Preserving Privacy in Clinical Trials: Scientific, Ethical, and Operational Considerations of On-Device Cough Monitoring

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.

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