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A glowing model of a heart on a dark background with charts and tables.

BeatLogic™ cardiac algorithm

The BodyGuardian™ remote cardiac monitor system incorporates AI for superior data annotation of electrocardiographic monitoring.

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Advanced arrhythmia detection and identification 

BeatLogic is a cloud-based ECG analysis platform that leverages artificial intelligence (AI) algorithms and deep learning to automate ECG interpretation and increase diagnostic yield. The platform delivers timely, accurate reports and critical notifications to help you optimize therapies and improve patient outcomes.

Four circles showing >99.7% beat detection, >97% sinus sensitivity, >97% VT sensitivity, and >96% AFib sensitivity.

Why is AI so powerful?

Graph inidcating deep learning increases with performance and amount of data, more than classic machine learning does.
  • Using AI empowers clinicians with more accurate ECG data enabling more accurate ECG analysis

  • Because AI leverages computation but learns like humans, it can be trained through trial-and-error on thousands or millions of ECG recordings, providing the algorithm with a lifetime of training in only a few hours

  • Like with human learning, more training makes for better decision making

Funnel representing millions of minutes of ECG being processed per day using the BeatLogic cardiac algorithm.

BeatLogic
Automated interpretation is performed using BeatLogic. All data is available to the physician and clinically notable events (minute-long strips) are passed downstream.

Rate Limiter
For individual patients, rate limiting removes duplicate events but lets higher acuity events through. The remaining events are passed downstream.

Event Triage
Certified ECG technicians use custom tooling to evaluate events based on physician provided rhythm thresholds. Events selected for reporting are passed downstream.

Report Builds
Certified ECG technicians adjudicate events and build event reports, which are delivered to physicians.

Notification
Events that meet specified criteria require specially trained technicians to contact and notify the physician directly.


State-of-the-art AI

BeatLogic offers built-in deep learning and best-in-class algorithms across single and multi-channel ambulatory monitors.


What clinicians are saying about our AI

Dr. Hamid Ghanbari

“This analysis continues to validate that it is feasible to train the deep learning models to closely monitor and interpret multiple levels of signals with a high level of reliability. Most important, this allows physicians to effectively utilize the volumes of data to guide their care and allow them to spend more time focusing on the patient.” 

Hamid Ghanbari, MD, MPH, FACC
Cardiac Assistant Professor University of Michigan
Electrophysiology Services

Publications about BeatLogic

Deep learning for automated QTc measurement

BeatLogic empowers physicians to efficiently and effectively take action to treat prolongs QT which can be related to increased risk of developing dangerous arrhythmias. An analysis presented at ACC 2024 found the BeatLogic algorithm:

  • Provides accurate QTc measurement over a patient’s entire ECG study

  • Identifies possible Long-QT cases with excellent sensitivity

  • Overcomes challenges of manual QT measurements on real-world ambulatory ECG data

Deep learning for automated QTc measurement poster.

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Additional publications

Deep learning for comprehensive ECG annotation

The BeatLogic algorithm advances state-of-the-art performance for ECG analysis on real-world data. Multiple specialized deep learning models work in concert to accurately identify and classify beats and rhythms from raw ECG data.


Deep learning for ECG waveform segmentation

BeatLogic finds and measures each waveform within individual heartbeats, laying the foundation for accurate and automated analysis of wave internal timings such as PR and QT intervals.


Fully-automated ventricular ectopic beat classification for use with mobile cardiac telemetry

BeatLogic uses custom AI models that leverage temporal and spatial information from the ECG to locate and classify beats by their individual types. Deep learning has become the basis for a new generation of automated ECG interpretation algorithms that are capable of achieving human levels of accuracy for rhythm and beat detection.

Want more information?

Connect with a sales representative to learn more about how BeatLogic uses deep learning to automate ECG interpretation for efficient, accurate data and enhanced patient care.

Caution: U.S. federal law restricts this device to sale by or on the order of a physician.