ECG-X: Making ECGs explainable with colour to support early detection of life-threatening heart conditions

"In a busy hospital, a junior A&E doctor is learning to interpret ECGs. Where once she would have been counting tiny squares and trying to manually determine the beginning and end of waves using trigonometry - for example drawing tangents - on a paper printout, instead she is exploring the data on an iPad, changing the axes and orientation of the ECG, applying colour to the area under the curve and zooming in to understand details of the signal. The visualisation tool she uses to understand the data also supports her in another way: providing an automated estimation of the likelihood of the conditions she is investigating, explaining in natural language how it has come to its judgement. Because the automated interpretation uses 'cognitive fit' - where the human and the machine share the same representation of the data - it is intuitively understandable, and easy to check and explore. In this case, the fit is provided by the visual presentation of the ECG data. The techniques that support human interpretation, which combine pre-attentive processing to highlight anomalies in the signal with clinical knowledge to ensure reliability and accuracy, are also used as the basis for the machine interpretation."

"A patient has started taking a new medication for cancer treatment. He hasn't noticed it causing any side effects, but his smart watch has alerted him that the electrical activity of his heart may have changed, and advises him to consult a clinician urgently. He shows the data to his doctor in an emergency consultation, and has his medication changed. His heart activity soon returns to normal."

The scenarios above show the transformation our research aims to achieve - moving from difficult manual interpretation of ECGs by experts, to self-monitoring at home to detect conditions that may lead to sudden cardiac death.

The Electrocardiogram (ECG) is a graphical representation of the heart's electrical activity that is widely used in clinical practice for detecting...