PPG-based algorithm achieves 98.93% accuracy in detecting device wear status with negligible battery impact, eliminating the critical problem of misclassifying patient stillness as non-compliance in continuous monitoring applications.
Simulation evidence supporting continuous, automated monitoring as a superior approach for clinical research.
A study demonstrating the use of synchronized wearables to determine when a cough monitor detects non-user coughs
Addressing privacy risks in clinical trials - edge computing and on-device cough analytics safeguard participant privacy, ensure regulatory compliance, and optimize clinical trial scalability.
Exploring integration of AI-driven cough monitoring into wearable technology, highlighting its potential as an early indicator of respiratory illness, immune stress, and chronic disease, while addressing technical feasibility, clinical validation, and future applications in personalized health & welness
Case studies on digital behavioral interventions for chronic cough management inside CoughPro, demonstrating promising reductions in cough frequency through AI-powered monitoring and science-based suppression techniques.
White paper on the connection between heart rate and cough severity. Integrating cardiovascular and respiratory metrics offers new possibilities for patient monitoring, clinical trials, and health technology innovation.
7-day continuous cough monitoring outperforms 24-hour methods. Hyfe white paper presents data-driven evidence showing how prolonged monitoring provides more reliable insights for clinical trials and research studies, offering a new standard in understanding cough variability
Exploring advanced machine learning models as solutions to the "Other Peoples Cough Problem" - distinguishing user coughs from others in shared environments.
Explores the cost-effectiveness of at-home monitoring for Chronic Obstructive Pulmonary Disease (COPD) exacerbations using a cough monitoring system. It highlights the significant economic burden COPD imposes on healthcare systems, especially through acute exacerbations that often lead to costly hospitalizations.
Explores the complexities of defining and measuring cough bouts using continuous monitoring technology. It highlights the inadequacies of traditional definitions and emphasizes the need for patient-centered metrics to better capture the severity and impact of chronic coughing on individuals' quality of life.
28.04.2025
As clinical research evolves toward high-frequency, decentralized, and digitally augmented models, a central paradox emerges: the very technologies that offer unprecedented scientific precision also create new vulnerabilities in participant privacy.
In this paper, the Hyfe team systematically examines this tension, focusing on the unique privacy challenges posed by audio-based digital endpoints. The paper critiques traditional clinical trial methodologies reliant on continuous audio recording - exposing risks such as participant behavior modification, elevated attrition rates, re-identification threats, and significant operational burdens related to data storage, bandwidth, and compliance with GDPR, HIPAA, and related frameworks.
The paper advocates for a paradigm shift toward edge computing and privacy-preserving analytics, where cough events are detected in real time on participant devices without recording or transmitting raw audio data. Through technical validation studies and deployment case examples, Hyfe demonstrates that on-device cough monitoring achieves clinical-grade accuracy while significantly enhancing participant trust and trial scalability.
The paper concludes that privacy-by-design architectures are not merely ethical enhancements but scientific necessities for future-proofing digital clinical trials, ensuring data integrity, preserving participant autonomy, and enabling large-scale, longitudinal research without compromising regulatory compliance or operational feasibility.
PPG-based algorithm achieves 98.93% accuracy in detecting device wear status with negligible battery impact, eliminating the critical problem of misclassifying patient stillness as non-compliance in continuous monitoring applications.
Simulation evidence supporting continuous, automated monitoring as a superior approach for clinical research.
A study demonstrating the use of synchronized wearables to determine when a cough monitor detects non-user coughs
Addressing privacy risks in clinical trials - edge computing and on-device cough analytics safeguard participant privacy, ensure regulatory compliance, and optimize clinical trial scalability.
