AI-powered algorithms in wearable defibrillators enhance accuracy in detecting life-threatening cardiac events, aiming to reduce false alarms and improve patient outcomes.

By Trevor Bromley

Artificial intelligence (AI) is changing the field of cardiac monitoring, offering new levels of precision for patients at risk of sudden cardiac arrest. By integrating artificial intelligence (AI) algorithms into wearable defibrillators, these devices can now provide more precise detection of cardiac events, helping to reduce the likelihood of unnecessary shocks and improving the overall reliability of the technology.

Wearable defibrillators equipped with AI-driven technology continuously monitor a patient’s heart rhythm through an electrocardiogram (ECG), which monitors the electrical signals from the heart. Unlike traditional devices that rely primarily on preset thresholds, advanced models utilize AI-based morphology analysis, analyzing the shape and structure of heartbeats, to better differentiate between shock-worthy and non-shock-worthy rhythms. This approach reduces the occurrence of false alarms, contributing to improved device performance and patient experience.

These highly effective AI models enable cardiology patients to live their daily lives without worry that a false shock will occur and, if a cardiac arrest does happen, that the wearable they have on will provide the necessary life-saving shock.

Constructing the AI

An important advancement in AI-driven devices is the adoption of explainable AI, which provides users with clearer insights into the decision-making process of the device.  

For example, a device like the Jewel Wearable Patch Defibrillator by Element Science provides access to heart waveform patterns leading up to rhythm classification to ensure clinicians understand the rationale behind each shock decision. This transparency allows for better-informed clinical decisions and a deeper understanding of patient data.

Instead of relying on rhythm classification gates by thresholds, as most available defibrillators on the market do, Jewel monitors an individual’s ECG continuously and in real-time, looking at morphology features and deciding whether a rhythm is indicative of a cardiac arrest.

The development of AI algorithms for wearable defibrillators involves close collaboration between clinicians, engineers, and data scientists. These multidisciplinary teams conduct extensive research and testing to refine the algorithms, ensuring they can accurately detect critical cardiac events while minimizing false positives. The machine learning process includes advanced signal processing techniques to filter out noise, enabling the device to focus on the most relevant cardiac data.

Brittany Bowers, algorithms and data systems engineer at Element Science, says, “By leveraging advanced machine learning-based algorithms, we’ve created a device that clinicians can trust to make critical decisions with accuracy, with the goal of ultimately improving patient outcomes and enhancing the overall effectiveness of wearable defibrillators.” 

Vice president of engineering Walt Stevens adds, “Our focus is on developing technology that delivers a new level of precision, ensuring patients receive the care they need when they need it.”  

As the device constantly monitors an individual’s ECG, it continuously collects heart rhythm data, which can help refine and improve future algorithms.

Learning from the User

As AI technologies continue to evolve, wearable defibrillators are expected to become even more precise and user-friendly. Future iterations of these devices will likely incorporate improvements that address various factors influencing patient compliance, such as comfort and ease of use, ultimately leading to better outcomes for those at risk of sudden cardiac arrest. 

Jewel clinical data already demonstrates significant protection time, as shown during a recent clinical trial.

AI helps to monitor and interpret the innate details of a patient’s heart rhythm signals and can better detect which features of the signals correlate with a lethal rhythm, essentially creating a binary classifier.

Future Iterations

As AI technologies continue to evolve, wearable defibrillators are expected to become even more precise and user-friendly. Future iterations of these devices will likely incorporate improvements that address various factors influencing patient compliance, such as comfort and ease of use, ultimately leading to better outcomes for those at risk of sudden cardiac arrest. 

With the implementation of AI, cardiac monitoring will continue to learn and improve over time so more individuals can benefit from this life-saving technology. 

AI In Healthcare Becoming A Focus in Higher Education

A growing number of prominent universities worldwide offer specialized courses, degrees, and research opportunities that focus on AI in healthcare. 

In the United States, leaders include Stanford, Harvard, MIT, and Johns Hopkins, which have variously developed AI courses relating to genomics, precision medicine, treatment plans, and medical imaging, developing smart medical devices and processing to name a few. 

In Europe, institutions including Oxford, Cambridge, Imperial College, and Technical College of Munich offer AI courses that explore applications in medical imaging, drug discovery, and a variety of diagnostics, informatics, bioinformatics, and personal medicine applications. They are joined by other institutions around the world, including National University of Singapore, Tsinghua University, Indian Institute of Technology, and McGill.  

Several now offer specific medical device AI curricula focused on medical device design, including AI components related to building and enhancing smart medical devices, AI in medical device design, including development of diagnostic devices, imaging systems, robotic surgery, and real-time monitoring tools and devices. Stanford’s Biomedical Informatics Program is pursuing AI applications in medical devices, including wearable technology, medical imaging systems, and diagnostic devices.

Photo caption: Jewel Wearable Patch Defibrillator by Element Science