An App to Detect Heart Attacks and Strokes - and Save Lives

A potentially lifesaving new smartphone app can help people determine if they are suffering heart attacks or strokes and should seek medical attention, a clinical study suggests.

The ECHAS app (Emergency Call for Heart Attack and Stroke) is being developed by experts at UVA Health, Harvard, Northeastern and other leading institutions. It is designed to help people recognize the signs of cardiac and neurological emergencies so that they get care as quickly as possible, for the best possible outcomes.

Put to the test in an initial clinical study with more than 200 real-life emergency-room patients, the app proved effective at identifying people suffering strokes or heart attacks. It had a "high sensitivity" the researchers report, for detecting people who needed emergency care and was rated "highly usable," suggesting it could be an easy and effective resource for people untrained to recognize the signs of a potentially devastating health emergency.

"Heart attack and stroke are two leading causes of death in Virginia and the U.S. Our study found that the ECHAS app could accurately identify patients with heart attack, stroke and other emergency brain or heart problems who needed evaluation in the emergency room or admission to the hospital," said UVA Health neurologist Jonathan R. Crowe, MD, MPH, one of the study's authors. "We hope ECHAS could help save lives by reducing delay and helping patients get the heart attack and stroke care they need."

When it comes to strokes and heart attacks, time is of the essence. Doctors consider the first 60 minutes after a stroke or heart attack the "golden hour" because that is when medical treatments are the most effective. Waiting can have grave, long-term consequences - more than half of stroke deaths, for example, occur before patients even reach the hospital. And those who do survive can be left with life-changing disabilities. Yet many people hesitate to seek care because they are uncertain if they're really suffering a medical emergency.

That's where ECHAS would come in. The app is based on the same questions doctors ask when patients arrive at the emergency room; it also includes a finger-tapping test that can detect weakness on one side of the body. After users complete their virtual exam, the app calculates a risk score and advises whether to call 911, call a medical hotline or contact their doctor or other care provider.

In the app's initial clinical trial, 202 emergency room patients were asked to use the app after they had been seen and stabilized. Of these patients, 57 were suffering stroke symptoms and 145 were suffering heart attack symptoms. The average age of the participants was 62; most were white and 126 were men.

The app proved 100% effective at identifying patients who would ultimately be admitted to the hospital after their emergency evaluation. The app was also fast, detecting strokes in less than two minutes and heart attacks in only one. "In heart attack and stroke care, time can make the difference between life and death," said Crowe, who is also part of the University of Virginia School of Medicine's Department of Public Health Sciences. "We need solutions like ECHAS that are accurate, fast and easy to use."

The app is not yet available, and the researchers say further testing in larger trials is needed. But they are pleased about the promise their app has displayed in its first test-run.

"At UVA, we have partnered with UVA’s Center for Telehealth to apply for a grant to study ECHAS here in Virginia," Crowe said. "We want people in Virginia and around the world to be able to use their smartphones and tablets to reduce delay and help them get the care they need, especially in medical emergencies."

Dhand A, Mangipudi R, Varshney AS, Crowe JR, Ford AL, Sweitzer NK, Shin M, Tate S, Haddad H, Kelly ME, Muller J, Shavadia JS.
Assessment of the Sensitivity of a Smartphone App to Assist Patients in the Identification of Stroke and Myocardial Infarction: Cross-Sectional Study.
JMIR Form Res. 2025 Mar 3;9:e60465. doi: 10.2196/60465

Most Popular Now

AI Catches One-Third of Interval Breast …

An AI algorithm for breast cancer screening has potential to enhance the performance of digital breast tomosynthesis (DBT), reducing interval cancers by up to one-third, according to a study published...

Great plan: Now We need to Get Real abou…

The government's big plan for the 10 Year Health Plan for the NHS laid out a big role for delivery. However, the Highland Marketing advisory board felt the missing implementation...

Researchers Create 'Virtual Scienti…

There may be a new artificial intelligence-driven tool to turbocharge scientific discovery: virtual labs. Modeled after a well-established Stanford School of Medicine research group, the virtual lab is complete with an...

From WebMD to AI Chatbots: How Innovatio…

A new research article published in the Journal of Participatory Medicine unveils how successive waves of digital technology innovation have empowered patients, fostering a more collaborative and responsive health care...

New AI Tool Accelerates mRNA-Based Treat…

A new artificial intelligence (AI) model can improve the process of drug and vaccine discovery by predicting how efficiently specific mRNA sequences will produce proteins, both generally and in various...

Can Amazon Alexa or Google Home Help Det…

Computer scientists at the University of Rochester have developed an AI-powered, speech-based screening tool that can help people assess whether they are showing signs of Parkinson’s disease, the fastest growing...

AI also Assesses Dutch Mammograms Better…

AI is detecting tumors more often and earlier in the Dutch breast cancer screening program. Those tumors can then be treated at an earlier stage. This has been demonstrated by...

RSNA AI Challenge Models can Independent…

Algorithms submitted for an AI Challenge hosted by the Radiological Society of North America (RSNA) have shown excellent performance for detecting breast cancers on mammography images, increasing screening sensitivity while...

AI could Help Emergency Rooms Predict Ad…

Artificial intelligence (AI) can help emergency department (ED) teams better anticipate which patients will need hospital admission, hours earlier than is currently possible, according to a multi-hospital study by the...

Head-to-Head Against AI, Pharmacy Studen…

Students pursuing a Doctor of Pharmacy degree routinely take - and pass - rigorous exams to prove competency in several areas. Can ChatGPT accurately answer the same questions? A new...

NHS Active 10 Walking Tracker Users are …

Users of the NHS Active 10 app, designed to encourage people to become more active, immediately increased their amount of brisk and non-brisk walking upon using the app, according to...

The Human Touch of Doctors will Still be…

AI-based medicine will revolutionise care including for Alzheimer’s and diabetes, predicts a technology expert, but it must be accessible to all patients. Healing with Artificial Intelligence, written by technology expert Daniele...