The Zio AT ECG Monitoring System and its ZEUS System component are used for long-term cardiac monitoring by capturing continuous ECG data and analyzing it with AI algorithms to detect arrhythmias. The system helps clinicians by automatically detecting and reporting symptomatic and asymptomatic cardiac events, allowing improved cardiac care and diagnostics.
The device is intended to capture, analyze and report symptomatic and asymptomatic cardiac events and continuous electrocardiogram information for long-term monitoring in adults.
The ZEUS System uses a deep learning-based rhythm classification algorithm to analyze continuously recorded ECG data. It processes digital long-term continuous ECG signals, downloads and stores the data, and integrates machine learning and deep learning classifications to generate detailed cardiac rhythm reports for clinicians.
The device's arrhythmia detection algorithm was tested according to AAMI ANSI EC57:2012 performance standards and IEC 60601-2-47:2012 safety standards for ambulatory ECG systems. Verification and system-level regression testing demonstrated that the device meets design requirements and intended use without new safety or effectiveness concerns.
No predicate devices specified
Submission
6/7/2018
FDA Approval
8/29/2018
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