The Development of a Smart Telehealth ECG and Human Activity Monitoring System to Improve Cardiovascular health of Older Adults - PROJECT SUMMARY/ABSTRACT While the quality of overall health care has been substantially improved during the past few decades, cardiovascular disease (CVD) continues to be the number one leading cause of morbidity and mortality in the United States. Arrhythmias and other cardiac symptoms are often not detectable since many of them are intermittent. To enhance cardiovascular health care, therefore, it is important to develop a smart telehealth system that provides long-term ambulatory monitoring of high-quality ECG signals with automated ECG analysis for timely intervention when cardiac events occur. Furthermore, it is essential to understand needs, perceptions, and preferences of older adults for telehealth and long-term wearable health monitoring devices to improve their acceptance and use of the system since it will be widely used among older adults due to their high rates of CVD. The broad, long-term goal of this study is to reduce morbidity and mortality of CVD and improve cardiovascular health of older adults by developing a user-friendly, smart telehealth system. As the first step toward achieving the goal, the objective of this study is to develop a new class of technologies for an ambulatory ECG and human activity monitoring system via fundamental understanding of inkjet-printing technologies, stretchable mechanics, deep learning approaches for automated analysis, and knowledge and perceptions of older adults for wearable health monitoring-based telehealth including the proposed system. This study includes the following specific aims: (1) Experimental study for optimal inkjet printing conditions and flexible/stretchable mechanics of inkjet- printed electronics for long-term ambulatory ECG and human activity monitoring. The expected outcome will be successful demonstration of a low-cost, simple, and rapid fabrication for ultrathin, skin-wearable health monitoring devices; (2) Development of two different state-of-the-art Deep Learning based models for classification of ECG arrhythmias and human activities to fulfill needs of both health care providers and patients for fast but accurate and efficient arrhythmia detection in various computing environments; (3) Understand telehealth literacy and perceptions of older adult population for long-term wearable health monitoring devices. The structured studies for understanding knowledge and perceptions of the older adult population will ensure the successful adoption of the smart telehealth system; and (4) Validation of features and functions of the proposed device for smart telehealth. This convergence research with expertise in biomedical engineering, computer science, and social work will tackle existing complex challenges in the development of the smart telehealth system. Findings from the proposed study will provide important insights for biomedical engineers, computer scientists, social work practitioners, and health care providers to improve the quality of life for older adults and other age groups through the development of smart telehealth systems. Overall, the proposed study will improve the quality of life and independence of older adults by reducing morbidity and mortality from CVD and improve the cardiovascular health of older adults, which is also well aligned with the NIH’s mission.
