Novel Algorithm can Non-invasively Localize Source of Heart Conditions

Novel Algorithm can Non-invasively Localize Source of Heart Conditions

by Dr. Lakshmi Venkataraman on Oct 17 2018 6:13 PM
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  • Currently, doctors use invasive electrical procedures to diagnose and localize the source of abnormal heart beats such as atrial fibrillation
  • Using signals produced externally at the body surface by the electrical activity of heart (measured as electrocardiogram), scientists have developed a method to reconstruct what is happening deep within the heart
  • In future, it may be possible to diagnose and assess response to treatment of cardiac conditions using this non-invasive cardiac imaging algorithm
A new non-invasive algorithm has been developed to diagnose and localize the origin of atrial fibrillation, a type of rhythm disturbance of the heart where the heart beats very fast and the patient is able to sense the rapidly beating heart as palpitations. The research work was conducted by a team from the University of California, Santa Barbara. The findings appear in the journal APL Bioengineering, from AIP Publishing.
"Using heart signals produced at the body surface, we can try to reconstruct what's going on inside your heart," said UC Santa Barbara graduate student Abhejit Rajagopal, an author on the paper . "This is typically done by simulating a model for the propagation of signals from your heart to the surface and inverting it. The 'inverted' model is known as an inverse operator. Typically, if the forward model is linear so is the inverse operator."


Reconstructing Heart Electrical Activity Using Inverse Operator Model

The main aim of noninvasive electrical imaging of the heart is to accurately reconstruct information about the electrical activity of the heart from numerous ECG impulses on the surface of the chest. Quantitative interpretation of these superficial signals in the context of the underlying cardiac electrical activity is an inverse mathematical problem and the current study is one of the many algorithms that have been developed to solve it

As stated above, the basic concept employed by the UC Santa Barbara group's work is that the inverse operator, (a mathematical function that maps body-surface ECG signals to electrical potentials in the innermost layer of the heart), can also be expressed in a non-linear fashion and optimized by adding patient-specific parameters

By carefully including more parameters, presumed models of body tissue can be optimized by actual patient data to provide more precise reconstructions of endocardial potentials.

“This enables development of models for predicting cardiac potentials that are accurate and realistic from electrocardiograms, and may be used as a new cardiac imaging tool," said Rajagopal.


Applications of the Inverse Operator Model

  • Someday, instead of a doctor listening to the heart using a stethoscope, they may be able to see a live video of the heart activity via ultrasound with corresponding measurements of local electrical potentials around the heart. This technology will enable doctors to diagnose and treat patients with various heart conditions without the need to perform invasive surgeries just to determine the cause of the problem
  • In some cases of atrial fibrillation, it may be possible to localize the origin of the abnormal rhythm and determine whether surgery is recommended for the patient.
"A lot of work remains to be done before we can make this a reality," he said. "But our work is a good step in that direction, since it shows that the resolution of the noninvasive reconstruction can be sufficiently high to aid in diagnosis and prognosis of such cardiac disorders."



The current research is significant because it shows that that much higher resolution of the tissues is possible if nonlinear reconstruction algorithms are employed using a few extended data, compared with what is described theoretically using linear methods and partial data.

Rajagopal said, "We were surprised that we didn't need to explode the number of parameters allowed in the reconstruction. By adding just a few extra parameters -- while still respecting the structure of the original reconstruction algorithm -- we found that high-accuracy reconstruction is possible."

  1. Noninvasive reconstruction of cardiac electrical activity: update on current methods, applications and challenges - (
  2. Nonlinear electrocardiographic imaging using polynomial approximation networks - (


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