ZEUS System

iRhythm Technologies, Inc. • Cardiovascular • 02/15/2023

510(k)IEC 62304 Class C

Device Purpose

The ZEUS System is an AI-powered software platform designed for long-term electrocardiogram (ECG) monitoring, analyzing data from compatible wearable sensors to capture, analyze, and report symptomatic and asymptomatic cardiac events in adult patients. Its methodology integrates automated ECG processing by the ECGDL algorithm with crucial review and curation by Certified Cardiographic Technicians to generate comprehensive reports, including daily AF/AFL burden estimates, thereby supporting clinicians in arrhythmia diagnosis and patient management.

Summary

The ZEUS System by iRhythm Technologies is a software-based programmable diagnostic computer designed for long-term cardiac monitoring in adult patients (18 years or older), including those who are asymptomatic or experience transient symptoms like palpitations, dizziness, or syncope. Its core function is to capture, analyze, and report continuous electrocardiogram (ECG) information by processing data from compatible monitoring devices using an AI-based ECG Analysis Software (ECGDL) to generate initial cardiac information on beats, ectopic runs, ECG segments, rhythms, and heart rate; for the Zio AT service, an AI-based AutoTrigger Engine (ATE) also enables asymptomatic ECG triggers and analysis of arrhythmia events. The ECG analysis output from the ZEUS System is reviewed by Certified Cardiographic Technicians (CCTs) before a final report of preliminary findings is compiled and made available to clinicians via a secure website, aiding in diagnosis and management. This iteration introduces software modifications for daily atrial fibrillation/atrial flutter (AF/AFL) burden estimate reporting and incorporates ECGDL software improvements for enhanced performance, with its safety and efficacy for these changes supported by nonclinical verification and validation testing according to design specifications.

AI Regulatory Concerns

Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

Keywords

ZEUS SystemECG AnalysisLong-term Cardiac MonitoringArrhythmia DetectionArtificial Intelligence (AI)ECGDL SoftwareAF/AFL Burden EstimateRemote Patient MonitoringAsymptomatic Cardiac EventsCertified Cardiographic Technician Review

Device Metadata

Submission Number

K222389

Company

iRhythm Technologies, Inc.

Panel

Cardiovascular

Product Code

N/A

Data Type

Signals

Clinical Function

Assessment

AI Function

Analysis

AI Subclass

detection/diagnosis

Relevant Clinical Questions

Q1. What specific metrics demonstrate the "modest performance improvements" in the updated ECGDL software, and how do these impact diagnostic accuracy or CCT workflow efficiency?; How does the AI-based AutoTrigger Engine (ATE) balance sensitivity for asymptomatic event detection with specificity to minimize false positives that could increase Certified Cardiographic Technician workload or clinician alarm fatigue?; What is the validation process for the AF/AFL burden estimates provided in the daily reports, particularly regarding their accuracy compared to the final, more comprehensively reviewed report?; Can the ZEUS system differentiate and report on various subtypes of atrial arrhythmias beyond general AF/AFL, and are there plans to expand its AI capabilities for other complex arrhythmias?; Considering the reliance on Certified Cardiographic Technician review, what measures are in place to ensure inter-rater reliability and consistency in the interpretation and reporting of ECG data processed by the ZEUS system?

Risk Classification

ESL Analysis

IEC 62304 ClassC

FDA Device ClassII

FDA Class II via 510(k) pathway; IEC 62304 Class C (software safety classification); Authorized before §524B enforcement

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Cybersecurity Evidence

Based on AI-generated device summaries, not the full FDA submission. Items not detected here may still be present in the complete submission package.

Cyber Score30/100

SBOM Evidence⚠ Not mentioned in summary

Cyber Risk Assessment⚠ Not mentioned in summary

Postmarket Plan✓ Detected in Summary

§524B ApplicableNo

Supply Chain BOM Evidence

Based on the CycloneDX / OWASP ECMA-424 xBOM ecosystem. Detection is from the AI-generated summary.

SBOMSoftware Bill of Materials

- Not detected

ML-BOMMachine Learning Bill of Materials(algorithm)

✓ Detected

SaaSBOMSoftware-as-a-Service Bill of Materials(remote, platform)

✓ Detected

HBOMHardware Bill of Materials(sensor)

✓ Detected

CBOMCryptography Bill of Materials

- Not detected

VDR/VEXVulnerability Disclosure Report / Vulnerability Exploitability eXchange

- Not detected

OBOMOperations Bill of Materials

- Not detected

Analysis:

• Analysis is based on the AI-generated device summary, not the full FDA submission package. Click "Analyze Full FDA PDF" below to scan the actual submission document.

• Evidence of ML-BOM, SaaSBOM, HBOM detected in AI-generated device summary.

• This device was authorized before §524B took effect. Cybersecurity evidence requirements were less prescriptive at the time.

• Not detected in AI-generated device summary: SBOM, CBOM, VDR/VEX, OBOM. These may be present in the full FDA submission.

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