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.
16.10.2024
This paper presents a data-driven argument for extending the standard cough monitoring period to seven days, significantly longer than the conventional 24-hour period. This conclusion is grounded in statistical analysis derived from large-scale continuous cough monitoring, which offers insights into the frequency and variability of coughing over time.
The document addresses the significant limitations of historic cough research, which could not rely on comprehensive data due to technological constraints. With the advent of advanced cough monitoring tools, researchers now have access to vast datasets of coughs, which allow for more detailed analyses of coughing patterns.
A key insight is that daily cough rates, traditionally used in studies, do not conform to standard statistical distributions. However, hourly cough counts exhibit more predictable behavior. This breakthrough allows for realistic simulations of cough patterns, which are used to model 504 hours of coughing for over 20 million simulated subjects.
Through this simulation, the study determined that for most subjects, a seven-day monitoring period provides reliable estimates of hourly cough averages and variances.
The paper emphasizes that the variability in cough frequency both across and within individuals makes seven days a more accurate standard for most cases.
Key Insights:
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.
