⚡ electrical engineering

An auscultation location specific study on the relationship between expiratory-to-inspiratory acoustic patterns and spirometric airflow limitation across age and gender in asthmatic patients

This study demonstrates that the expiratory-to-inspiratory acoustic power ratio in specific frequency bands, particularly at posterior lung sites, correlates significantly with spirometric airflow limitation in asthmatic patients, with the strength and location of these associations varying notably by age and gender.

Original authors: Dheeraj Harish Kumar, Sanjana M C, Keerthi Priya, K V Nikhath Khanam, Uma Maheshwari Krishnaswamy, Prasanta Kumar Ghosh

Published 2026-06-16

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CC BY 4.0

Original authors: Dheeraj Harish Kumar, Sanjana M C, Keerthi Priya, K V Nikhath Khanam, Uma Maheshwari Krishnaswamy, Prasanta Kumar Ghosh

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine your lungs as a complex network of hollow tunnels (airways) that act like a musical instrument. When you breathe, air rushes through these tunnels, creating sound. In people with asthma, these tunnels get narrow and stiff, making it harder to push air out.

Doctors usually check how bad this blockage is using a "blow test" called spirometry, where you have to take a deep breath and blow as hard and fast as you can into a machine. This is like trying to blow out a candle from a distance; if you are tired, a child, or an elderly person, it's hard to blow hard enough to get an accurate reading.

This paper asks a simple question: Can we listen to the "music" of breathing to figure out how blocked the lungs are, without needing a hard blow?

Here is what the researchers found, broken down into everyday concepts:

1. The "Volume Ratio" (The E/I Ratio)

Think of breathing as a song with two parts: the "inhale" (taking a breath in) and the "exhale" (blowing it out).

In healthy lungs, the sound of breathing in and breathing out is somewhat balanced.
In asthmatic lungs, the "exhale" part gets noisy and turbulent because the air is struggling to squeeze through narrow tubes.
The researchers calculated a "Volume Ratio": How loud is the "out" sound compared to the "in" sound? They found that when this "out" sound gets louder relative to the "in" sound, it matches up with the "blow test" results showing more severe blockage.

2. The "Radio Tuner" (Frequency Bands)

Just like a radio has different stations, lung sounds have different pitches (frequencies).

The researchers tried listening to the whole range of sounds (low to high pitches).
The Discovery: They found that the "sweet spot" for listening was the low-to-mid range (like a deep hum or a low buzz).
The very low sounds were too muddy (like hearing a heartbeat or muscle noise), and the very high sounds were too quiet to tell much. The "Goldilocks" zone was between 100 Hz and 400 Hz. In this range, the sound of the air struggling to get out was the clearest indicator of how bad the asthma was.

3. The "Listening Post" (Where to Put the Stethoscope)

The researchers didn't just listen to one spot; they put their digital stethoscope on four different spots on the back of the chest (Left/Right, Upper/Lower).

The General Rule: The lower parts of the back (near the bottom of the lungs) were usually the best places to listen. It's like checking the foundation of a house; if the bottom is shaky, the whole structure is affected.
The Twist (Age Matters):
- Younger Adults (20s-30s): The "best listening spot" was the bottom-left of the back.
- Older Adults (50s-60s): The "best listening spot" shifted to the top-left of the back.
- Why? As we age, the bottom of our lungs tends to "close up" a bit earlier when we breathe out (like a deflating balloon that crinkles at the bottom first). So, in older people, the top of the lungs does more of the work, and that's where the most important clues about the blockage are found.

4. The "Gender Difference"

The study also noticed that men and women had different "best listening spots."

Men: The bottom-left spot was the most reliable.
Women: The top-left spot was the most reliable.
Why? Men and women have different lung sizes and airway widths (like different sized pipes). These physical differences change where the sound of the air struggling is loudest.

The Bottom Line

This study didn't invent a new machine or a new cure. Instead, it acted like a detective map. It showed that:

Listening to the low-to-mid hum of breathing is a good way to guess how blocked the lungs are.
You can't use the same "listening spot" for everyone. To get the best clue, you need to know the person's age and gender to know exactly where to place the stethoscope on their back.

Essentially, the paper proves that the "music" of breathing changes in predictable ways based on who is breathing, and if we know how to tune our ears to the right pitch and the right spot, we can hear the severity of asthma without needing a difficult "blow test."

Technical Summary: Auscultation Location-Specific Analysis of Expiratory-to-Inspiratory Acoustic Patterns in Asthma

Problem Statement
Asthma is a chronic inflammatory disease characterized by expiratory airflow limitation, clinically monitored via spirometry. The gold standard metric, the FEV1/FVC ratio (the proportion of air exhaled in the first second relative to total forced vital capacity), relies heavily on patient effort and cooperation. This dependency makes reliable assessment difficult in specific demographics, such as children and the elderly. While prior research suggests that respiratory sounds recorded at posterior lung sites reflect regional airflow patterns, the influence of demographic factors—specifically age and gender—on the relationship between acoustic patterns and spirometric limitation remains underexplored. This study addresses the gap in understanding how the correlation between the expiratory-to-inspiratory (E/I) spectral power ratio and FEV1/FVC varies across different auscultation locations, age groups, and genders in asthmatic patients.

Methodology
The study analyzed data from 141 clinically diagnosed asthma participants (66 males, 75 females) aged 20–60 years.

Data Acquisition: Respiratory sounds were recorded at four posterior auscultation sites: Left Upper (LU), Left Lower (LL), Right Upper (RU), and Right Lower (RL). Five breath cycles were captured per site using a Littmann CORE digital stethoscope at a 4 kHz sampling rate while participants breathed normally in an upright position.
Signal Processing:
- Inhalation and exhalation segments were manually annotated.
- The Short-Time Fourier Transform (STFT) was applied using a Hanning window (length $N=2048$ , hop length $H=512$ ) to compute time-frequency spectral power.
- Spectral power was averaged across time frames and specific frequency bands: 100–200 Hz, 200–400 Hz, 400–800 Hz, and broadband 0–800 Hz.
- The E/I ratio was calculated as the ratio of expiratory spectral power ( $P^{(E)}_B$ ) to inspiratory spectral power ( $P^{(I)}_B$ ) for each breath cycle. The median of five cycles per site was used as the representative subject-level value to mitigate artifacts.
Statistical Analysis: Spearman's rank correlation coefficient ( $\rho$ ) was computed to assess the monotonic relationship between the E/I ratio and the FEV1/FVC ratio. Analyses were stratified by age groups (20–30, 30–40, 40–50, 50–60) and gender, with statistical significance set at $p < 0.05$ .

Key Results

Frequency Dependence: Significant correlations between the E/I ratio and FEV1/FVC were consistently observed in the lower-to-mid frequency bands (100–200 Hz and 200–400 Hz). The 400–800 Hz band and the broadband 0–800 Hz range showed weaker associations, likely due to the inclusion of physiological noise (0–100 Hz) and reduced dominance of airflow-related acoustic energy at higher frequencies.
Location Specificity:
- Overall: The Left Lower (LL) posterior site generally demonstrated stronger associations with FEV1/FVC compared to other sites, particularly in the 100–200 Hz band.
- Age Trends: In younger adults (20–30 years), the LL site showed the strongest correlations. In contrast, older adults (50–60 years) exhibited the strongest correlations at the Left Upper (LU) site across all frequency bands.
- Gender Trends: Gender-stratified analysis revealed distinct patterns: males showed stronger correlations at the LL site, whereas females showed stronger correlations at the LU site.
Physiological Interpretation: The shift in correlation strength from lower to upper lung regions with increasing age aligns with known physiological changes, such as reduced elastic recoil and increased closing volume, which lead to premature small airway closure in the lower lung zones. This redistribution of airflow contribution may explain why upper regions become more representative of expiratory limitation in older populations.

Significance and Claims
The paper claims that the relationship between acoustic E/I ratios and spirometric airflow limitation is not uniform but exhibits systematic, location-specific variations dependent on age and gender.

Non-Invasive Biomarker Potential: The study suggests that the E/I ratio, particularly in the 100–400 Hz range, could serve as a non-invasive and less effort-dependent marker for assessing obstruction severity in asthma.
Demographic Nuance: A primary contribution is the demonstration that the optimal auscultation location for acoustic assessment may vary based on patient demographics. Specifically, the study posits that relying on a single fixed location (e.g., LL) may not be universally optimal across all age groups or genders, as the spatial distribution of airflow limitation changes with physiological aging and anatomical differences.
Validation of Acoustic-Spirometric Link: The findings reinforce the physiological consistency of comparing expiratory acoustic characteristics with spirometric indices, confirming that changes in acoustic patterns reflect underlying airflow mechanics.

The authors conclude that future acoustic biomarker development should consider these demographic and spatial factors to improve the accuracy of non-invasive asthma monitoring.