AI foot scanner predicts heart failure 13 days earlier
Surprising research presented at the British Cardiovascular Society conference in June 2025 revealed the fascinating capabilities of an AI-powered foot scanner that can predict worsening heart failure an average of 13 days earlier than conventional methods. This technology, developed by Cambridge start-up Heartfelt Technologies and tested as part of the FOOT study across five healthcare facilities, represents an important step forward in home care for patients with heart failure and could dramatically reduce the number of unplanned hospital admissions.
Technical capabilities and operation of the device
The AI foot scanner is a compact device about the size of a smart speaker that is typically mounted on the wall by the patient’s bed. The technology uses advanced recognition algorithms similar to facial identification systems, which have been adapted to analyze the lower limbs. The device can capture an impressive 1,800 to 2,000 images per minute from different angles and can scan up to a height of 50 centimeters above the floor, enabling detailed imaging of the entire foot and ankle area.
The scanner’s key function is the detection of edema, or swelling caused by fluid retention in the tissues, which is one of the three main warning signs of worsening heart failure, along with weight gain and increased shortness of breath. The artificial intelligence system analyzes the captured images and calculates fluid levels in the tissues. If worsening swelling is detected, the device can immediately alert the healthcare team caring for the cardiac patient, enabling rapid intervention through medication adjustments or other therapeutic measures before the condition acutely deteriorates and requires hospitalization.
Results of the FOOT study
The FOOT study, which monitored 26 patients with heart failure across five healthcare facilities between 2020 and 2022, provided compelling evidence of the technology’s effectiveness. During the study, patients used not only the AI foot scanner but also Bluetooth scales to monitor their weight. The results showed that the scanner was able to identify worsening edema an average of 13 days before hospitalization would otherwise have been necessary. An exceptionally important feature of the device is its ability to operate without a WiFi connection, making it suitable for a wide range of home environments and increasing its accessibility to patients in different social and geographical circumstances.
Professor Bryan Williams, Chief Scientific and Medical Officer of the British Heart Foundation, emphasized in his comments that the study demonstrates how simple technology can enable earlier intervention and potentially reduce hospital admissions while improving patient outcomes. This assessment is particularly significant in the context of more than one million UK patients living with heart failure, for whom this technology could represent a fundamental improvement in quality of life.
NHS context and future implications for healthcare
The FOOT study is part of ongoing NHS (National Health Service) research supported by the British Heart Foundation and involving several NHS facilities. The National Institute for Health and Care Research (NIHR) is actively involved in related studies focused on AI-driven risk prediction, although not all proposed projects receive funding. This technology highlights the growing role of artificial intelligence and remote monitoring in the NHS care system and demonstrates the potential of scalable, non-invasive solutions for home monitoring.
The clinical impact of this innovation is potentially enormous, as early detection of worsening heart failure symptoms in the home can enable rapid treatment adjustments, thereby reducing emergency hospital admissions and improving patients’ quality of life. The 2025 study clearly demonstrates that an AI-powered foot scanner can reliably detect early signs of worsening heart failure, providing NHS patients and clinicians with a valuable tool for preventing hospital admissions through timely intervention.
This technology represents a significant advance in personalized medicine and indicates the direction that future healthcare is likely to take - toward proactive, home-based monitoring using artificial intelligence to detect health problems early, before they acutely worsen.
