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510(k) Data Aggregation

    K Number
    K061610
    Device Name
    PHILIPS MODEL MP20, MP30, MP40, MP50, MP60, MP70, MP80 AND MP90 INTELLIVUE PATIENT MONITORS
    Manufacturer
    PHILIPS MEDIZINSYSTEME BOEBLINGEN GMBH
    Date Cleared
    2006-08-14

    (66 days)

    Product Code
    MHX
    Regulation Number
    870.1025
    Type
    Special
    Panel
    Cardiovascular (CV)
    Reference & Predicate Devices
    K021778,K030038,K032858,K033513,K040304,K041235,K042845,K050141,K050762,K051106,K052801,K053522,K060221
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    Device Name :

    PHILIPS MODEL MP20, MP30, MP40, MP50, MP60, MP70, MP80 AND MP90 INTELLIVUE PATIENT MONITORS

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

    Indicated for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. Intended for monitoring, recording and alarming of multiple physiological parameters of adults, pediatrics and neonates in healthcare facilities. The MP20, MP30, MP40 and MP50 are additionally intended for use in transport situations within healthcare facilities.

    ST Segment monitoring is restricted to adult patients only.

    The transcutaneous gas measurement (tcp02 / tcpCO2) is restricted to neonatal patients only.

    Device Description

    The modification is the introduction of Release D.05 software for the IntelliVue patient monitor devices.

    AI/ML Overview

    Here's a breakdown of the acceptance criteria and study information based on the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance

    Feature/MetricAcceptance CriteriaReported Device Performance
    System level testsBased on specifications cleared for predicate deviceMet acceptance criteria (implied by "test results showed substantial equivalence")
    Performance testsBased on specifications cleared for predicate deviceMet acceptance criteria (implied by "test results showed substantial equivalence")
    Safety testing (from hazard analysis)Based on specifications cleared for predicate deviceMet acceptance criteria (implied by "test results showed substantial equivalence")
    Reliability requirementsBased on specifications cleared for predicate device"Meets all reliability requirements"
    Performance claimsBased on specifications cleared for predicate device"Meets all performance claims"

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

    The document does not specify a sample size for the test set or the data provenance (e.g., country of origin, retrospective/prospective). It generally refers to "testing activities" and "test results" without providing these details.

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

    The document does not provide any information about experts used to establish ground truth or their qualifications. The testing appears to be based on engineering and performance specifications rather than expert interpretation of data.

    4. Adjudication Method for the Test Set

    The document does not specify any adjudication method for the test set.

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

    The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study, nor does it discuss human reader improvement with or without AI assistance. This type of study is not relevant for the described device which is a patient monitor.

    6. Standalone (Algorithm Only) Performance Study

    The document describes testing activities that establish the performance, functionality, and reliability of the modified device (software Release D.05 for IntelliVue patient monitors). This implies a standalone performance evaluation of the device as a whole (hardware and software), rather than a separate "algorithm only" study. The device's performance is gauged against its own specifications, not against human performance.

    7. Type of Ground Truth Used

    The ground truth for the testing appears to be based on engineering specifications, performance metrics, and safety standards established for the predicate device. It's not based on expert consensus, pathology, or outcomes data in the way medical imaging or diagnostic AI devices might be. The goal was to demonstrate that the updated software met the established parameters of the previous, cleared device.

    8. Sample Size for the Training Set

    The document does not mention a training set or its sample size. This device is a patient monitor with updated software, and the testing described is verification and validation, not a machine learning model training process that would typically involve a training set.

    9. How Ground Truth for the Training Set Was Established

    As no training set is mentioned or implied for this type of device and software update, this information is not applicable and therefore not provided in the document.

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