Smart T-Shirt Uses AI to Enhance Detection of Heart Rhythm Disorders

As a result, delayed diagnosis increases the likelihood of sudden cardiac death, particularly in young people. To address this gap, researchers have developed a wearable system designed to extend cardiac monitoring into daily life and improve diagnostic yield. The artificial intelligence (AI)–enabled smart T-shirt aims to identify inherited conditions such as Brugada syndrome earlier and more consistently.

Developed at Imperial College London with clinical input from Imperial College Healthcare NHS Trust and supported by the British Heart Foundation, the AI-enabled smart T‑shirt targets rare, inherited heart conditions. The initiative has been awarded more than £340,000 to advance development. It is intended to be worn during normal activities, providing longer monitoring windows than standard devices.

The garment integrates up to 50 sensors stitched into the fabric to mirror a clinical electrocardiogram (ECG). Conductive wiring embedded within the material captures electrical signals while the T‑shirt is worn under clothing. This design seeks to overcome limitations of portable ECGs that rely on precisely positioned sticky electrodes connected to a waist‑worn monitor, which patients must remove and reattach for activities like showering.

The research team will train the AI algorithm on data from more than 1,000 people, including individuals with inherited rhythm disorders and controls, to teach the model to recognize abnormal ECG patterns. A total of 200 patients and volunteers attending Hammersmith Hospital’s Peart‑Rose Research Unit, part of Imperial College Healthcare NHS Trust, will receive the T‑shirt. Participants will wear it continuously for up to three months to assess how effectively it detects serious heart conditions.

Early detection is critical for conditions such as of  Brugada syndrome because untreated cases increase the risk of sudden cardiac death. An estimated 340,000 people in the United Kingdom live with an inherited heart condition, and these disorders are estimated to claim the lives of 12 people under age 35 each week. Diagnosing in hospital can be challenging because heart rhythm tests and scans may appear normal, so the team plans adult development first, with future aims that include pediatric use and potential application to atrial fibrillation, and they hope clinicians could use the technology in roughly five years.

 “Far too many people die from inherited heart conditions which could be treated if they were identified earlier. One of the challenges of diagnosis today is that irregular heart rhythms may not always occur during routine 10- minute hospital ECGs or even 48-hour ECG monitoring at home,” said professor Zachary Whinnett, Professor of Cardiology at Imperial College London, who is leading the project. “We hope our AI-assisted t-shirt will provide a practical and comfortable solution, allowing us to carry out longer-term scanning that could improve diagnosis.” 

Related Links
Imperial College London
British Heart Foundation