53
Research Trials
20
Peer-reviewed publications
16
Clinical Conditions
At CHEST 2025, held in Chicago, Illinois, Laurie Slovarp, PhD, CCC-SLP, professor at the University of Montana and certified speech pathologist, presented a poster on the development of a digital therapeutic designed to improve access to behavioral cough suppression therapy for patients with refractory chronic cough.
A large-scale trial examining the effect of azithromycin on the relationship between oesophageal function and cough as evaluated by Hyfe's cough monitoring technology in respiratory disease is feasible and acceptable to patients.
This study used Hyfe's wearable cough monitor during a 7-day run in, 28-day treatment, and 14-day follow-up period in patients with chronic bronchitis.
Periods of intense coughing (termed bouts, epochs or bursts) are particularly problematic for some coughers and may not be reflected by simply counting the number of coughs per day. This study explored how varying the definition of bouts yield different impressions of cough severity.
01.10.2024
The ability to passively and continuously monitor cough would significantly improve cough management and research. Recent advances in acoustic AI have prompted the development of automated cough monitoring technology. Here we describe for the first time the process and results of validating an acoustic AI based cough monitor.
We collected 20-24 hours of continuous sounds from each of 23 adult subjects while they wore a Cough Monitor and went about their usual daily activities. The watch was charged <3 ft by the bedside at night, and manual cough counting is considered the gold standard. We noted the exact time of every cough in the continuous recording using a validated annotation methodology. These results were compared to the timestamps of cough from the Cough Monitor to determine the system’s performance for each subject, for the entire group, and for subsets using event-to-event and hourly rate correlation analyses.
In 546 hours of monitoring across 23 subjects, 4,454 coughs were detected by the trained annotators. Hyfe's CoughMonitor sensitivity was 90.4% (95% CI: 89.5-91.2%), with a false positive rate of 1.03/hour (95% CI: 0.94-1.11). Hourly cough rates showed a high correlation between manual counts and CoughMonitor data (Pearson r = 0.99, OLS slope = 0.94, intercept = 0.68).
The Cough Monitor's accuracy, ease of use, and scalability suggest it could significantly enhance cough management and research.
