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510(k) Data Aggregation

    K Number
    K210086
    Manufacturer
    Date Cleared
    2021-05-20

    (127 days)

    Product Code
    Regulation Number
    870.2300
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Vitals360® device is intended to be used for measuring, displaying, reviewing and storing of non-invasive blood pressure (NIBP), non-invasive monitoring of functional oxygen saturation of arterial hemoglobin (SpO2), pulse rate (PR), forehead temperature (TEMP), ECG, weight and height in adults no less than 18 years of age.

    This VITALS360® device is intended for use by trained adults only who can use smartphones proficiently.

    This VITALS360® device is intended for use in a clinical or home environment.

    This VITALS360® device is a reusable device following thorough cleaning between uses.

    Device Description

    The Vitals360® is a device designed for spot-checking measuring of the patient's physiological parameters. It can monitor the patient's blood oxygen saturation (SpO2) and pulse rate (PR) non-invasively by the photoelectric method. It can also measure non-invasive blood pressures of systolic and diastolic) by the oscillating method and body temperature (TEMP) by the infrared radiation energy technology. Additionally, it can record single lead ECG signal.

    The Vitals360® capabilities include storing, displaying measuring data.

    AI/ML Overview

    This document describes the regulatory submission for the Vitals360® Multi-Vitals Mobile Monitor (K210086). The device is intended for measuring, displaying, reviewing, and storing non-invasive blood pressure (NIBP), functional oxygen saturation of arterial hemoglobin (SpO2), pulse rate (PR), forehead temperature (TEMP), and ECG in adults 18 years of age and older.

    Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

    1. A table of acceptance criteria and the reported device performance

    The document does not present a single table of acceptance criteria and specific reported device performance in a dedicated section with pass/fail outcomes. Instead, it describes performance characteristics and accuracies within the "Comparison to the Predicate Device" section and lists the standards to which clinical studies were conducted under "Performance Data."

    Based on the information provided, we can infer the acceptance criteria for individual parameters from the device's specifications and the adherence to relevant ISO standards for medical devices. The "reported device performance" is essentially the device's stated specifications and accuracies.

    ParameterAcceptance Criteria (Implied from stated device performance and predicate comparison)Reported Device Performance (Vitals360®)
    SpO2 AccuracyShould be comparable to or better than predicate (±3% for 70%-100% range)Displayed range: 70%100%. Accuracy: ±2% (during 90100%), ±4% (during 70~89%)
    Pulse Rate RangeComparable to predicate (30 bpm-240 bpm)30 to 150 bpm
    Pulse Rate AccuracyComparable to predicate (±2bpm or ±2%, whichever is greater)±2bpm or ±2%, whichever is greater
    NIBP AccuracyMean deviation values: ±5 mmHg. Standard deviation <= 8 mmHg (Consistent with predicate)Mean deviation values: ±5 mmHg. Standard deviation <= 8 mmHg.
    NIBP PressureRange - SystolicComparable to predicate (60 mmHg - 255 mmHg)60 mmHg ~230mmHg
    NIBP PressureRange - DiastolicComparable to predicate (30 mmHg - 195 mmHg)40 mmHg ~130mmHg
    Temperature RangeComparable to predicates (e.g., 32.0°C to 43.0°C)34.0°C 43.0°C (93.2°F109.4°F)
    Temperature AccuracyComparable to predicates (e.g., ±0.2°C for 36.0°C to 39.0°C, ±0.3°C other range)±0.3°C (±0.5°F)
    ECG Heart Rate RangeComparable to predicate (30bpm-240bpm)30bpm-240bpm
    ECG Heart Rate PrecisionComparable to predicate (±2bpm or ±2%, whichever is greater)±2bpm or ±2%, whichever is greater

    The claims of "substantial equivalence" imply that these reported performances met the criteria required for comparison to the predicate devices and relevant standards.

    2. Sample size used for the test set and the data provenance

    The document states: "Clinical studies were conducted to verify the accuracy of proposed device." and "Clinical testing has been performed under an approved protocol with subject informed consent. Clinical test results support device accuracy claims for the specified measurement range."

    However, the specific sample sizes for the test sets are not explicitly stated in the provided text. The data provenance is generally clinical studies for verification, implying human subjects. The country of origin of the data and whether the studies were retrospective or prospective are not specified.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

    The document does not provide information on the number of experts or their qualifications used to establish ground truth for the test set.

    4. Adjudication method for the test set

    The document does not specify any adjudication method (e.g., 2+1, 3+1, none) for the test set.

    5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

    The Vitals360® device is a medical monitoring device, not an AI-assisted diagnostic imaging tool that would typically involve human readers. Therefore, an MRMC comparative effectiveness study involving human readers with and without AI assistance is not applicable and was not conducted for this type of device.

    6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done

    This refers to the inherent accuracy of the device's measurements (SpO2, NIBP, TEMP, PR, ECG). The document states that "Clinical studies were conducted to verify the accuracy of proposed device" and lists ISO standards that govern the accuracy and performance of such medical devices. This implicitly means that the device's standalone performance, i.e., its ability to accurately measure these physiological parameters, was evaluated. The reported accuracies (e.g., for SpO2, NIBP, Pulse Rate, Temperature) represent the standalone performance of the device's algorithms and sensors.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

    For a monitoring device measuring vital signs, the ground truth is typically established by:

    • Reference standard devices: Using highly accurate and calibrated medical equipment as the gold standard for comparison (e.g., a clinically validated sphygmomanometer for NIBP, a co-oximeter for SpO2, or a precision thermometer for temperature).
    • Direct physiological measurements: For parameters like ECG, the ground truth would be the actual electrical activity of the heart as captured by a reference ECG system.

    The document states that clinical studies were performed according to standards like ISO 80601-2-61 (Pulse Oximeter), ISO 81060-2 (Non-invasive sphygmomanometers), and ISO 80601-2-56 (clinical thermometers). These standards outline the methods for establishing ground truth for each specific parameter, typically involving comparisons to reference devices or established physiological measurements. While not explicitly detailed in the text, adherence to these standards implies the use of appropriate ground truth methods.

    8. The sample size for the training set

    The Vitals360® is a vital signs monitor, not typically an AI/machine learning device that requires a "training set" in the conventional sense for a diagnostic algorithm. Its performance relies on established physical principles of measurement (e.g., oscillometric for NIBP, photoelectric for SpO2, infrared for temp) and signal processing. Therefore, the concept of a "training set" from the perspective of teaching an AI model is not applicable to this device.

    9. How the ground truth for the training set was established

    As explained in point 8, the concept of a "training set" for an AI model is not applicable to this device.

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