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Indicated for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. Intended for monitoring and recording of, and to generate alarms for, multiple physiological parameters of adults and pediatrics in hospital environments and during transport inside hospitals.

The name of this device is the IntelliVue MX40 Patient Monitor.

This document outlines information found in the provided 510(k) summary for the Philips IntelliVue MX40 Patient Monitor. Please note that the available text primarily focuses on regulatory compliance and substantial equivalence to a predicate device, rather than a detailed comparative clinical study. Therefore, some of the requested information, particularly regarding specific performance metrics, sample sizes for test sets, and details of clinical studies, may not be explicitly present.

Acceptance Criteria and Reported Device Performance

Study Information

1. Sample size used for the test set and the data provenance:

   • Test Set Sample Size: The document does not specify a separate "test set" sample size in terms of patient data or clinical cases. The testing described is at a system, performance, and safety level, likely using engineering tests, simulations, and possibly limited human factor evaluations (though not explicitly stated as such). It is not a clinical study with a patient cohort. The evaluation is primarily based on demonstrating substantial equivalence to a predicate device and compliance with technical standards.
   • Data Provenance: Not applicable in the context of a clinical test set from patients. The testing involved internal verification and validation activities, which would use simulated data, test equipment, and engineering specifications.

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

   • This information is not applicable as the document describes a technical verification and validation process against predefined specifications and standards, not a clinical study requiring expert-established ground truth from patient data. The "ground truth" here would be the technical specifications and performance characteristics of the predicate device, as well as the requirements of the cited voluntary standards.

3. Adjudication method for the test set:

   • Not applicable. There was no clinical test set requiring adjudication in the context of this 510(k) summary. The "adjudication" in this context would be the pass/fail assessment against the established technical specifications and standards by the engineering and regulatory teams at Philips, and ultimately, by the FDA.

4. 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:

   • No. The document makes no mention of AI assistance or human readers. This is a 510(k) submission for a patient monitor, which is a standalone device providing physiological parameter monitoring. It is not an AI-powered diagnostic or assistive technology for human readers.

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

   • Yes, in essence. The "performance" being evaluated is that of the device itself (the monitor), which operates in a standalone capacity to measure and display physiological parameters and generate alarms. The verification and validation activities described (system level tests, performance tests, safety testing) assess the device's inherent function, without explicitly involving human-in-the-loop performance measurement or comparison in the context of a clinical study. The device is intended for use by healthcare professionals, but the performance testing described here is about the device's technical capabilities, not its impact on human action or diagnostic accuracy in a study context.

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

   • The "ground truth" for this submission against the acceptance criteria is primarily based on:
     • Predicate Device Specifications: The established performance and reliability specifications of the previously cleared MX40 IntelliVue Patient Monitor (K103646).
     • Voluntary National and International Standards: Such as IEC 60601-1, ANSI/AAMI EC 13, ISO EN 9919, etc., which define acceptable performance limits and safety requirements for medical devices of this type.
     • Internal Engineering Specifications: Philips's own internal design and performance specifications for the updated device.

7. The sample size for the training set:

   • Not applicable. There is no mention or indication of a "training set" in the context of this 510(k) summary. The device is an updated version of an existing patient monitor, implying its core algorithms and functions are established and validated-it is not a machine learning model that undergoes a training phase as described in AI/ML development.

8. How the ground truth for the training set was established:

   • Not applicable, as there is no training set mentioned.

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Indicated for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. Intended for monitoring and recording of, and to generate alarms for, multiple physiological parameters of adults and pediatrics in hospital environments and during transport inside hospitals.

The name of this device is the MX40 patient monitor.

The provided text describes a 510(k) premarket notification for the Philips MX40 patient monitor. However, the information regarding specific acceptance criteria, detailed study design, sample sizes, expert qualifications, adjudication methods, or specific performance metrics is very limited.

Here's an analysis of what can be extracted and what is missing, presented in the requested format:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not specified.
• Data Provenance: Not specified. The document mentions "system level tests, performance tests, and safety testing," but does not indicate whether these involved clinical data, simulated data, or a combination, nor does it mention the country of origin or whether it was retrospective or prospective.

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

• Number of Experts: Not mentioned.
• Qualifications of Experts: Not mentioned.
• Ground Truth Establishment: Not mentioned. Given the nature of a patient monitor, "ground truth" would likely involve comparison to established reference standards or expert clinical assessment, but this is not detailed.

4. Adjudication method for the test set

• Adjudication Method: Not mentioned.

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

• MRMC Study: No, this is not an MRMC comparative effectiveness study. The device is a patient monitor, not an AI-assisted diagnostic tool for human readers. Therefore, the concept of "human readers improve with AI" is not applicable here.

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

• This device is a patient monitor, and its performance would inherently be "standalone" in terms of its physiological measurement and alarm functions. However, the text does not explicitly refer to 'algorithm-only' or 'human-in-the-loop' performance. The evaluations were focused on the device's ability to "monitor and record" and "generate alarms," which are intrinsic functions of the device itself.

7. The type of ground truth used

• Type of Ground Truth: Not explicitly stated. For a patient monitor, ground truth would typically refer to the true physiological state or precise measurements obtained from a gold standard reference device, or expert clinical assessment. The document states "Verification, validation, and testing activities establish the performance, functionality, and reliability characteristics," suggesting an engineering and performance testing approach rather than an explicit "ground truth" in the clinical evaluation sense, although clinical validity would be part of overall performance.

8. The sample size for the training set

• Sample Size for Training Set: This device is a physiological monitor, not a machine learning or AI-driven system that would typically have a "training set" in the common understanding of those terms. Therefore, this information is not applicable or provided.

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

• Ground Truth for Training Set: Not applicable (as explained in point 8).

Summary of the Study that Proves the Device Meets Acceptance Criteria:

The document broadly states that "Verification, validation, and testing activities" were conducted. These activities involved:

• System level tests: Evaluation of the integrated system.
• Performance tests: Assessment of the device's functional capabilities (e.g., accuracy of physiological parameter measurement, alarm generation).
• Safety testing from hazard analysis: Ensuring the device meets safety requirements.

The acceptance criteria for these tests were based on the existing "specifications cleared for the predicate device" (TRx4841A, IntelliVue Telemetry System Transceiver). The study concluded that the new device, MX40 patient monitor, exhibited "substantial equivalence" to the predicate device and "meets all defined reliability requirements and performance claims."

In essence, the provided text describes a regulatory submission where the new device's equivalence to a cleared predicate device was established through a series of internal verification and validation tests, rather than a detailed clinical trial with extensive ground truth establishment and expert review. The focus was on demonstrating that the new device performs as reliably and effectively as its legally marketed predecessors according to their established specifications.

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