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Indicated for use by health care professionals whenever there is a need for monitoring and recording of and to generate alarms for multiple physiological parameters of adults, pediatrics and neonates in a hospital environment and during transport situations within and outside of hospital environment.

The modified Philips MP5 IntelliVue Patient Monitor is substantially equivalent to previously cleared Philips MP5 IntelliVue Patient Monitor marketed pursuant to K062392, the M3/M3046A Compact Portable Patient Monitor marketed pursuant to K971910, K992273, K030973, and the Welch Allyn SureTemp® Plus thermometer module marketed pursuant to K031740. The modification adds the capability to the MP5 patient monitor to interface to the legally marketed Welch Allyn SureTemp® Plus thermometer module. The modification also adds the capability to the MP5 patient monitor to function in a transport environment outside of hospitals, such as a road ambulance, airplane or helicopter.

The provided document is a 510(k) summary for the Philips MP5 IntelliVue Patient Monitor. It describes the device, its intended use, and its substantial equivalence to predicate devices. However, it does not contain the specific details about acceptance criteria, device performance, sample sizes, ground truth establishment, or expert qualifications that you requested for a detailed study description.

The document broadly states: "Verification, validation, and testing activities establish the performance, functionality, and reliability characteristics of the modified device with respect to the predicate. Testing involved system level tests, performance tests, EMC, safety and environmental testing from hazard analysis. Pass/Fail criteria were based on the specifications cleared for the predicate devices and test results showed substantial equivalence. The results demonstrate that the modified Philips MP5 IntelliVue Patient Monitor meets all reliability requirements and performance claims."

This statement is very general and does not provide the specific quantitative information you are looking for. It confirms that testing was done and performance claims were met, but it lacks the detailed breakdown of the acceptance criteria and results.

Therefore, I cannot populate the table or answer most of your detailed questions based solely on the provided text. The document is a regulatory submission summary, not a detailed technical study report.

Here's what I can extract and what is missing:

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

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Sample Size (Test Set): Not specified.
• Data Provenance: Not specified. The device manufacturer is in Germany, but the testing details are not provided.
• Retrospective/Prospective: Not specified.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not applicable/Not specified. This document pertains to a patient monitor, which would likely be evaluated against reference standards (e.g., highly accurate sensors, calibrated equipment) rather than expert human interpretation for ground truth.

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

• Not applicable/Not specified. (See point 3)

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

• Not applicable/Not specified. This is a patient monitor, not an AI-assisted diagnostic tool for human readers.

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

• The testing described, "system level tests, performance tests, EMC, safety and environmental testing," generally refers to standalone device performance against specifications. There's no mention of a human-in-the-loop study.

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

• Not explicitly defined, but for patient monitors, the "ground truth" for physiological parameters (like ECG, blood pressure, temperature) would typically be established by highly accurate and calibrated reference measurement devices.

8. The sample size for the training set

• Not applicable/Not specified. This device is not described as having a "training set" in the context of machine learning or AI. Its core technology would be signal processing and hardware integration, not learned algorithms from a dataset.

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

• Not applicable/Not specified. (See point 8)

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The Propaq LT 802 series monitors are highly portable devices intended to be used by clinicians and medically qualified personnel for single or multi-parameter vital signs monitoring of ambulatory and non-ambulatory neonate, pediatric and adult patients. These monitors are indicated for ECG, noninvasive blood pressure (NIBP), respiration and SpO2. The most likely locations for patients to be monitored by this device are hospital general medical, telemetry, and intermediate care floors, hospital emergency departments, transport, emergency medical services and other healthcare applications. The monitors may be used as standalone devices or as devices networked to an Acuity " central station through wireless communication over Welch Allyn's FlexNet™ network.

This device is available for sale only upon the order of a physician or licensed health care professional.

The Propaq LT 802 Series of monitors are small, lightweight patient monitoring devices intended to be used by clinicians and medically qualified personnel for monitoring of noninvasive Interious bo adou by cirite, ECG, noninvasive functional oxygen saturation of arteriolar hemoglobin (SpO2) in ambulatory, non-ambulatory and transport environments

This document is a 510(k) summary for the Welch Allyn Propaq LT 802 Series vital signs monitor. It describes the device, its intended use, and provides a statement of its substantial equivalence to predicate devices. However, it does not contain the detailed performance study results, acceptance criteria, or ground truth information typical for an AI/ML device submission.

Therefore, I cannot fully complete the requested table and sections based on the provided text.

Here's what I can infer and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Missing Information:

• Specific numerical acceptance criteria for each vital sign parameter (ECG, NIBP, Respiration, SpO2).
• Quantified performance results (e.g., mean absolute difference for NIBP, accuracy percentages for heart rate, SpO2 accuracy over specific ranges).

Study Related Information (Based on what can be inferred/is missing):

• Study That Proves the Device Meets Acceptance Criteria: The document mentions that the device "will be tested in accordance with the [test methods mentioned elsewhere in the submission] using production equivalent units prior to release to market." This indicates that verification and validation testing was planned or executed, but the details of these studies are not present in this summary. The summary focuses on regulatory compliance and substantial equivalence rather than detailed performance study reports.

• 2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective):

  • Not specified in the document. The document does not provide details on specific test sets, sample sizes, or data provenance.

• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience):

  • Not applicable/Not specified. For a vital signs monitor, ground truth is typically established by reference devices (e.g., a highly accurate NIBP simulator, a SpO2 simulator, or a known ECG waveform generator) rather than expert consensus on medical images or diagnoses. The document does not mention experts for ground truth establishment.

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

  • Not applicable/Not specified. Adjudication methods are typically used in studies involving subjective interpretation (e.g., image reading). For vital sign measurements, accuracy is usually determined against a validated reference.

• 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:

  • No. This is a vital signs monitor, not an AI-powered diagnostic device. MRMC studies are not relevant in this context.

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

  • Yes, implicitly. The device itself is a standalone vital signs monitor. Its performance would be evaluated as an algorithm/device-only performance against reference standards. This is the primary mode of evaluation for such devices.

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

  • Likely a combination of physical simulators and clinical studies against reference devices. While not explicitly stated, for vital signs monitors, ground truth typically comes from:
    • For NIBP: Cuff inflation measurements against a reference manometer or invasive arterial pressure measurements.
    • For ECG: Standardized ECG waveforms, or simultaneous recordings with a highly accurate reference ECG device.
    • For SpO2: Controlled hypoxia studies against a CO-oximeter, or testing with calibrated SpO2 simulators.
  • The document mentions "production equivalent units," implying testing against established standards.

• 8. The sample size for the training set:

  • Not applicable/Not specified. This is not an AI/ML device that requires a "training set" in the conventional sense. The device's algorithms for processing vital signs are likely based on established physiological principles and signal processing, not statistical learning from a large training dataset.

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

  • Not applicable/Not specified. As it's not an AI/ML device relying on a training set, this question is not relevant.

Summary of Device and Regulatory Context:

This 510(k) summary is for a traditional medical device (vital signs monitor). The regulatory pathway focuses on demonstrating "substantial equivalence" to existing legally marketed predicate devices. This typically involves showing that the new device has the same intended use, similar technological characteristics, and raises no new questions of safety and effectiveness compared to the predicate. The performance data, while crucial for the submission, is usually summarized or referenced rather than detailed in the public 510(k) summary.

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