Modeling and measurement of flow effects on tracheal sounds

Abstract

The analysis of breathing sounds measured over the extrathoracic trachea offers a noninvasive technique to monitor obstructions of the respiratory tract. Essential to development of this technique is a quantitative understanding of how such tracheal sounds are related to the underlying tract anatomy, airflow, and disease-induced obstructions. In this study, the first dynamic acoustic model of the respiratory tract was developed that takes into consideration such factors as turbulent sound sources and varying glottal aperture. Model predictions were compared to tracheal sounds measured on four healthy subjects at target flow rates of 0.5, 1.0, 1.5, and 2.0 L/s, and also during nontargeted breathing. Both the simulation and measurement spectra depicted increasing sound power with increasing flow, with smaller incremental increases at the higher flow rates. A sound power increase of approximately 30 dB between a flow rate of 0.5 and 2.0 L/s was observed in both the simulated and measured spectra. Variations of as much as 15 dB over the 300-600 Hz frequency band were noted in the sound power produced during targeted and nontargeted breathing maneuvers at the same flow rates. We propose that this variability was in part due to changes in glottal aperture area, which is known to vary during normal respiration and has been observed as a method of flow control. Model simulations incorporating a turbulent source at the glottis with respiratory cycle variations in glottal aperture from 0.64 cm2 to 1.4 cm2 explained approximately 10 dB of the measured variation. This study provides the first links between spatially distributed sound sources due to turbulent flow in the respiratory tract and noninvasive tracheal sounds measurements.

Aeroacoustic sound alteration in airway bronchoconstriction, represented by a constricted T-branch model

“…This clearly shows that the sound frequency distribution of a model strongly depends on airway geometry and that the level of the PSD depends on the air flow rate (which also determines the Reynolds number in the constricted region). These results are contradictory to the theory proposed by Hardin and Patterson (1979), but in agreement with observations of lung sound over a range of flow rates in the inspiratory maneuver (Gavriely and Cugell, 1996;Harper, et al, 2003). In some further studies, it was found that the characteristics of the inspiratory sound (mean, median, or the highest frequency) were changed when the patient performed a methacholine challenge test (Habukawa et al, 2010).…”

“…In the higher constriction level model, compressibility of the flow must also be considered and this may lead to a significant increase in the higher frequency range. Physically, high frequency sound might be reduced during lung sound measurement from the chest surface because lung parenchyma acts as a low-pass filter, with a general threshold frequency of 1000 Hz (Schreur et al, 1995), or 2000 Hz (Harper et al, 2003).…”

Validation of a New System Using Tracheal Body Sound and Movement Data for Automated Apnea-Hypopnea Index Estimation

“…Nevertheless, body sound recorded at the trachea is affected by individual anatomy. 22 To compensate for this variation, the correlation between sound amplitude and airflow is individually and continuously recalculated.…”

Automatic wheeze detection based on auditory modelling

“…Breath sounds have a strong relationship with flow rate [20][21][22][23] . That is, all frequency components of spectral power are changed with flow rate: the higher the flow rate, the higher the spectral power.…”