Now, algorithm to identify cause of killer cardiac disease

Scientists have developed a novel non-invasive algorithm to identify the origin of irregular electrical 'storm waves' in the heart, an advance that may lead to treatment for the killer cardiac disease.
Atrial Fibrillation - one of the most common forms of abnormal heart rhythm - is caused by these waves, and is a major cause of stroke as it increases the risk of blood clots forming inside the heart.
Identifying the origin of atrial fibrillation is vital for its diagnosis and treatment.
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.

Researchers from the University of Manchester and University of Hull in the UK 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 method which can pin down the location of Atrial Fibrillation non-invasively, as well identifying different types of the condition.

"This technique can identify the origin of Atrial Fibrillation extremely effectively, which may provide a powerful tool for treatment in the future," said Professor Henggui Zhang, who led the study.

"This is very exciting research, which we think could lead to new developments to tackle heart problems more effectively and simply," said Zhang.
It occurs in about one to two per cent of people, and studies have shown that it is on the rise in the developed world due to our ageing population, researchers said.
The potential societal and economic implications of this increase highlight the urgent need for new and more effective treatment options for the condition, they said.
The research was published in the journal PLOS Computational Biology.