Effects of breathing pathways on tracheal sound spectral features

Kraman, Steve S.; Pasterkamp, Hans; Kompis, Martin; Takase, Masato; Wodicka, George R.

doi:10.1016/s0034-5687(97)00113-8

Cited by 31 publications

(17 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Because most of the power in the tracheal sound signal is below 800 Hz (11), we chose 1,000 Hz as the low-pass cutoff for eliminating highfrequency noises and a sampling frequency of 3,000 Hz to exceed the Nyquist frequency. Tracheal sound fre- quencies can exceed 1,000 Hz (16), and these were not included in the sound envelope we measured. Nevertheless, our measurements of VT were reasonably accurate.…”

Section: Discussionmentioning

confidence: 99%

Phonospirometry for noninvasive measurement of ventilation: methodology and preliminary results

Que

Kolmaga

Durand

et al. 2002

Journal of Applied Physiology

View full text Add to dashboard Cite

We measured tracheal flow from tracheal sounds to estimate tidal volume, minute ventilation (VI), respiratory frequency, mean inspiratory flow (VT/TI), and duty cycle (TI/Ttot). In 11 normal subjects, 3 patients with unstable airway obstruction, and 3 stable asthmatic patients, we measured tracheal sounds and flow twice: first to derive flow-sound relationships and second to obtain flow-volume relationships from the sound signal. The flow-volume relationship was compared with pneumotach-derived volume. When subjects were seated, facing forward and with neck rotation, flexion, and standing, flow-volume relationship was within 15% of pneumotach-derived volume. Error increased with neck extension and while supine. We then measured ventilation without mouthpiece or nose clip from tracheal sounds during quiet breathing for up to 30 min. Normal results +/- SD revealed tidal volume = 0.37 +/- 0.065 liter, respiratory frequency = 19.3 +/- 3.5 breaths/min, VI = 6.9 +/- 1.2 l/min, VT/TI = 0.31 +/- 0.06 l/s, and TI/Ttot = 0.37 +/- 0.04. Unstable airway obstruction had large VI due to increased VT/TI. With the exception of TI/Ttot, variations in ventilatory parameters were closer to log normal than normal distributions and tended to be greater in patients. We conclude that phonospirometry measures ventilation reasonably accurately without mouthpiece, nose clip, or rigid postural constraints.

show abstract

Section: Discussionmentioning

confidence: 99%

Phonospirometry for noninvasive measurement of ventilation: methodology and preliminary results

Que

Kolmaga

Durand

et al. 2002

Journal of Applied Physiology

View full text Add to dashboard Cite

show abstract

“…3,4 The vibrations are transmitted to the skin through the tracheal wall and tissue beneath the skin, and can be picked up by a microphone placed over the trachea. Normal tracheal breath sound has a broad-band spectrum below 1000 Hz; it has been shown that its shape and spectral peaks change with the geometry and pathology of the upper airway, 3,4,12,16,24,28 while its amplitude and energy change with the amount of respiratory flow. 3,10,13,38 Based on these findings, several researchers have studied various features of tracheal sound for implementing acoustical respiratory flow estimation from tracheal sound.…”

Section: Introductionmentioning

confidence: 99%

Respiratory Flow–Sound Relationship During Both Wakefulness and Sleep and Its Variation in Relation to Sleep Apnea

et al. 2012

View full text Add to dashboard Cite

Tracheal respiratory sound analysis is a simple and non-invasive way to study the pathophysiology of the upper airway and has recently been used for acoustic estimation of respiratory flow and sleep apnea diagnosis. However in none of the previous studies was the respiratory flow-sound relationship studied in people with obstructive sleep apnea (OSA), nor during sleep. In this study, we recorded tracheal sound, respiratory flow, and head position from eight non-OSA and 10 OSA individuals during sleep and wakefulness. We compared the flow-sound relationship and variations in model parameters from wakefulness to sleep within and between the two groups. The results show that during both wakefulness and sleep, flow-sound relationship follows a power law but with different parameters. Furthermore, the variations in model parameters may be representative of the OSA pathology. The other objective of this study was to examine the accuracy of respiratory flow estimation algorithms during sleep: we investigated two approaches for calibrating the model parameters using the known data recorded during either wakefulness or sleep. The results show that the acoustical respiratory flow estimation parameters change from wakefulness to sleep. Therefore, if the model is calibrated using wakefulness data, although the estimated respiratory flow follows the relative variations of the real flow, the quantitative flow estimation error would be high during sleep. On the other hand, when the calibration parameters are extracted from tracheal sound and respiratory flow recordings during sleep, the respiratory flow estimation error is less than 10%.

show abstract

“…adults. In another study [29], it is shown that the anatomy of the trachea determines the characteristic features of tracheal sounds. However, there was no study confirming the change in the features of SS segments due to the height.…”

Section: Resultsmentioning

confidence: 97%

Snoring sounds’ statistical characteristics depend on anthropometric parameters

Azarbarzin¹,

Moussavi²

2012

JBiSE

View full text Add to dashboard Cite

Snoring is common in people with obstructive sleep apnea (OSA). Although not every snorer has OSA or vice-versa, many studies attempt to use snoring sounds for classification of people into two groups of OSA and simple snorers. This paper discusses the relationship between snorers' anthropometric parameters and statistical characteristics of snoring sound (SS) and also reports on classification accuracies of methods using SS features for screening OSA from simple snorers when anthropometric parameters are either matched or unmatched. Tracheal respiratory sounds were collected from 60 snorers simultaneously with full-night Polysomnography (PSG). Energy, formant frequency, Skewness and Kurtosis were calculated from the SS segments. We also defined and calculated two features: Median Bifrequency (MBF), and projected MBF (PMBF). The statistical relationship between the extracted features and anthropometric parameters such as height, Body Mass Index (BMI), age, gender, and Apnea-Hypopnea Index (AHI) were investigated. The results showed that the SS features were not only sensitive to AHI but also to height, BMI and gender. Next, we performed two experiments to classify patients with Obstructive Sleep Apnea (OSA) and simple snorers: Experiment A: a small group of participants (22 OSA and 6 simple snorers) with matched height, BMI, and gender were selected and classified using Naïve Bayes classifier, and Experiment B: the same number of participants with unmatched height, BMI, and gender were chosen for classification. A sensitivity of 93.2% (87.5%) and specificity of 88.4% (86.3%) was achieved for the matched (unmatched) groups.

show abstract

Effects of breathing pathways on tracheal sound spectral features

Cited by 31 publications

References 12 publications

Phonospirometry for noninvasive measurement of ventilation: methodology and preliminary results

Phonospirometry for noninvasive measurement of ventilation: methodology and preliminary results

Respiratory Flow–Sound Relationship During Both Wakefulness and Sleep and Its Variation in Relation to Sleep Apnea

Snoring sounds’ statistical characteristics depend on anthropometric parameters

Contact Info

Product

Resources

About