JMIR Publications

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.