Smartphone-Enabled Cough Detection in Severely Exacerbated COPD: An Exploratory Pilot Study

Area of Science:

• Digital health technologies
• Respiratory medicine
• Biomarker discovery

Background:

• Chronic obstructive pulmonary disease (COPD) incidence is rising globally.
• Acute exacerbations of COPD (AECOPD) significantly increase morbidity, mortality, and healthcare costs.
• Remote patient monitoring via digital health tools can improve COPD management.

Purpose of the Study:

• To assess the feasibility of smartphone-enabled cough monitoring in hospitalized AECOPD patients.
• To evaluate the biomarker potential of automated cough detection.
• To correlate cough counts with clinical and biochemical markers during AECOPD recovery.

Main Methods:

• A single-center, prospective, observational cohort study enrolled 23 hospitalized AECOPD patients.
• A contact-free, smartphone-enabled system was used for automated, near real-time cough detection and quantification.
• Cough counts were correlated with clinical data and biochemical markers.

Main Results:

• Smartphone-based cough detection was feasible in hospitalized AECOPD patients.
• Cough counts were highest at enrollment (approx. 15/hour) and declined during recovery (to <5/hour).
• Cough counts showed diurnal variation, were inversely associated with oxygen saturation, and positively correlated with body temperature.

Conclusions:

• Automated cough monitoring using smartphones is a viable tool for AECOPD patients.
• Cough counts reflect disease status and correlate with key clinical indicators.
• This technology may enable telemonitoring and serve as an early digital biomarker for AECOPD, facilitating timely interventions and cost savings.