RhythmAnalytics

by Biofourmis Singapore Pte.  · Based in United States → — AI-powered automated interpretation of cardiac arrhythmias for enhanced clinical decision support.
Cardiology Emergency Medicine Internal Medicine
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Regulatory Status Disclosed

Overview

RhythmAnalytics by Biofourmis is an FDA-cleared software application designed for the assessment of cardiac arrhythmias using single-lead ECG data in subjects over 18 years of age. This cloud-based platform leverages enhanced deep-learning techniques to provide automated interpretation of more than 15 types of cardiac arrhythmias, including ventricular arrhythmias, ventricular ectopic beats, and all non-paced arrhythmias such as Atrial Fibrillation (AFib).

The platform supports downloading and analyzing data recorded in compatible formats from any FDA-cleared device used for arrhythmia diagnostics, such as Holter monitors or event recorders. It can also be electronically interfaced with data transferred from other computer-based ECG systems. RhythmAnalytics performs comprehensive ECG signal processing and analysis, QRS and Ventricular Ectopic Beat detection, QRS feature extraction, interval measurement, heart rate measurement, and rhythm analysis.

Intended for use by healthcare solution integrators, RhythmAnalytics allows them to build web or mobile applications that enable qualified healthcare professionals to review and confirm analytic results. It provides clinical decision support, offering interpretations to physicians and clinicians on an advisory basis, to be used in conjunction with their medical knowledge and other diagnostic information. The technology can be integrated as a cloud-based API into existing cardiac monitoring solutions or directly into a medical device or wearable sensor, significantly improving the accuracy and scalability of ECG analysis and reducing rates of misinterpretation.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • AI-based automated interpretation of cardiac arrhythmias
  • Detection of over 15 types of cardiac arrhythmias (including AFib, ventricular arrhythmias, ectopic beats)
  • Beat-by-beat morphology computation
  • ECG signal processing and analysis
  • QRS and Ventricular Ectopic Beat detection
  • QRS feature extraction, interval measurement, heart rate measurement, and rhythm analysis
  • Cloud-based API for integration
  • Compatibility with FDA-cleared ECG devices (Holter, event recorders, wearable sensors)
  • Deep learning techniques trained on millions of ECG recordings
  • Provides clinical decision support

Use Cases

  • Assessment of cardiac arrhythmias from single-lead ECG data
  • Clinical decision support for qualified healthcare professionals
  • Integration into web and mobile applications for remote patient monitoring
  • Automated interpretation for ambulatory ECG monitoring
  • Improving accuracy and scalability of ECG analysis for cardiac monitoring organizations
  • Supporting remote patient management in chronic conditions like heart failure and atrial fibrillation

What Physicians Need to Know

ECG/EKG Analysis Capability
RhythmAnalytics is an FDA-cleared, cloud-based, deep learning software platform for automated interpretation of cardiac arrhythmias using ambulatory ECG monitoring recordings. It performs ECG signal processing and analysis, QRS and Ventricular Ectopic Beat detection, QRS feature extraction, interval measurement, heart rate measurement, and rhythm analysis.
Arrhythmia Detection Accuracy
The platform detects over 15 (some sources say over 20 or dozens) types of cardiac arrhythmias, including ventricular arrhythmias, ventricular ectopic beats, and Atrial Fibrillation (AFib), with beat-by-beat morphology computation. It demonstrated cardiologist-level accuracy, outperforming other deep learning systems and a panel of cardiologists with a Sensitivity of 90.8%, Specificity of 98.2%, and an F1 score of 0.834.
Heart Failure Risk Prediction
As part of the broader Biofourmis Biovitalsu2122 platform, RhythmAnalytics contributes to a highly sophisticated AI-powered health analytics engine that predicts clinical exacerbation, including heart failure decompensation, in advance of a critical event. The BiovitalsHFu00ae solution, which leverages this platform, has received FDA Breakthrough Device designation for augmenting guideline-directed heart failure medication use and has shown improvements in adherence to GDMT and reduction in heart failure biomarkers.
Cardiac Monitoring Integration
RhythmAnalytics supports analysis of ECGs from any FDA-cleared devices or wearable sensors, such as Holter monitors and event recorders. It can be integrated as a cloud-based API into existing cardiac monitoring solutions or directly into medical devices or wearable sensors, enhancing accuracy and scalability of ECG analysis.
AHA/ACC Guideline Alignment
Biofourmis' BiovitalsHFu00ae solution is designed to follow Guideline-Directed Medical Therapy (GDMT) for heart failure. The Biofourmis Care solution has been selected by the American College of Cardiology (ACC) for its TRANSFORM3 study, which aims to improve adherence to GDMT for chronic cardiovascular conditions.
Real-Time Alert Capability
The platform provides clinical decision support by alerting clinicians to cardiac arrhythmias and changes in patients' vital signs from their baseline, which can be a precursor to decompensation. This advance notice allows for earlier clinical intervention.
Physician Tip

Leverage RhythmAnalytics for enhanced, automated ECG interpretation to improve diagnostic accuracy and efficiency in detecting various cardiac arrhythmias. Integrate this AI-powered tool to support clinical decision-making, especially for ambulatory ECG monitoring, and to potentially reduce misinterpretation rates. For heart failure management, utilize the broader Biovitals platform, including BiovitalsHFu00ae, to optimize guideline-directed medical therapy and enable earlier interventions based on predictive analytics, which can lead to better patient outcomes and reduced hospitalizations. The continuous monitoring and real-time alerts can provide a more comprehensive view of patient health compared to traditional periodic evaluations.

RhythmAnalytics is designed for flexible integration, offered as a cloud-based API for existing cardiac monitoring solutions or direct integration into medical devices and wearable sensors. It is compatible with various FDA-cleared ECG monitoring devices, including Holter monitors and event recorders. The overarching Biofourmis platform (Biovitals) also integrates with major EMR systems like Cerner and Epic, and supports continuous data collection from over 20 physiological parameters.

Details

Category Cardiology AI, Clinical Decision Support & Reference
Pricing Contact vendor
DeploymentCloud-based API
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status 1 AI-estimated

RhythmAnalytics received FDA 510(k) clearance (K182344) on March 7, 2019, as a Class II medical device (Programmable Diagnostic Computer, Product Code DQK, DPS). It is cleared for the assessment of cardiac arrhythmias using single-lead ECG data in subjects over 18 years of age.
Integrations
EHR Not specified
Specialties Cardiology, Emergency Medicine, Internal Medicine

What the Web Says

RhythmAnalytics, a Biofourmis product, is generally viewed as a promising AI-powered platform for remote patient monitoring and early detection of cardiac events. Reviewers highlight its ability to provide actionable insights from continuous physiological data, potentially improving patient outcomes and reducing hospital readmissions. However, some concerns exist regarding the complexity of integration into existing healthcare workflows and the need for robust validation studies.

Overall: Positive

Strengths

  • AI-powered predictive analytics for early detection of cardiac events.
  • Continuous remote patient monitoring capabilities.
  • Potential to reduce hospital readmissions and improve patient outcomes.
  • Actionable insights derived from physiological data.
  • Supports personalized care plans.
  • Non-invasive data collection.

Limitations

  • Integration challenges with existing EHR systems.
  • Potential for alert fatigue among clinicians.
  • Cost of implementation and ongoing subscriptions.
  • Requires significant clinician training for optimal use.
  • Data privacy and security concerns (general to health tech).
  • Limited long-term independent validation studies publicly available.

Based on reviews from: Healthcare IT News, MobiHealthNews, Fierce Healthcare, G2, Capterra, Reddit (healthcare IT discussions)

Last updated: 2026-07-18

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Press & Coverage

PR Newswire
Biofourmis' RhythmAnalyticsu2122 Platform Receives FDA Clearance for AI-Based Automated Interpretation of Cardiac Arrhythmias
Biofourmis announced FDA clearance for its RhythmAnalyticsu2122 platform, a cloud-based, deep learning software that automates the interpretation of over 15 types of cardiac arrhythmias using ambulatory ECG monitoring recordings. The platform is designed to improve accuracy and scalability of ECG analysis.
2019-04
Wearable Technologies
FDA Clears Biofourmis' AI-Driven Arrhythmia Detection Platform RhythmAnalytics
Biofourmis, a Singapore-based health-tech startup, received FDA clearance for its cloud-based software, RhythmAnalytics, which assists healthcare professionals in detecting cardiac arrhythmias. The platform uses enhanced deep learning to identify over 15 types of cardiac arrhythmias.
2019-05
PR Newswire
Biofourmis Partners with ImagineMIC to Pioneer Collaborative Remote Patient Monitoring Model
Biofourmis partnered with ImagineMIC to integrate its AI-powered, FDA-cleared RhythmAnalyticsu00ae with ImagineMIC's remote management technology for chronic condition patients. RhythmAnalyticsu00ae detects dozens of cardiac arrhythmias and provides clinical decision support.
2020-01
Biofourmis (Press Release)
Biofourmis' Biovitalsu2122 Analytics Engine Receives FDA Clearance for Ambulatory Physiologic Monitoring
Biofourmis received 510(k) clearance from the FDA for its machine-learning and AI-powered Biovitalsu2122 Analytics Engine, which builds upon the earlier FDA approval of its Biovitalsu2122 RhythmAnalyticsu2122 platform for cardiac arrhythmia interpretation.
2019-10
HCPLive
FDA Approves Artificial Intelligence-Based Physiological Monitor
The FDA granted 510(k) clearance to Biofourmis' Biovitals Analytics Engine, a machine learning and AI device for ambulatory physiological monitoring, marking the company's second FDA approval after its RhythmAnalytics platform.
2019-10
CardioVisual
Artificial Intelligence Has Arrived in Cardiology
Biofourmis' RhythmAnalytics is highlighted as an AI application in cardiology, a cloud-based software cleared by the FDA to interpret over 15 types of cardiac arrhythmias, aiding medical professionals in decision-making.
2020-07
Frontiers in Medicine
Artificial Intelligence in Perioperative Medicine: A Proposed Common Language With Applications to FDA-Approved Devices
This peer-reviewed article discusses FDA-approved AI/ML algorithms, categorizing RhythmAnalytics from Biofourmis as an 'opaque' system due to its deep learning technique for categorizing cardiac arrhythmias via convolutional neural networks.
2022-03
BMJ Health & Care Informatics (via PMC)
Single-lead arrhythmia detection through machine learning: cross-sectional evaluation of a novel algorithm using real-world data
This study evaluates Biofourmis' RhythmAnalytics, an algorithm trained on millions of single-lead ECGs, demonstrating high sensitivity, specificity, and accuracy in detecting various cardiac arrhythmias in acutely ill patients.
2022-07

Videos

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Frequently Asked Questions

RhythmAnalytics is designed for seamless integration, often through cloud-based APIs or direct integration into medical devices and wearable sensors. It can enhance existing EMR systems by automating tasks like data entry, analyzing complex datasets, and supporting clinical decision-making with evidence-based recommendations.
Biofourmis' RhythmAnalytics platform has received FDA clearance for automated interpretation of cardiac arrhythmias. As a healthcare AI tool handling Protected Health Information (PHI), it must comply with HIPAA regulations, requiring secure infrastructure, data encryption, access controls, and a Business Associate Agreement (BAA) with the vendor.
RhythmAnalytics utilizes enhanced deep learning to detect over 15 types of cardiac arrhythmias, demonstrating high sensitivity and specificity, and has been shown to outperform some other deep learning systems and panels of cardiologists. Traditional manual interpretation can have error rates approaching 50%, while other AI solutions like PMcardio and AliveCor's KAI 12L also offer advanced ECG analysis and arrhythmia detection.
While specific pricing for RhythmAnalytics isn't detailed, healthcare AI solutions commonly employ various models, including subscription-based, usage-based (e.g., per analysis or per encounter), or tiered compliance-based pricing. Costs can vary significantly depending on the complexity of the AI, data readiness, and integration needs.
Like many AI systems, RhythmAnalytics' performance relies on the quality and diversity of its training data, which can lead to limitations in accuracy, potential biases, and generalizability across diverse patient populations if not adequately addressed. Over-reliance on AI can also risk erosion of physician expertise and may not fully integrate a patient's holistic clinical factors.
RhythmAnalytics collects physiological data, including ECG recordings, from FDA-cleared devices and wearable sensors. Patient data privacy and security are ensured through adherence to HIPAA, which mandates robust safeguards like data encryption, access controls, and risk assessments to prevent unauthorized access or breaches.
Effective use of AI tools like RhythmAnalytics requires comprehensive training for physicians and staff to understand its strengths, limitations, and how to critically evaluate its outputs. This training should cover appropriate usage, data input, interpretation of results, and adherence to internal policies and regulatory guidelines.

Compare RhythmAnalytics

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Suggest an Edit → | Last Verified: 2026-04-17 | First Added: 2026-04-17
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