Our Bureau
Boulder, CO
In a major leap for preventive cardiac care, Dr. Pratibha Sharma, a pioneer in biomedical signal processing, has developed a novel method using wavelet transforms to detect the early shift from stable to unstable stages in patients suffering from congestive heart failure (CHF)—a change that can be fatal if not recognized early.
With over 6 million Americans living with heart failure, and more than 1 million hospitalizations per year, early intervention is critical. Yet many patients deteriorate silently. Dr. Sharma’s work empowers clinicians with a predictive tool to detect this transition before symptoms escalate.
“We’re essentially teaching machines how to listen to the heart in a more intelligent way,” said Dr. Sharma. “Wavelet transforms help us detect micro-patterns in heart electrical signals—tiny red flags that appear before patients feel unwell.”
Her approach, which analyzes ECG signals using advanced mathematical modeling, is now being considered for integration into wearable technologies and remote monitoring systems, marking a shift toward smarter, more proactive care.
Many leading experts and US cardiologists lauded the development of its path-breaking technology.
“A Game Changer for Heart Failure Management,” says Dr. Ranjita Sengupta, MD, FACC, Assistant Dr.essor at Robert Wood Johnson Medical School and practicing cardiologist at Cardiology Associates of Somerset County.
Dr. Sengupta praised the research and said, “Dr. Sharma’s work is not just academically brilliant—it’s clinically vital. Heart failure is a progressive disease, and recognizing the decompensated phase early can significantly reduce mortality and readmission rates. A tool that enhances remote detection could be transformative, especially for Medicare and VA patients.”
“We’ve Been Waiting for Technology Like This,” says Dr. Meherwan Burzor Joshi, MD, Associate Dr.essor of Cardiology at Rutgers University of Health Sciences.
Dr. Burzor emphasized the utility for high-risk populations and said, “Many heart failure patients don’t live near advanced care centers. Having a wearable or home-monitoring system that leverages wavelet-based ECG analysis could drastically improve outcomes for underserved populations. Dr. Sharma’s research fills a critical gap in digital cardiovascular diagnostics.”
“This Represents the Future of Cardiac AI,” says Dr. Raj Khandwalla, MD, Director of Digital Therapeutics at Cedars-Sinai’s Smidt Heart Institute in Beverly Hills.
Dr. Khandwalla added and said, “As someone focused on merging cardiology and technology, I’m excited by this development. Wavelet-based signal analysis has been underutilized in clinical applications. Dr. Sharma’s ability to extract actionable insights from subtle changes in ECG is cutting-edge. It’s precisely the kind of innovation that AI-driven healthcare needs.”
This technology is crucial as Dr. Sharma’s work directly supports U.S. public health priorities:
● Reduces hospital admissions and costs tied to CHF
● Enables remote and preventive care in rural, underserved, and aging populations
● Integrates seamlessly with AI and wearable health tech
● Helps meet federal targets on chronic disease prevention and smart healthcare
Dr. Pratibha Sharma is a global expert in biomedical engineering, focusing on real-world solutions that merge mathematics, medicine, and machine learning. Her research has been cited internationally and has the potential to reshape how cardiac care is delivered across the world—including here in the US.
