AI-Powered 'Smart Shirt' Could Revolutionize Hidden Heart Disorder Detection

AI-Powered 'Smart Shirt' Could Revolutionize Hidden Heart Disorder Detection

Mitchell Wilson
Mitchell Wilson
2 Min.
A man with a heart monitor on his chest, with a heart diagram and explanatory text on the left, and an image of a connected machine on the right.

AI-Powered 'Smart Shirt' Could Revolutionize Hidden Heart Disorder Detection

Researchers at Imperial College London have created an AI-powered 'smart shirt' to uncover hidden heart rhythm disorders. The wearable device, fitted with sensors, aims to detect rare conditions that often go unnoticed during short medical checks. Early trials suggest it could transform how doctors identify life-threatening heart problems in the future.

The smart shirt contains up to 50 sensors woven into its fabric. These sensors track the heart's electrical signals continuously, even during everyday activities. Unlike traditional tests, the device can monitor patients for a week or longer without disruption.

Scientists are training the AI system using ECG data from over 1,000 people. The goal is to teach the algorithms to spot abnormal patterns linked to rare disorders. Among the conditions it targets are Long QT Syndrome (LQTS), Brugada Syndrome, and Catecholaminergic Polymorphic Ventricular Tachycardia (CPVT).

A three-month trial will soon begin with 200 patients and volunteers. Researchers will assess how accurately the shirt diagnoses these disorders. If successful, the technology could also be adapted to detect atrial fibrillation in the future.

In the UK, around 340,000 people live with undiagnosed heart rhythm disorders. Each week, up to 12 young people under 35 die from sudden cardiac events caused by these conditions. The smart shirt aims to reduce such deaths by catching problems early.

The smart shirt is expected to enter clinical use within five years. Once available, it could provide a non-invasive way to monitor high-risk patients over extended periods. Doctors hope the device will improve early detection and save lives by identifying disorders that often remain hidden.

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