ArticleMedical & biological engineering & computing2018
Apnea and heart rate detection from tracheal body sounds for the diagnosis of sleep-related breathing disorders.
Article in Medical & biological engineering & computing, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 32 citations in OpenAlex.
- Estimation of anaerobic threshold and peak oxygen uptake from tracheal sound during cycle ergometer cardiopulmonary exercise test.Biomedical engineering online · 2026Article
- Integrating physiological signals for enhanced sleep apnea diagnosis with SleepNet.Scientific reports · 2025Article
- Fused Audio Instance and Representation for Respiratory Disease Detection.Sensors (Basel, Switzerland) · 2024Article
- Automatic Heart Rate Detection during Sleep Using Tracheal Audio Recordings from Wireless Acoustic Sensor.Diagnostics (Basel, Switzerland) · 2023Article
- A Comprehensive Review: Computational Models for Obstructive Sleep Apnea Detection in Biomedical Applications.BioMed research international · 2022Review
- Respiratory Monitoring Based on Tracheal Sounds: Continuous Time-Frequency Processing of the Phonospirogram Combined with Phonocardiogram-Derived Respiration.Sensors (Basel, Switzerland) · 2020Article
- Acoustic characterization of upper airway variations from wakefulness to sleep with respect to obstructive sleep apnea.Medical & biological engineering & computing · 2020Article
- Breathing, voice, and synchronized movement.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Sleep/Wakefulness Detection Using Tracheal Sounds and Movements.Nature and science of sleep · 2020Article
- Adaptive Filtering Improved Apnea Detection Performance Using Tracheal Sounds in Noisy Environment: A Simulation Study.BioMed research international · 2020Article
- Automated sleep stage classification based on tracheal body sound and actigraphy.German medical science : GMS e-journal · 2019Article
- Vision-Based Heart and Respiratory Rate Monitoring During Sleep - A Validation Study for the Population at Risk of Sleep Apnea.IEEE journal of translational engineering in health and medicine · 2019Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
Sleep apnea is one of the most common sleep disorders. Here, patients suffer from multiple breathing pauses longer than 10 s during the night which are referred to as apneas. The standard method for the diagnosis of sleep apnea is the attended cardiorespiratory polysomnography (PSG). However, this method is expensive and the extensive recording equipment can have a significant impact on sleep quality falsifying the results. To overcome these problems, a comfortable and novel system for sleep monitoring based on the recording of tracheal sounds and movement data is developed. For apnea detection, a unique signal processing method utilizing both signals is introduced. Additionally, an algorithm for extracting the heart rate from body sounds is developed. For validation, ten subjects underwent a full-night PSG testing, using the developed sleep monitor in concurrence. Considering polysomnography as gold standard the developed instrumentation reached a sensitivity of 92.8% and a specificity of 99.7% for apnea detection. Heart rate measured with the proposed method was strongly correlated with heart rate derived from conventional ECG (r
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