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.
Recent advances in wearable technology have made once-exotic metrics (like heart rate variability or oxygen saturation) widely available. Yet one vital indicator - cough - remains mostly untracked. Cough is a key marker for respiratory infections, immune stress, and chronic conditions such as asthma, COPD, and heart failure. It is also the leading reason people seek medical help. Historically, measuring cough continuously was very difficult, even in clinical settings.
AI-driven solutions now address this gap. Passive cough detection on wearables and smart devices is both accurate and scalable. These platforms can now easily integrate cough data with other health signals (e.g., sleep quality, heart rate variability, and environmental factors) to offer deeper, more valuable health and wellness insights. Early findings show that subtle changes in cough frequency can foreshadow infections, detect stress-related immune suppression, and flag worsening symptoms in chronic disease.
Adding cough metrics helps wearable and smart devices providers stand out in a saturated market. Many users would benefit:
In research settings, continuous cough monitoring provides objective data that do not rely on self-reporting. This creates new clinical endpoints for studies on respiratory conditions, cardiac health, and infectious diseases.
Several challenges have emerged, but solutions are in place. The best cough detection models run efficiently on-device, minimizing battery drain. Privacy concerns are addressed by processing data locally, storing no audio, and transmitting only cough timestamps. Clinical trials in multiple regions confirm that specificity and sensitivity for lead technologies can exceed 90%, showing real-world feasibility.
Looking ahead, standardizing cough-monitoring protocols will encourage broader adoption and fuel research into immune health, respiratory disease, and personalized preventive care. As integration becomes simpler and clinical evidence builds, cough tracking is poised to become a core feature of next-generation health platforms. For scientists, clinicians, and technology developers, it represents a powerful new dimension in wearable health and a major opportunity for innovation.
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.
