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510(k) Data Aggregation

    K Number
    K213189
    Date Cleared
    2022-03-01

    (153 days)

    Product Code
    Regulation Number
    870.1130
    Reference & Predicate Devices
    Predicate For
    N/A
    Why did this record match?
    Reference Devices :

    K170666

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Wrist-type Fully Automatic Digital Blood Pressure Monitors are intended to measure blood pressure (systolic and diastolic) and pulse rate of adults and adolescents over 12 years of age.

    Device Description

    The Wrist-type Fully Automatic Digital Blood Pressure Monitor is consist of sphygmomanometer main body and cuff. The mainbody contains ABS housing, LCD, keys, measurement control module, pneumatic control module, power supply module. The Wrist-type Fully Automatic Digital Blood Pressure Monitor is automatic, non-invasive, blood pressure measurement system for over-the-counter (OTC) use in home and clinical environment. The device with an inflatable cuff wrapping around the patient's wrist and the cuff is inflated automatically by an internal pump in the device. The systolic and diastolic blood pressures are determined by oscillometric method and silicon integrate pressure sensor technology. The deflation rate is controlled by a preset mechanical valve at a constant rate. The pressure of the cuff is completely released automatically at the end of the measurement. At the same time, the measurements are displayed on the LCD display for three minutes. The cuff can measure pressure range from 0 to 300mmHg, and the pulse rate range from 30 to 180 beats/min.

    AI/ML Overview

    Here's a breakdown 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

    The acceptance criteria are derived from the ISO 81060-2:2018+AMD2020 standard for clinical investigation of automated noninvasive sphygmomanometers.

    Acceptance Criteria (from ISO 81060-2:2018+AMD2020)Reported Device Performance (Model DBP-2208, Cuff 13.5-21.2cm)Reported Device Performance (Model DBP-2242, Cuff 12.5-23cm)
    Method 1:
    Average difference for Systolic Blood Pressure ≤ ±5 mmHg0.84 mmHg0.87 mmHg
    Standard deviation for Systolic Blood Pressure ≤ 8 mmHg5.25 mmHg5.22 mmHg
    Average difference for Diastolic Blood Pressure ≤ ±5 mmHg0.21 mmHg0.20 mmHg
    Standard deviation for Diastolic Blood Pressure ≤ 8 mmHg4.92 mmHg4.93 mmHg
    Method 2:
    Average difference for Systolic Blood Pressure ≤ ±5 mmHg0.84 mmHg0.87 mmHg
    Standard deviation for Systolic Blood Pressure ≤ Maximum permissible standard deviation (based on mean difference, from Table 1 in document)4.52 mmHg (<6.95mmHg)4.48 mmHg (<6.887mmHg)
    Average difference for Diastolic Blood Pressure ≤ ±5 mmHg0.21 mmHg0.20 mmHg
    Standard deviation for Diastolic Blood Pressure ≤ Maximum permissible standard deviation (based on mean difference, from Table 1 in document)4.36 mmHg (<6.879 mmHg)4.38 mmHg (<6.95 mmHg)

    Conclusion: Both tested models (DBP-2208 and DBP-2242) met all specified acceptance criteria according to both Method 1 and Method 2 of ISO 81060-2:2018+AMD2020.

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

    • Sample Size: 85 patients for each clinical investigation (one for cuff 13.5-21.2cm using DBP-2208 as representative, and one for cuff 12.5-23cm using DBP-2242 as representative). Each group comprised 43 females and 42 males.
    • Data Provenance: The document does not explicitly state the country of origin. It describes clinical studies conducted on "patients" and "subjects" indicating prospective data collection. "All the subjects were volunteer to take part in the clinical study, all the subjects completed the clinical study without any AE or side-effect."

    3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

    The document states that a "manual Mercury Sphygmomanometer was used as a reference device" to establish the ground truth. It does not explicitly mention the number of experts or their specific qualifications (e.g., "radiologist with 10 years of experience"). However, for a clinical study involving a mercury sphygmomanometer as the reference, it is implied that trained medical professionals would perform these measurements. The standard ISO 81060-2 typically requires measurements by qualified observers.

    4. Adjudication Method for the Test Set

    The adjudication method described is the "Same wrist sequential method." This means the device under test and the reference device (manual Mercury Sphygmomanometer) measurements were taken sequentially on the same wrist. The document does not specify a separate "adjudication" process involving multiple experts reviewing discrepancies, but rather a direct comparison to the reference device.

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

    No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The study focuses on the accuracy of the device itself compared to a reference standard, not on how human readers' performance might improve with AI assistance. This is a standalone device accuracy study.

    6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

    Yes, this was a standalone performance study. The "Wrist-type Fully Automatic Digital Blood Pressure Monitor" is an automated device designed to measure blood pressure. The clinical investigations directly assessed the device's accuracy against a manual reference without human intervention in the measurement process (other than proper placement and initiation).

    7. Type of Ground Truth Used

    The ground truth used was established by a manual Mercury Sphygmomanometer. This is considered a gold standard for blood pressure measurement in clinical studies.

    8. Sample Size for the Training Set

    The document does not provide any information about a training set. This is a validation study for a medical device's accuracy, not an AI/machine learning algorithm that typically requires a training set. The device determines blood pressure using an oscillometric method based on pre-programmed algorithms and hardware.

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

    Not applicable, as no training set for an AI/machine learning algorithm is mentioned in the document.

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