Your next heart test could start with a T‑shirt: Imperial College develops AI‑powered smart T‑shirt to spot hidden heart risks
Researchers at Imperial College London are creating an AI‑powered smart T‑shirt for continuous ECG monitoring to detect inherited rhythm disorders missed by brief clinic ECGs, offering a comfortable, long‑term option funded by the British Heart Foundation.
- Continuous, comfortable monitoring: a washable sportswear T‑shirt with up to 50 woven ECG‑style sensors for days‑to‑weeks recording.
- AI analysis: algorithm trained on ECG data to separate normal variation from signals tied to inherited rhythm disorders (AI training).
- Early trials and funding: >£340,000 from the British Heart Foundation and a planned 200‑person feasibility study at Hammersmith Hospital.
- Real‑world potential: could reach clinical practice in roughly five years if trials and regulators approve, but data security and independent validation remain critical.
Why the smart T‑shirt is being developed
Standard electrocardiograms (ECGs) taken for minutes in clinics provide a useful snapshot but can miss intermittent, inherited rhythm disorders that lie silent until they cause sudden cardiac events. Extended monitoring can reveal patterns a single clinic ECG might miss and may change outcomes, particularly for younger people who otherwise appear healthy. The Imperial team and the British Heart Foundation emphasise that longer recording windows improve detection.
How the device works
The garment uses flexible sportswear fabric with up to 50 ECG‑style sensors woven into it. The design looks and feels like everyday sportswear so people can wear it under clothes, sleep in it and wash it. The shirt collects continuous electrical heart signals over days or weeks, and a connected system stores the large data volume for AI analysis.
Comfort and practicality: the goal is improved adherence versus adhesive electrode systems and waist‑worn recorders, enabling long‑term, real‑life monitoring during ordinary activities.
AI training and the data behind it
Developers trained the algorithm on ECG data from more than 1,000 people, including both patients with known inherited heart rhythm disorders and people without these conditions. That diversity helps the AI distinguish normal variation from concerning signals and aims to reduce false positives in everyday settings (training dataset details).
What the trial will test
An initial feasibility study at Hammersmith Hospital’s Peart‑Rose Research Unit will enrol about 200 volunteers. Participants will wear the shirt continuously for up to three months so researchers can assess detection of abnormal rhythms during normal life. The trial begins with adults; if successful, researchers plan adaptation for children and exploration of detecting other conditions such as atrial fibrillation.
Clinical adoption will depend on rigorous trials and regulatory sign‑off.
Voices from the project
“Far too many people die from inherited heart conditions which could be treated if they were identified earlier… We hope our AI‑assisted t‑shirt will provide a practical and comfortable solution.”
— Professor Zachary Whinnett, project lead at Imperial College London’s National Heart and Lung Institute
“This innovative research will leverage the power of AI to help clinicians unmask these hidden conditions and identify patients at risk of sudden death.”
— Professor James Leiper, British Heart Foundation
Potential benefits and practical limits
Benefits: long‑term monitoring could uncover intermittent abnormalities missed by short ECGs, enabling earlier treatment, targeted follow‑up testing and potentially reducing emergency admissions. The shirt’s washability and sportswear look may improve compliance compared with adhesive electrode systems.
Limits and open questions: the project is early — the system must demonstrate accuracy and safety in real‑world conditions and clear regulatory review. There are broader concerns about data security, ownership of heart data, and how results would be shared with patients, providers and insurers. Independent validation remains crucial (external reporting).
Funding and support
The project received a grant of more than £340,000 from the British Heart Foundation and support from the NIHR Imperial Biomedical Research Centre. That initial funding covers development and the planned feasibility study; wider deployment will require more investment and demonstration of clinical benefit.
Implications for Walla Walla, Washington
Economic impact: wearable monitoring could lower long‑term costs by catching dangerous conditions before emergency care is needed and reduce expensive hospital stays. Rural hospitals and clinics in Walla Walla could use remote monitoring to serve patients more efficiently, though adoption will depend on device cost, insurance coverage and local budgets.
Political consequences: local policymakers will face questions on telehealth funding, reimbursement and data privacy. Stakeholders who prioritise fiscal responsibility may welcome tools that reduce ER strain, but will expect clear payment and privacy rules.
Social and cultural effects: a comfortable, washable T‑shirt may appeal to families, older residents, outdoor workers and local athletes in Walla Walla — fitting a culture of self‑reliance and practical solutions. Clinicians would need training to interpret long‑form ECG reports and integrate results with telemedicine workflows.
What to watch next
The immediate milestone is the Hammersmith feasibility study results, which will show the garment’s ability to detect intermittent problems in everyday life. Regulators, independent researchers and patient advocates will scrutinise safety, accuracy, data handling and cost. If trials succeed, researchers estimate a path to clinics in roughly five years, pending further testing and approvals (timeline and context).
