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Accepted for/Published in: JMIR Formative Research

Date Submitted: Apr 14, 2022
Date Accepted: Jan 17, 2023
Date Submitted to PubMed: Jan 19, 2023

The final, peer-reviewed published version of this preprint can be found here:

Nighttime Continuous Contactless Smartphone-Based Cough Monitoring for the Ward: Validation Study

Barata F, Cleres D, Tinschert P, Shih I, Rassouli F, Boesch M, Brutsche M, Fleisch E

Nighttime Continuous Contactless Smartphone-Based Cough Monitoring for the Ward: Validation Study

JMIR Form Res 2023;7:e38439

DOI: 10.2196/38439

PMID: 36655551

PMCID: 9989914

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Nighttime continuous contactless smartphone-based cough monitoring for the ward: A validation study

  • Filipe Barata; 
  • David Cleres; 
  • Peter Tinschert; 
  • Iris Shih; 
  • Frank Rassouli; 
  • Maximilian Boesch; 
  • Martin Brutsche; 
  • Elgar Fleisch

ABSTRACT

Background:

Clinical deterioration can go unnoticed in hospital wards for hours. Mobile technologies such as wearables and smartphones enable automated, continuous, non-invasive ward monitoring allowing detection of subtle changes in vital signs. In past decades, many efforts have been made to develop an automatic cough counting tool. To date, however, there is neither a standardized, sufficiently validated method, nor is there a scalable cough monitor that can be deployed on a consumer-centric device that reports cough counts continuously. These shortcomings limit the tracking of coughing and, consequently, hinder the monitoring of disease progression in prevalent respiratory diseases such as asthma, chronic obstructive pulmonary disease, and COVID-19 in the ward.

Objective:

This exploratory study involves the validation of an automated smartphone-based monitoring system for continuous cough counting in the ward.

Methods:

Automated cough counts are measured consistently on-device and compared with cough and non-cough sounds counted manually over eight hour-long nocturnal recordings in nine patients with pneumonia in the ward.

Results:

The proposed system yielded sensitivity and specificity of 71% and 99% for detecting coughs. The mean difference between the automated and human rater cough counts were -1.2, CI 95% [-12.8, 10.4] coughs per hour within-subject.

Conclusions:

The proposed system thus represents a smartphone cough counter that can be used for continuous hourly assessment of cough frequency in the ward.


 Citation

Please cite as:

Barata F, Cleres D, Tinschert P, Shih I, Rassouli F, Boesch M, Brutsche M, Fleisch E

Nighttime Continuous Contactless Smartphone-Based Cough Monitoring for the Ward: Validation Study

JMIR Form Res 2023;7:e38439

DOI: 10.2196/38439

PMID: 36655551

PMCID: 9989914

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