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510(k) Data Aggregation

    K Number
    K241634
    Date Cleared
    2025-02-11

    (250 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 Wrist Blood Pressure Monitor is intended to measure the systolic blood pressure as well as the pulse rate of adult person via non-invasive oscillometric technique at medical facilities or at home. The intended wrist circumference is 13.5-21.5 cm.

    Device Description

    The Wrist Blood Pressure Monitor, including XY-W01B, can automatically complete the inflation, deflation and measurement, which can measure systolic and diastolic blood pressure as well as the pulse rate of adult person with wrist circumference of 135-215mm through oscillometric method. The initial inflation pressure of the cuff is zero pressure. When start the cuff will be inflated and deflated. The Wrist Blood Pressure Monitor is composed of monitor unit and wrist cuff. Of which the monitor unit contains main control circuit board, air pump, deflation valve, LCD and shell. The two models XY-W01A and XY-W01B have the same intended use, working principle, measuring range, accuracy, cuff, and conformance standard, except for product appearance. The devices are powered by 2 AAA batteries. The Wrist Blood Pressure Monitor has a memory function that automatically stores 90 sets data of the latest measurements.

    AI/ML Overview

    The provided text describes the acceptance criteria and the study conducted for the Wrist Blood Pressure Monitor (models XY-W01A, XY-W01B).

    Here's a breakdown of the requested information:

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance Criteria (Standard: ISO 81060-2:2018)Reported Device Performance (Clinical Test)
    Mean error for systolic pressure ≤ ±5 mmHgMean error within ±5 mmHg
    Standard deviation for systolic pressure ≤ 8 mmHgStandard deviation within 8 mmHg
    Mean error for diastolic pressure ≤ ±5 mmHgMean error within ±5 mmHg
    Standard deviation for diastolic pressure ≤ 8 mmHgStandard deviation within 8 mmHg
    All data not over the limits.All data is not over the limits.

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

    • Sample Size: 120 subjects (53 female and 67 male)
    • Data Provenance: The document does not explicitly state the country of origin.
    • Retrospective or Prospective: Not explicitly stated, but clinical tests for device approval are typically prospective.

    3. Number of Experts Used to Establish Ground Truth and Qualifications

    This information is not provided in the document. For blood pressure monitors, the "ground truth" (reference measurements) is typically established by trained technicians using a standardized auscultatory method, not necessarily by "experts" in the sense of physicians or radiologists establishing a diagnostic truth.

    4. Adjudication Method

    This information is not provided in the document, as it relies on direct comparative measurements rather than expert adjudication of imaging or diagnostic results.

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

    A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This type of study is more relevant for diagnostic imaging AI systems where human readers interpret images. For a blood pressure monitor, the performance is compared against a reference measurement.

    6. Standalone Performance

    Yes, a standalone (algorithm only without human-in-the-loop performance) study was done. The clinical test evaluated the device's accuracy in measuring blood pressure and pulse rate against a reference standard.

    7. Type of Ground Truth Used

    The ground truth implicitly used is reference blood pressure measurements, likely obtained through a rigorously standardized auscultatory method as per the ISO 81060-2:2018 standard.

    8. Sample Size for the Training Set

    This information is not provided in the document. Given that this is a hardware device with an embedded algorithm (oscillometric technique), there isn't typically a separate "training set" in the way an AI/ML model would have for image recognition. The core algorithm's parameters are likely developed through extensive engineering and testing rather than a distinct training phase on a large dataset.

    9. How the Ground Truth for the Training Set Was Established

    This information is not provided. As mentioned above, the concept of a "training set ground truth" as understood in AI/ML is not directly applicable here. The device's underlying oscillometric algorithm and its parameters would have been developed and refined through engineering principles and testing against various blood pressure profiles and body types.

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