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510(k) Data Aggregation

    K Number
    K062545
    Date Cleared
    2007-04-09

    (222 days)

    Product Code
    Regulation Number
    862.3050
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K052448, K041334

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

    Intended to measure alcohol in human breath. Measurements obtained by this device are used in the detection of alcohol intoxication.

    Device Description

    The RMI® LCD Alcohol Tester is designed to measure deep lung air to test for the presence of alcohol in the blood. The relationship between alcohol in the blood and alcohol in the deep lung breath is well established by Henry's law in ratio of 2100:1. The RMI® LCD Alcohol Tester is an alcohol screening device and uses a blowing time of 3 seconds to capture an accurate deep lung sample. The RMI® LCD Alcohol Tester contains a semiconductor sensor designed to test for the presence of alcohol. The semiconductor material is heated to a specific temperature. The resistance of sensing material changes rapidly according to gas concentration changes, thereby enabling the reading of alcohol concentration by resistance measurement. The device employs a 3 digit LCD display which shows breath alcohol readings from 0.00 to 0.20 BAC (Breath Alcohol Concentration). Readings above 0.20 will display an LCD reading of "HI." The new device is a MODIFICATION of our old device, the Connectables® Alcohol Tester (K052448). We use the same sensor, but instead of three colored LEDs as indicators, the new device has a three digit LCD display of the measured BAC (breath alcohol concentration). Instead of analog comparators, we now employ an 8 bit microprocessor for control and measurement.

    AI/ML Overview

    The provided text is a 510(k) summary for the RMI® LCD Alcohol Tester. While it discusses the device's equivalence to a predicate device and mentions a "clinical trial" related to user understanding and device usage, it does not contain detailed acceptance criteria or a study proving the device directly meets specific performance metrics in terms of accuracy or precision against a gold standard for alcohol concentration measurement.

    The primary objective of the clinical trial mentioned was to establish that users could read and understand the instructions, properly use the device, and obtain comparable results to a predicate unit administered by a trained observer. This isn't a performance study in the sense of demonstrating accuracy against a laboratory reference.

    Here's an attempt to answer your request based on the limited information available in the provided document, highlighting what is not present:

    1. Table of Acceptance Criteria and Reported Device Performance

    Performance MetricAcceptance Criteria (Not explicitly stated for the new device's accuracy)Reported Device Performance (Implied equivalence)
    Accuracy of BAC measurementNot explicitly stated in terms of a specific range (e.g., +/- 0.01% BAC)The clinical trial showed that results were "comparable to those provided by a predicate unit administered by a trained observer." This indicates functional equivalence rather than specific accuracy data.
    User Understanding/Proper UseUser can read and understand instructions and properly use the device.The clinical trial showed that "the over the counter purchaser of this device could read and understand the instructions, could properly use the device."
    Comparability of resultsResults are comparable to a predicate unit administered by a trained observer.The clinical trial showed results were "comparable to those provided by a predicate unit administered by a trained observer."

    2. Sample Size for Test Set and Data Provenance

    • Sample Size for Test Set: Not specified. The document only mentions "a clinical trial was performed."
    • Data Provenance: Not specified (e.g., country of origin, retrospective or prospective). However, clinical trials are typically prospective.

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

    • Number of Experts: Not specified.
    • Qualifications of Experts: The ground truth for direct alcohol concentration was likely the "predicate unit administered by a trained observer" but the qualifications of this observer are not specified.

    4. Adjudication Method for the Test Set

    • Not specified. Given the nature of the study (user-centric rather than expert interpretation of complex images/data), a formal adjudication method like "2+1" or "3+1" is unlikely to have been relevant or applied.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

    • No. An MRMC study was not described. The study focused on user interaction with the device and comparability to a single predicate unit's readings, not the improvement of human readers with AI assistance. This device is a standalone breathalyzer, not an AI-assisted diagnostic tool for interpretation by humans.

    6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

    • Yes, implicitly. The device itself is a standalone algorithm (microprocessor controlled) that measures and displays BAC. The "clinical trial" assessed whether users could operate it correctly and if its readings were comparable to a predicate device, but the device's core function itself is "standalone" in that it performs its measurement without human interpretation of its internal signals.

    7. Type of Ground Truth Used

    • Comparison to a predicate device: The implied ground truth for the BAC measurement aspect was the "predicate unit administered by a trained observer." For the usability aspect, direct observation of user interaction and instruction comprehension would form the "ground truth."

    8. Sample Size for the Training Set

    • Not Applicable / Not Specified. This device is a hardware-based alcohol tester, not an AI or machine learning model that requires a training set in the conventional sense. Its "training" would involve calibration and engineering design, not data-driven model training.

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

    • Not Applicable. See point 8.
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