AI and Wearables That Help Detect Atrial Fibrillation in Patient Data
What is Atrial Fibrillation?
Atrial Fibrillation is a heart condition that causes irregular and often a fast heart rate. It’s unclear exactly what causes it, but we do know that it’s common in patients with other existing heart conditions.
How Are Wearables Helping with Detection?
On May 16, 2019, Preventice Solutions presented clinical data validating its BodyGuardian Remote Monitoring System with the BeatLogic deep learning platform at Heart Rhythm 2019 – the Heart Rhythm Society’s (HRS) 40th Annual Scientific Sessions in San Francisco.
This technology leverages machine learning and artificial intelligence (AI) for detection of atrial fibrillation (AF) and was validated using clinician adjudicated data. The system is designed to create a constant connection to monitor cardiovascular data in patients in their daily lives.
Today, AI, machine learning, and deep learning tools allow physicians to manage the massive amount of data produced on wearables and other sensor technology to track patient data, then diagnose health problems like AF, arrhythmia and hemodynamic instability.
What Does This Mean for Healthcare?
Without these AI technologies in healthcare, it would be impossible for physicians to manage and review the massive amounts of data collected on patients by wearables. With AI accurately identifying atrial fibrillation episodes, physicians can focus on the unique treatment for each patient.
Results from the study show how BeatLogic accurately detects the beginning and end of arrhythmias, ensuring accurate burden calculations while maximizing clinical value.
The platform leverages multiple deep neural networks to detect AF episodes at rates that meet or exceed the best reported values within the literature. Perfect detection performance was achieved for AF episodes lasting more than one minute.
Wearable patch electrocardiogram (ECG) monitoring devices combined with deep learning algorithms help detect the beginning and end of AF episodes, providing physicians with important clinical context for determining the appropriate treatment approach.