Non-invasive hemodynamic sensor patch for remote, early detection and prevention of heart failure with left bundle branch block

1 Project Abstract2 The long-term goal of this SBIR is to develop a remote, non-invasive early-warning system for heart3 failure progression in presymptomatic patients at elevated risk of developing heart failure. The early-warning4 system consists of a wireless sensor patch worn periodically by patients at home that diagnoses cardiac5 hemodynamics and electrophysiology to notify cardiologists of patients whose ventricular function is worsening6 and may benefit from early intervention. Currently there are no validated remote monitoring approaches for early7 detection of heart failure. Consequently, treatment guidelines restrict most invasive heart failure interventions8 (e.g. implantation of a pacemaker or defibrillator) to patients suffering from later-stage heart failure where some9 degree of symptoms may be irreversible. The need for early detection in heart failure is critical, as heart failure 10 is the leading cause of hospitalizations in adults over 65 years old and among the leading causes of mortality. 11 The proposed technology will aid early detection, prevention, and treatment of heart failure patients so 12 they can live longer, more fulfilling lives. Specific hemodynamic changes are known to be predictive of heart 13 failure outcomes, but current technologies used to diagnose cardiac hemodynamics are resource intensive 14 clinical methods like echocardiography or non-specific remote sensors like scales which only measure symptoms 15 of heart failure and not the underlying function of the heart. This SBIR will develop an unobtrusive hemodynamic 16 patch and automated analysis algorithm to monitor signals specific to the etiology of heart failure that are 17 predictive of disease progression. The proposed solution changes the diagnostic paradigm in 3 specific ways: 18 passive measurement of multiple hemodynamic-specific variables, direct integration into remote monitoring 19 workflows, and ease of use to support more efficient chronic care delivery (e.g. telemedicine). 20 Aim 1 will evaluate the accuracy and precision of the patch versus clinical standard devices like 21 echocardiography, electrocardiography, and blood pressure cuffs. This Aim will validate that the sensor can 22 reliably measure hemodynamic and electrophysiological signals at clinical grade accuracy. It will also investigate 23 the sensitivity of the data collected to patch placement and body composition variability. Aim 2 will investigate 24 cardiac physiological changes associated with heart failure progression in patients with left bundle branch block 25 (LBBB), a cardiac conduction disorder associated with increased risk of developing heart failure. To achieve this, 26 LBBB patients at various disease stages will sleep while wearing the wireless patch. Then, physiological signal 27 changes associated with disease stage will be identified. Successful completion of Phase I will validate technical 28 feasibility of a non-invasive sensor capable of identifying upstream physiological changes predictive of heart 29 failure. The work also has broader applications to improve health and gain fundamental knowledge by elucidating 30 specific progressive hemodynamic changes associated with LBBB-driven dysfunction and by introducing a non- 31 invasive hemodynamic remote monitoring platform to empower future longitudinal cardiovascular studies.Project Narrative This project is relevant to the 6 million people suffering from heart failure in the United States. The goal of this project is to build and test a wireless sensor patch periodically worn at home by people who are at an elevated risk of developing heart failure due to left bundle branch block to diagnose changes in the way the heart contracts to predict disease progression. The long-term goal is to create a cost-effective, non-invasive technique to detect heart failure progression and identify patients who will benefit from early treatment before severe heart failure symptoms occur.