Researcher wins award to study irregular heartbeat

Behnaz Ghoraani’s work in signal processing targets irregular heartbeats that can lead to stroke

Behnaz Ghoraani

Behnaz Ghoraani, engineering faculty at Rochester Institute of Technology, was recently awarded a $456,000 grant from the National Institutes for Health for the project “Catheter guidance algorithm for identification of atrial fibrillation ablation.”

According to the American Heart Association, atrial fibrillation, a heart rhythm disorder, affects more than 2 million Americans. These fluctuations in the heart can cause increased risk of stroke and heart failure. Electrical signals within the body drive the mechanical movement of the heart. Atrial fibrillation is an irregularity of the heart rate, specifically within the atria, the two upper chambers of the heart, due to a disturbance in the electrical activity.

Ghoraani and her research team are developing a novel low-risk, low-cost algorithm allowing improved and patient-specific localization of electrical disturbance sites to improve clinical intervention for atrial fibrillation.

Clinicians and electro-physiologists access the atria using a catheter, a process called atrial fibrillation ablation, isolating the atria from the pulmonary veins as a means to stabilize the electrical activity.

“This will help the doctors to better target the problem,” said Ghoraani, an assistant professor of biomedical engineering in RIT’s Kate Gleason College of Engineering. “The developed algorithm is going to help them attempt to better ‘see’ what is going on in the atrium—more than sensing the electrical signals in the heart, but analyzing it. This technology is about guiding the clinicians to where they need to sense in the atria, by analyzing the patterns of the electrical signals in the atria.”

Ghoraani has done extensive work in the area of developing signal and image processing techniques to characterize the human atrial fibrillation mechanism, in addition to developing signal analysis algorithms for electrocardiogram, electroencephalogram, audio and speech data.

Through signal analysis and pattern recognition techniques, Ghoraani has been able to find patterns that can guide researchers toward the disturbance source, and this will be the basis of the research team’s diagnostic application. She is collaborating with Elizabeth Cherry, associate professor in RIT’s School of Mathematical Sciences, as well as clinicians at the University of Rochester Medical Center, electro-physiologists and scientists at SUNY Upstate Medical University in Syracuse, N.Y.

The team is developing the algorithm building upon clinical data collected from an early project through Toronto General Hospital where Ghoraani was a post-doctoral Fellow. She found evidence of patterns of atrial fibrillation in the intra-cardiac signal, and the preliminary data is being used to establish the algorithm for this latest project.

“The human body is a source of information and it is communicating with us. We have to translate it in a way that we can better use that information,” she said, “with many scientists looking at possible solutions, and trying to tackle it from different angles. It is very hard to access this data because it is so dynamic, that’s kind of the challenge we are facing. We are combining information and trying to understand the clinical problem through engineering and mathematics. I think that is the interesting side of this project.”


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