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A wearable multi-modal acoustic system for breathing analysis.

Lloyd E Emokpae1, Roland N Emokpae1, Ese Bowry1

  • 1LASARRUS Clinic and Research Center, Baltimore, Maryland 21220, USA.

The Journal of the Acoustical Society of America
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A new wearable system detects breathing changes in Chronic Obstructive Pulmonary Disease (COPD) patients. This early detection can reduce hospitalizations and healthcare costs, especially during pandemics.

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Area of Science:

  • Biomedical Engineering
  • Respiratory Medicine
  • Wearable Technology

Background:

  • Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of death globally, with exacerbations often requiring hospitalization.
  • Early detection of COPD exacerbations is crucial for timely home treatment, reducing readmissions and healthcare burdens, particularly during health crises like COVID-19.
  • Current lung function assessment tools are costly, time-consuming, and unsuitable for remote monitoring during acute events.

Purpose of the Study:

  • To introduce a novel wearable multi-modal system for analyzing breathing patterns.
  • To assess the system's capability in quantifying airflow obstructions in individuals with COPD.
  • To explore the potential of this technology for remote patient monitoring and early exacerbation detection.

Main Methods:

  • Development of a wearable electroacoustic system with a body area sensor network.
  • Integration of multi-modal sensing capabilities including digital stethoscope, ECG, thermometer, and goniometer.
  • Utilizing the signal-to-noise ratio (SNR) of the acoustic spectrum as a metric for breathing intensity.

Main Results:

  • The wearable system demonstrated feasibility in collecting breathing data from both healthy subjects and COPD patients.
  • A positive correlation was observed between SNR values and a health-scale score in collected data.
  • The system shows potential for quantifying airflow obstructions and monitoring breathing intensity.

Conclusions:

  • The presented wearable multi-modal system offers a promising non-invasive approach for breathing analysis.
  • This technology could facilitate early detection of COPD exacerbations, enabling timely interventions and reducing healthcare system strain.
  • Further research and validation are warranted to establish its clinical utility in managing COPD patients.