NIT Rourkela’S New ECG Lead System To Boost Diagnosis Of Abnormal Heart Rhythms
ECG is one of the most commonly used techniques to monitor heart activity.
The novel lead placement system called the Atrial Lead System (ALS) helps in easily detecting subtle electrical signals from the upper chambers of the heart, which are often too indistinct to be seen clearly in regular ECGs. These signals play a key role in identifying abnormal heart rhythms -- responsible for a large number of cardiac-related deaths around the world.
Irregular heart rhythms in the heart's upper chambers, known as atrial arrhythmias, are among the most common, especially in patients who have been hospitalised. Identifying these arrhythmias in the early stages can help doctors begin timely treatment and prevent complications.
An ECG records the electrical activity of the heart using electrodes placed on the body. In an ECG, doctors check the 'P-wave', which reflects the electrical activity in the upper chambers of the heart. However, P-waves are often small and easily lost in background noise making it difficult to detect atrial arrhythmias.
The ALS uses a modified arrangement to improve how electrical activity from the atria is recorded. By strengthening these signals, especially the P-wave, the system helps improve the accuracy of arrhythmia detection, both by doctors and by computer-based diagnostic tools.
“We introduced novel electrode placements that significantly increased the visibility of atrial activity on ECG readings. The improved signal clarity allows for quicker analysis and better clinical decision-making,” said Dr. J. Sivaraman, Research lead, and Assistant Professor at the the Department of Biotechnology and Medical Engineering, at NIT Rourkela
Importantly, the new system requires no change to the ECG machine itself. The innovation lies entirely in the way the leads are placed, which means the upgrade can be easily adopted in both public and private healthcare settings without additional cost.
The findings are published in international journals including Biomedical Signal Processing and Control, Medical Hypotheses, and Physical and Engineering Sciences in Medicine.

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