Respiratory Sounds: Laryngeal Origin Sounds

Barker, Nicola; Elphick, Heather

doi:10.1007/978-3-319-71824-8_13

Cited by 4 publications

(8 citation statements)

References 44 publications

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“…The tonal characteristics of the SGS sound are highly variable but when combined with factors such as the respiration phase, volume, duration, rate of onset, and associated symptoms, the tonal characteristics of the sound can serve as an indicator of the location and size of the airway obstruction [2]. This current study suggests that developing different glottal tasks can provide more acoustic information for differential diagnosis, which is encouraging since the SGS sound is more affected by glottal configuration.…”

Section: Discussionsupporting

confidence: 52%

“…SGS can be of idiopathic, congenital, or acquired origin (e.g., as a result of prolonged intubation) [1]. Apart from common symptoms like hoarse voice, shortness of breath, and dysphonia, SGS can also lead to adventitious tonal sound during respiration, which is sometimes referred to as stridor [1][2][3][4]. For example, P. H. Holinger et al [4] reported that in infants and children with congenital SGS, 43% presented stridor.…”

Section: Introduction 1subglottic Stenosis and Respiratory Soundsmentioning

confidence: 99%

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Effect of Subglottic Stenosis on Expiratory Sound Using Direct Noise Calculation

Geng,

Xue,

Thomson

et al. 2023

Applied Sciences

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Subglottic stenosis (SGS) is a rare yet potentially life-threatening condition that requires prompt identification and treatment. One of the primary symptoms of SGS is a respiratory sound that is tonal. To better understand the effect of SGS on expiratory sound, we used direct noise calculation to simulate sound production in a simplified axisymmetric configuration that included the trachea, the vocal folds, the supraglottal tract, and an open environmental space. This study focused on flow-sustained tones and explored the impact of various parameters, such as the SGS severity, the SGS distance, the flowrate, and the glottal opening size. It was found that the sound pressure level (SPL) of the expiratory sound increased with flowrate. SGS had little effect on the sound until its severity approached 75% and SPL increased rapidly as the severity approached 100%. The results also revealed that the tonal components of the sound predominantly came from hole tones and tract harmonics and their coupling. The spectra of the sound were greatly influenced by constricting the glottis, which suggests that respiratory tasks that involve maneuvers to change the glottal opening size could be useful in gathering more information on respiratory sound to aid in the diagnosis of subglottic stenosis.

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Section: Discussionsupporting

confidence: 52%

Section: Introduction 1subglottic Stenosis and Respiratory Soundsmentioning

confidence: 99%

Effect of Subglottic Stenosis on Expiratory Sound Using Direct Noise Calculation

Geng,

Xue,

Thomson

et al. 2023

Applied Sciences

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“…The discontinuous, noisy nature of the BR is evident from Figure 1c. The musical and sinusoidal nature of the ST is visible in the magnified time-domain signal of ST (Figure 1d) (Barker & Elphick, 2018). The time-domain signal of ST also contains regions, a combination of two modulated signals.…”

Section: Resultsmentioning

confidence: 95%

Nonlinear signal processing, spectral, and fractal based stridor auscultation: A machine learning approach

Raj

Renjini

Swapna

et al. 2021

KJS publishes peer-review articles in Mathematics, Computer Sci

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The work reported in the paper analyses the adventitious stridor breath sound (ST) and the normal bronchial breath sound (BR) using spectral, fractal, and nonlinear signal processing methods. The sixty breath sound signals are subjected to power spectral density (PSD) and wavelet analyses to understand the temporal evolution of the frequency components. The energy envelope of the PSD plot of ST shows three peaks labelled as A (256 Hz), B (369 Hz), and C (540 Hz), of which A alone is present in BR at 265 Hz. The appearance of B and C in the PSD plot of ST is due to the obstructions in the trachea and upper airways caused by lesions. The phase portrait analysis of the time series data of ST and BR gives information about the randomness and the sample entropy of the dynamical system. The study reveals that the fractal dimension and sample entropy values are higher for BR, which may be due to the musical ordered behaviour of ST. The machine learning techniques based on the features extracted from the PSD data and phase portrait parameters offer good predictability, besides the classification of BR and ST, and thereby revealing its potential in pulmonary auscultation.

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“…The 'Waveform Graph' function was used to display the real time waveform signals on the display screen. The 'Time Target' function was used to set the sound recording time of the stethograph system for 20 seconds to cover at least 4 breath cycles (based on a previously reported study by Gurung et al, [35]). The 'Write to Measurement File' option was used to save the recorded data in a '.lvm' format database.…”

Section: E Custom-built Labview and Matlab Programmentioning

confidence: 99%

“…Wheeze, crackle and rhonchi are the most common abnormalities in the CCD [35]. Wheeze is a high-pitched adventitious, continuous sound.…”

Section: A Identification Of Abnormalities In Lung Sounds (Visualization Of Lung Sounds)mentioning

confidence: 99%

Development of a Novel Wireless Multi-Channel Stethograph System for Monitoring Cardiovascular and Cardiopulmonary Diseases

Zhang

Maddipatla

Narakathu

et al. 2021

Preprint

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A multi-channel stethograph system was designed and developed as an electronic auscultation system for graphic recording of heart, lung and trachea (HLT) sounds non-invasively through a set of 16 acoustic sensors. The multi-channel stethograph system was fabricated by placing 16 microphone based acoustic sensor in a CNC machined Delrin® housing cases that are covered using diaphragms. Among the 16 acoustic sensors, 14 were positioned in a memory foam pad and 2 were placed directly on the heart and trachea to acquire sounds simultaneously from the lungs, heart and trachea. The sounds acquired from the 16 acoustic sensors were processed through a custom designed and fabricated 16-channel PCB for signal conditioning. A National Instruments (NI) 9205 data acquisition device (DAQ) along with a NI 9191 wireless chassis was used to acquire and wirelessly transmit the data from the 16-channel PCB to a Wi-Fi enabled device such as a PC/tablet. A custom LabVIEW program was developed on a Wi-Fi enabled PC/tablet to record the data from the DAQ. In addition, a MATLAB program was developed to convert the recorded data from the acoustic sensors into 16 audio files (for audio playback) and plot the waveforms in time and frequency domain as well as spectrogram for visual examination of any abnormal patterns in inhalation and exhalation. This provides critical information on the presence of wheezes, crackles and rhonchi sounds as well as abnormal heartbeat and respiration rate which helps in analyzing the condition of heart and lungs. The graphically displayed HLT sounds will help physicians in the clinical diagnosis and monitoring of lung and heart disorders, particularly chronic obstructive pulmonary disease (COPD), asthma, pneumonia, and congestive heart failure by providing objective evidence.

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Respiratory Sounds: Laryngeal Origin Sounds

Cited by 4 publications

References 44 publications

Effect of Subglottic Stenosis on Expiratory Sound Using Direct Noise Calculation

Effect of Subglottic Stenosis on Expiratory Sound Using Direct Noise Calculation

Nonlinear signal processing, spectral, and fractal based stridor auscultation: A machine learning approach

Development of a Novel Wireless Multi-Channel Stethograph System for Monitoring Cardiovascular and Cardiopulmonary Diseases

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