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510(k) Data Aggregation

    K Number
    K180234
    Device Name
    physiQ Heart Rhythm Module
    Manufacturer
    physiQ Inc.
    Date Cleared
    2018-08-10

    (193 days)

    Product Code
    DPS, DBS
    Regulation Number
    870.2340
    Why did this record match?
    Applicant Name (Manufacturer) :

    physiQ Inc.

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP Authorized
    Intended Use
    The physlQ Heart Rhythm Module is intended for use by a physician or other qualified medical professionals for the calculation of heart rate and heart rate variability and the detection of atrial fibrillation using ambulatory ECG data. The physlQ Heart Rhythm Module supports receiving and analyzing single-lead ECG signals recorded in a compatible format from FDA-cleared ECG biosensor devices using "wet" electrode technology when assessment of rhythm is desired. The phys\Q Heart Rhythm Module is for use in subacute clinical settings for remote patient monitoring. The physlQ Heart Rhythm Module is not for use in patients requiring or life-sustaining systems or ECG Alam devices.
    Device Description
    The physIQ Heart Rhythm Module (Version 1.0) is a computerized all-software callable function library in the Python programming language that is designed for calculating heart rate and heart rate variability and for detecting atrial fibrillation determined by automated analysis of any single electrocardiogram (ECG) channel collected by commercially-available ECG biosensor devices. This Heart Rhythm Module will be integrated by the customer organization into an end-to-end system (biosensor data collection to clinician display) that makes calls into the product, most typically via a Python middleware script. The "middleware" accesses the source ECG data from a customer's data collection system, most likely via its own application programming interface (API), and makes calls to the physIQ Heart Rhythm Module to input ECG for processing into the vital sign outputs of the product. These outputs are returned to the middleware, which may insert these results into a downstream monitoring system for clinical use.
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