This new method may help improve treatment for irregular heart rate

London: Researchers have developed a new method that may help improve the treatment for irregular heart rate.

This new algorithm will identify the origin of irregular electrical 'storm waves' in the heart, a finding with major implications for the future treatment of a killer cardiac disease.

Atrial Fibrillation is one of the most common forms of abnormal heart rhythm. It is caused by these waves and is a major cause of stroke as it increases the risk of blood clots forming inside the heart.

Current methods involve the use of a catheter to isolate the storm waves. However, this is very invasive surgery and it is extremely difficult to identify the origin of the waves in order to treat the condition, said researchers from UK's University of Manchester.

For the study, researchers used a virtual human heart-torso and a 64-lead electrocardiogram (ECG) vest to study the correlation between the origin of the storm waves and the features of the ECG signals.

Using the properties of the atrial activation and the signals, they were able to develop a novel algorithm which could pin down the location of Atrial Fibrillation non-invasively, as well identifying different types of the condition.

Lead author Henggui Zhang, Professor at University of Manchester, "This technique can identify the origin of Atrial Fibrillation extremely effectively, which may provide a powerful tool for treatment in the future".

Zhang added, "The research, could lead to new developments to tackle heart problems more effectively and simply".

Atrial tachy-arrhythmias, including atrial fibrillation (AF), atrial tachycardia (AT) and flutter (AFL), are the most common cardiac arrhythmias, predisposing to heart attack, stroke and even possible cardiac death.

Atrial fibrillation presents the greatest complexity and occurs in about 1-2 per cent of people and studies have shown that it is on the rise in the developed world due to the ageing population.

The findings was published in ther journal PLOS Computational Biology,

(With IANS inputs)