53
Research Trials
20
Peer-reviewed publications
16
Clinical Conditions
This narrative review by Hyfe's R&D team makes the case that continuous cough monitoring (CCM), powered by acoustic AI, transforms cough from a subjective symptom into a quantifiable digital biomarker.
This ERS 2025 abstract from Hyfe's R&D team validates the wear-detection algorithm built into the Hyfe CoughMonitor smartwatch against participant-reported wear status across 418 person-hours of data in ten participants.
Authored by Hyfe's R&D team, this review synthesizes work presented at the European Respiratory Society Congress 2025 and argues that objective cough monitoring has crossed a practical threshold, moving from experimental technique to deployable clinical endpoint.
This study asked whether the core components of BCST could be embedded in a digital therapeutic and paired with continuous, objective cough monitoring inside the CoughPro app.
02.07.2021
This paper proposes an observational protocol to monitor and analyze acoustic data (like cough sounds) to identify potential outbreaks rapidly. It aims to develop a digital acoustic surveillance system for the early detection of respiratory disease outbreaks in Spain.
The researchers are utilizing digital devices, such as smartphones and environmental sensors, running AI powered cough detection technology, to record acoustic oustic data in selected regions of Spain. Advanced algorithms and artificial intelligence techniques are applied to the collected acoustic data to detect patterns indicative of respiratory diseases.
The study will be conducted in diverse regions across Spain, possibly targeting areas with high population densities or previous records of significant respiratory disease outbreaks.
Key Takeaways
Implications for Public Health Policy: Successful implementation of this protocol could influence public health policies, especially in adopting more digital and AI-based approaches for disease surveillance and response.
