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Fully portable continuous real-time auscultation with a soft wearable stethoscope designed for automated disease diagnosis

  • Sung Hoon Lee
    ,
  • Yun Soung Kim
    ,
  • Min Kyung Yeo
    ,
  • Musa Mahmood
    ,
  • ,
  • Chaeuk Chung
*Corresponding author for this work
  • Georgia Institute of Technology
    ,
  • School of Electrical and Computer Engineering
    ,
  • Chungnam National University
    ,
  • IEN Center for Human-Centric Interfaces and Engineering
    ,
  • Chungnam National University Hospital
Research Output:
Contribution to journal
Article
Peer-review

Open access

Abstract

Modern auscultation, using digital stethoscopes, provides a better solution than conventional methods in sound recording and visualization. However, current digital stethoscopes are too bulky and nonconformal to the skin for continuous auscultation. Moreover, motion artifacts from the rigidity cause friction noise, leading to inaccurate diagnoses. Here, we report a class of technologies that offers real-time, wireless, continuous auscultation using a soft wearable system as a quantitative disease diagnosis tool for various diseases. The soft device can detect continuous cardiopulmonary sounds with minimal noise and classify real-time signal abnormalities. A clinical study with multiple patients and control subjects captures the unique advantage of the wearable auscultation method with embedded machine learning for automated diagnoses of four types of lung diseases: crackle, wheeze, stridor, and rhonchi, with a 95% accuracy. The soft system also demonstrates the potential for a sleep study by detecting disordered breathing for home sleep and apnea detection.

Bibliographic Information

Output type

Research Output:
Contribution to journal
Article
Peer-review

Original language

English

Article number

eabo5867

Journal (Volume, Issue Number)

Science Advances (Volume 8, Issue 21)

Publication milestones

  • Published - 05/2022

Publication status

Published - 05/2022

Publication IDs

  • Scopus: 85130859850
  • PubMed: 35613271