Development of a miniaturized mechanoacoustic sensor for continuous, objective cough detection, characterization and physiologic monitoring in children with cystic fibrosis.

Andreas Tzavelis, John Palla, Radhika Mathur, Brittany Bedford, Yung Hsuan Wu, Jacob Trueb, Hee Sup Shin, Hany Arafa, Hyoyoung Jeong, Wei Ouyang, Jay Young Kwak, Jennifer Chiang, Sydney Schulz, Tina M. Carter, Vittobai Rangaraj, Aggelos K. Katsaggelos, Susanna A. McColley, John A Rogers

Research output: Contribution to journalArticlepeer-review

Abstract

Cough is an important symptom in children with acute and chronic respiratory disease. Daily cough is common in Cystic Fibrosis (CF) and increased cough is a symptom of pulmonary exacerbation. To date, cough assessment is primarily subjective in clinical practice and research. Attempts to develop objective, automatic cough counting tools have faced reliability issues in noisy environments and practical barriers limiting long-term use. This single-center pilot study evaluated usability, acceptability and performance of a mechanoacoustic sensor (MAS), previously used for cough classification in adults, in 36 children with CF over brief and multi-day periods in four cohorts. Children whose health was at baseline and who had symptoms of pulmonary exacerbation were included. We trained, validated, and deployed custom deep learning algorithms for accurate cough detection and classification from other vocalization or artifacts with an overall area under the receiver-operator characteristic curve (AUROC) of 0.96 and average precision (AP) of 0.93. Child and parent feedback led to a redesign of the MAS towards a smaller, more discreet device acceptable for daily use in children. Additional improvements optimized power efficiency and data management. The MAS's ability to objectively measure cough and other physiologic signals across clinic, hospital, and home settings is demonstrated, particularly aided by an AUROC of 0.97 and AP of 0.96 for motion artifact rejection. Examples of cough frequency and physiologic parameter correlations with participant-reported outcomes and clinical measurements for individual patients are presented. The MAS is a promising tool in objective longitudinal evaluation of cough in children with CF.

Original languageEnglish (US)
Pages (from-to)1-13
Number of pages13
JournalIEEE Journal of Biomedical and Health Informatics
DOIs
StateAccepted/In press - 2024

Keywords

  • Biomedical monitoring
  • Hospitals
  • Lung
  • Monitoring
  • Particle measurements
  • Pediatrics
  • Usability

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics
  • Electrical and Electronic Engineering
  • Health Information Management

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