedical engineering2019
Acoustic Methods for Pulmonary Diagnosis.
Review in IEEE reviews in biomedical engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Cough biomarkers for diagnosis and monitoring of respiratory disease: a systematic review.European respiratory review : an official journal of the European Respiratory Society · 2026Pooled it
- Acoustic Lung Imaging Utilized in Continual Assessment of Patients with Obstructed Airway: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- A wearable eddy current based pulmonary function sensor for continuous non-contact point-of-care monitoring during the COVID-19 pandemic.Scientific reports · 2021Trial
- All-fiber wireless auscultation garment for cardiopulmonary diagnostics.Nature cardiovascular research · 2026Article
- Cough in Interstitial Lung Disease: Current Knowledge and Research Gaps.Pulmonary therapy · 2026Review
- From Fixed-Frequency to Tunable: Advances in Acoustic Sensors for Physiological Acoustic Monitoring.Sensors (Basel, Switzerland) · 2026Review
- Monitoring Respiratory Health in Children With Acute Asthma Using Wearable Electrical Bioimpedance and Breath Sounds: Observational Case-Control Study.JMIR mHealth and uHealth · 2026Observational
- Unobtrusive continuous hemodynamic monitoring method using processed heart sound signals in patients undergoing surgery: a proof of concept study.Biomedical engineering letters · 2025Article
- Non-invasive acoustic classification of adult asthma using an XGBoost model with vocal biomarkers.Scientific reports · 2025Article
- Neural network based AI model for lung health assessment.Scientific reports · 2025Article
- Effect of Chronic Obstructive Pulmonary Disease (COPD) on Biventricular Mechanics in Patients Without Severe Airflow Obstruction.Journal of clinical medicine · 2025Review
- Early Diagnosis of Pneumonia and Chronic Obstructive Pulmonary Disease with a Smart Stethoscope with Cloud Server-Embedded Machine Learning in the Post-COVID-19 Era.Biomedicines · 2025Article
- High-accuracy lung sound classification for healthy versus unhealthy diagnosis using artificial neural network.Frontiers in bioengineering and biotechnology · 2025Article
- Development and validation of a nomogram for predicting lung cancer based on acoustic-clinical features.Frontiers in medicine · 2025Article
- Enabling Continuous Breathing-Phase Contextualization via Wearable-Based Impedance Pneumography and Lung Sounds: A Feasibility Study.IEEE journal of biomedical and health informatics · 2023Article
- A New Shapley-Based Feature Selection Method in a Clinical Decision Support System for the Identification of Lung Diseases.Diagnostics (Basel, Switzerland) · 2023Article
- Deep learning-based lung sound analysis for intelligent stethoscope.Military Medical Research · 2023Review
- Sound-guided assessment and localization of pulmonary air leak.Bioengineering & translational medicine · 2023Article
- Enabling effective breathing sound analysis for automated diagnosis of lung diseases.Smart health (Amsterdam, Netherlands) · 2022Article
- Audio Recording Patient-Nurse Verbal Communications in Home Health Care Settings: Pilot Feasibility and Usability Study.JMIR human factors · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Recent developments in sensor technology and computational analysis methods enable new strategies to measure and interpret lung acoustic signals that originate internally, such as breathing or vocal sounds, or are externally introduced, such as in chest percussion or airway insonification. A better understanding of these sounds has resulted in a new instrumentation that allows for highly accurate as well as portable options for measurement in the hospital, in the clinic, and even at home. This review outlines the instrumentation for acoustic stimulation and measurement of the lungs. We first review the fundamentals of acoustic lung signals and the pathophysiology of the diseases that these signals are used to detect. Then, we focus on different methods of measuring and creating signals that have been used in recent research for pulmonary disease diagnosis. These new methods, combined with signal processing and modeling techniques, lead to a reduction in noise and allow improved feature extraction and signal classification. We conclude by presenting the results of human subject studies taking advantage of both the instrumentation and signal processing tools to accurately diagnose common lung diseases. This paper emphasizes the active areas of research within modern lung acoustics and encourages the standardization of future work in this field.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.