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The MPS450 Multiparameter Simulator is an electronic signal source for determining that patient monitors are performing within their operating specifications. The MPS450 provides the following function categories: ECG Functions Arrhythmia Functions ECG-Performance Testing Respiration Blood Pressure Temperature Cardiac Output (Optional) Fetal/Maternal ECG & IUP (Optional)

Fluke Biomedical's MPS450 Multiparameter Simulator (hereafter referred to as the MPS450) provides a basis to train, evaluate, and perform preventive maintenance for virtually all patient monitors found in the healthcare industry. This is accomplished with multiple physiological simulations for ECG, blood pressure, respiration, temperature, artifact, and arrhythmia conditions. The MPS450 is a lightweight, battery powered unit that is portable enough to test a patient monitor anywhere the monitor is being used.

The provided document describes the Fluke Biomedical MPS450 Multiparameter Simulator, a device intended to test the operation of patient monitors by simulating various physiological parameters. The submission focuses on demonstrating substantial equivalence to a predicate device, the MedSim300B.

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

Acceptance Criteria and Reported Device Performance

The acceptance criteria for the MPS450 are implicitly defined by comparing its performance specifications to those of the predicate device, the MedSim300B. The differences highlight where the MPS450 either meets or exceeds the predicate's capabilities or where features were deemed "not needed by customers."

Study Information:

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

   • The document states "Laboratory studies have been conducted with a representative patient monitor to verify and validate the MPS450 will perform within its' published specifications."
   • It also mentions "The MPS450 software has been successfully validated to confirm the performance of the device."
   • However, specific numbers for the sample size of "patient monitors" or detailed data provenance (e.g., country of origin, retrospective/prospective) are not provided. The studies are described as "Non-Clinical Test Data" and were conducted in a laboratory setting.

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

   • This information is not provided. As "non-clinical test data" performed in a laboratory, the "ground truth" would likely be established by comparing the MPS450's output against known, highly accurate reference signals or measurements from calibrated laboratory equipment, rather than expert human interpretation.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

   • This information is not provided. Given the nature of a simulator, the "adjudication" would be a technical verification process against defined specifications, not a consensus-based method typically seen in image interpretation or diagnostic studies.

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, an MRMC comparative effectiveness study was not done. This type of study relates to AI-assisted human performance in diagnostic tasks, which is not applicable to a device like the MPS450, designed as a simulator for equipment testing. The MPS450 does not involve "human readers" or "AI assistance" in the diagnostic sense.

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

   • Yes, a standalone performance evaluation was done. The "Non-Clinical Test Data" section explicitly states: "Laboratory studies have been conducted with a representative patient monitor to verify and validate the MPS450 will perform within its' published specifications" and "The MPS450 software has been successfully validated to confirm the performance of the device." This describes the device's inherent functional performance without human intervention in the signal generation process.

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

   • The ground truth for this device would be established by known, precise electrical and physiological signal characteristics generated by the simulator itself and verified against highly accurate measurement equipment. It's a technical "ground truth" based on physics and engineering specifications, not clinical outcomes or expert labels.

7. The sample size for the training set:

   • This device is a simulator, not an AI/machine learning algorithm that requires a "training set" in the conventional sense. Therefore, the concept of a training set sample size is not applicable. The device's "training" refers to its design, programming, and rigorous testing against engineering specifications.

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

   • As explained above, there is no "training set" in the context of machine learning. The device's "ground truth" is based on the fundamental electronic and physiological parameters it is designed to simulate, which are derived from established medical and engineering standards. Its performance is verified against these standards in laboratory testing.

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