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510(k) Data Aggregation

    K Number
    K122443
    Device Name
    UFIT TEN-10
    Date Cleared
    2012-11-20

    (102 days)

    Product Code
    Regulation Number
    870.1130
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The UFIT® TEN-10 Automated Wrist Blood Pressure Monitor with Computer Controls and Web Services is a non-invasive blood pressure measurement system intended to measure the systolic and diastolic blood pressure and pulse rate. It is intended for patient use at home and by healthcare professionals in their respective practice.

    The device is intended for use by adults 18 years or older. The cuff is to be used for wrist sizes from 13.5 cm to 23 cm (5.3 in to 9.1 in).

    Device Description

    UFIT® TEN-10 "Automated Wrist Blood Pressure Monitor with Computer Controls and Web Services" is for use by medical professionals or at home and is a non-invasive blood pressure measurement system intended to measure the diastolic and systolic blood pressures and pulse rate of an adult individual by using a non-invasive technique in which an inflatable cuff is wrapped around the wrist. The cuff circumference is limited to 13.5cm-23cm.

    UFIT® TEN-10 "Automated Wrist Blood Pressure Monitor with Computer Controls and Web Services" is designed and manufactured according to ANSI/AAMI SP10-manual, electronic or automated sphygmanometers.

    The operational principle is based on oscillometric method and pressure sensor technology. It calculates the systolic and diastolic blood pressure. UFIT® TEN-10 "Automated Wrist Blood Pressure Monitor with Computer Controls and Web Services" achieves its function by connecting the device to a Personal Computer via USB connection. Furthermore the device does not contain an LCD or other display components, so it is necessary for the device to connect to a Personal Computer containing a support software to constitute a complete blood pressure measurement system.

    When a reading is taken by the device through the software, it is sent through the Internet to servers that perform the analysis of the reading and the result is returned through the Internet to the end user - all by means of Cloud Computing. This provides secure accounts for the users to submit their data so that they can monitor their results and progress.

    AI/ML Overview

    Here's a summary of the acceptance criteria and the study proving the device meets them, based on the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance:

    Acceptance Criteria (from ANSI/AAMI SP10:2002)Reported Device Performance (UFIT® TEN-10)
    All applicable safety and performance requirements for an automated sphygmomanometer (as defined by ANSI/AAMI SP10:2002, and its amendments A1:2003 and A2:2006)The UFIT® TEN-10 complies with and meets all applicable requirements of the standards.
    Compliance to IEC 60601-1-2 (Electromagnetic Compatibility)Complied with EN 60601-1-2:2001, ICES-001 Issue 4 June 2006, and FCC 47 CFR Part 15, Subpart B - Verification.
    Compliance to IEC 60601-1 (General Requirements for Safety)Successfully subjected to the test requirements of IEC 60601-1:1988, CAN/CSA C22.2 No.601.1-M90 and UL 60601-1:2003.

    2. Sample Size for the Test Set and Data Provenance:

    • Sample Size: The document does not explicitly state the number of subjects (sample size) used for the clinical tests that demonstrated compliance with ANSI/AAMI SP10. It only mentions that "UFIT® TEN-10 Automated Wrist Blood Pressure Monitor with Computer Controls and Web Services tests in accordance with ANSI/AAMI SP10, and the device meets all applicable requirements of the standard."
    • Data Provenance: Not explicitly stated. The document doesn't provide information on the country of origin of the data or whether the study was retrospective or prospective.

    3. Number of Experts and Qualifications for Ground Truth:

    • The document does not specify the number of experts used to establish ground truth or their qualifications. The clinical performance data references compliance with the ANSI/AAMI SP10 standard, which implies a standardized method for validation, usually involving a comparison to a reference standard (like a mercury sphygmomanometer) performed by trained observers. However, the details of these observers or their specific roles in establishing "ground truth" are not provided.

    4. Adjudication Method:

    • Not explicitly stated. The document refers to compliance with ANSI/AAMI SP10, which outlines specific methodologies for validating blood pressure devices. These methodologies often involve simultaneous measurements by multiple observers (adjudication). However, the specific adjudication method (e.g., 2+1, 3+1) is not detailed in this summary.

    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

    • No. The document does not describe an MRMC comparative effectiveness study where human readers improve with AI vs. without AI assistance. This device is a standalone blood pressure monitor, not an AI-assisted diagnostic tool for human readers.

    6. Standalone Performance (Algorithm only without Human-in-the-loop performance):

    • Yes. The entire testing described in the "Non-Clinical Performance Data" and "Clinical Performance Data" sections, specifically compliance with ANSI/AAMI SP10, refers to the standalone performance of the UFIT® TEN-10 device in measuring blood pressure and pulse rate. The software merely processes and displays the data, and the web services provide storage and analysis, but the core measurement is performed by the device itself.

    7. Type of Ground Truth Used:

    • Compliance with a recognized standard: The ground truth for validating the device's accuracy would have been established through a comparison to a referencestandard according to ANSI/AAMI SP10 protocols. This typically involves simultaneous measurements against a highly accurate, calibrated reference device (e.g., mercurysphygmomanometer) performed by trained observers.

    8. Sample Size for the Training Set:

    • The document does not provide a sample size for a training set. This is because the device is a medical measurement device, not an AI/machine learning model that typically requires a separate training set. The performance is validated through clinical testing against a standard, not by training an algorithm.

    9. How the Ground Truth for the Training Set was Established:

    • Not applicable, as there is no mention of a training set for an AI/machine learning algorithm. The "ground truth" for the device's performance evaluation was established by adherence to the methodologies outlined in the ANSI/AAMI SP10:2002 standard and its amendments, as described in point 7.
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