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The CNAP® Monitor 500 HD is intended for the non-invasive continuous monitoring of blood pressure, and the determination of associated derived hemodynamic parameters including cardiac output within hospitals. The device displays the blood pressure waveform, trends, and numeric for blood pressure, pulse rate, and associated derived hemodynamic parameters. Alarms are generated for blood pressure parameters and pulse rate. The CNAP® Monitor 500 HD is to be used for adults and is to be operated by healthcare professionals.

The CNAP® Monitor 500 HD is a stand-alone device for continuous non-invasive blood pressure and hemodynamic monitoring with alarming functionality. The continuous non-invasive blood pressure is measured on the patient's finger using a double finger cuff, the oscillometric blood pressure measurement function (Advantage 2.0 OEM module by SunTech Inc.) is used for intermittent calibration of the continuous blood pressure curve. Medium priority alarming can be set for blood pressure beat values and pulse rate.

Based on the provided text, the CNAP® Monitor 500 HD is a blood pressure and hemodynamic monitoring system. The acceptance criteria and the study proving it meets these criteria are primarily focused on its substantial equivalence to predicate devices rather than independent performance metrics against a defined standard.

Here's the breakdown of the information provided, or lack thereof, regarding a detailed AI/algorithm study:

Key Observation: The document describes a medical device, not an AI/ML algorithm. The performance data section focuses on electrical safety, electromagnetic compatibility, mechanical and acoustical testing, and software verification/validation, along with a claim of substantial equivalence to predicate devices based on clinical testing using "measurement data from different sources." There is no indication of an AI/ML algorithm being developed or studied for this device, nor is there a study described that would fit the typical criteria for AI/ML performance evaluation (e.g., sensitivity, specificity, AUC, human reader improvement studies).

Therefore, I will answer the questions based on the closest relevant information provided, while highlighting where the requested details for an AI/ML study are not applicable or not present in the document.

Acceptance Criteria and Device Performance (based on provided text)

The document focuses on demonstrating substantial equivalence to predicate devices. This is the primary "acceptance criterion" from a regulatory perspective. The performance data presented are primarily related to safety, electromagnetic compatibility, and software verification rather than specific diagnostic accuracy metrics for an AI.

Given the nature of the device (a non-invasive blood pressure and hemodynamic monitor), the key performance "acceptance" would be its accuracy in measuring blood pressure and derived hemodynamic parameters, and its safety. However, the document does not provide a table of precise acceptance criteria with numeric targets (e.g., ±5 mmHg for BP accuracy) or how the specific device performance was measured against such targets for the new device. Instead, it relies on demonstrating comparable performance to predicate devices.

Table of Acceptance "Criteria" (based on regulatory submission principles for this device type) and Reported Device "Performance":

Details Specific to AI/ML Studies (Not Applicable or Not Provided)

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

   • The document states "For clinical testing and evaluation measurement data from different sources was used to demonstrate that the device is substantially equivalent to the predicate devices."
   • No specific sample size for a "test set" (as understood in AI/ML validation) is provided.
   • No data provenance (e.g., country of origin, retrospective/prospective) is specified for this "measurement data." This is typical for a traditional medical device submission focused on equivalence, rather than a novel AI algorithm.

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

   • Not applicable / Not provided. The device is a monitor that directly measures/derives physiological parameters, not an diagnostic imaging AI that requires expert labeling for ground truth. Ground truth for blood pressure and hemodynamic parameters in a device like this would typically involve invasive measurements (e.g., arterial line for BP) or established reference methods, not expert consensus on image labels. The document does not describe how this "measurement data" was validated against a gold standard.

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

   • Not applicable / Not provided. This method is relevant for studies involving human interpretation or labeling of data, especially in AI development for image analysis or diagnostics. It does not apply to a physiological monitoring device undergoing substantial equivalence testing.

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:

   • Not applicable / Not done. An MRMC study is specific to AI-assisted diagnostic tools where human interpretation is part of the workflow. This device is a physiological monitor, not an AI that assists human readers.

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

   • Not applicable / Not explicitly detailed as an AI algorithm study. The device itself is a "standalone" monitor that performs continuous non-invasive blood pressure and hemodynamic monitoring. The "performance data" section broadly covers its functional performance, but not in the context of an isolated AI algorithm. The device's "algorithms" are for signal processing and calculation of physiological parameters, which are validated as part of the overall device functionality, not typically as distinct "standalone AI" studies in the regulatory sense described.

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

   • Not explicitly stated in detail. For a non-invasive blood pressure device, the gold standard (ground truth) is typically invasive arterial blood pressure monitoring. For hemodynamic parameters, it would be direct measurement methods like thermodilution (e.g., using a Swan-Ganz catheter). The document only generically refers to "measurement data from different sources."

7. The sample size for the training set:

   • Not applicable / Not provided. This device is not described as involving a machine learning model that would require a distinct "training set" for its primary function. While there might be internal development data used to optimize signal processing algorithms, it is not presented as an AI/ML training regimen.

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

   • Not applicable / Not provided. As no AI/ML training set is described, this question is not relevant to the provided text.

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The CNAP Monitor 500 is intended for the monitoring of non-invasive continuous blood pressure and pulse rate in hospitals, clinical institutions, medical practices and outpatient settings. The device displays the blood pressure waveform and generates trends, beat numerics and alarms for the parameters blood pressure and pulse rate. The CNAP Monitor 500 is to be used for adults and pediatric patients from the age of 4 year and is to be operated by physicians and other medical professional staff.

The CNAP™ Monitor 500 is a device for continuous non-invasive blood pressure monitoring. The device measures continuous and oscillometric blood pressure as well as pulse rate. CNAP is a joint solution, where absolute blood pressure values are coming from an integrated OEM oscillometric blood pressure device and beat-to-beat changes as well as waveform are measured with the CNAP finger sensor. Finger-BP is automatically calibrated to absolute NIBP-values. Immediately after a NIBP, the CNAP computer puts systolic and diastolic finger BP on the same level as NIBP values. NIBP calibrations can be obtained ipsilateral as well as contralateral to the CNAP-cuff.

The CNAP Monitor 500 device is a non-invasive continuous blood pressure monitoring system. The provided text indicates that the device underwent functional and clinical performance testing to demonstrate equivalence to its predicate device.

1. Table of Acceptance Criteria and Reported Device Performance:

The document explicitly states that "Bench Testing (for continuous blood pressure measurement functionality)" and "Clinical Performance Testing (for oscillometric NIBP measurement functionality)" were conducted. However, it does not provide specific numerical acceptance criteria or detailed results for either of these tests. It only states that the device "has successfully undergone safety testing as well as functional testing to demonstrate equivalence to its predicate device." and "The results of this testing demonstrates that the device is safe and effective and substantially equivalent to its predicate device."

Without specific numerical criteria or performance metrics, a table cannot be accurately generated.

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

The document mentions "Clinical Performance Testing (for oscillometric NIBP measurement functionality)" but does not specify the sample size used for this test set or the country of origin of the data. It also does not explicitly state whether the study was retrospective or prospective.

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

The document does not provide information regarding the number of experts used to establish ground truth or their qualifications.

4. Adjudication Method for the Test Set:

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

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

A MRMC comparative effectiveness study was not performed or described in the provided text. The document focuses on demonstrating substantial equivalence to a predicate device, rather than comparing human reader performance with and without AI assistance.

6. Standalone Performance Study:

The document discusses "Bench Testing (for continuous blood pressure measurement functionality)" and "Clinical Performance Testing (for oscillometric NIBP measurement functionality)," which suggest standalone performance evaluations. However, specific details about these studies and their outcomes (beyond general success and equivalence) are not provided. The device itself is an algorithm-driven monitor, implyiung its standalone performance is what was evaluated against the predicate.

7. Type of Ground Truth Used:

While the document states that clinical performance testing was done for oscillometric NIBP measurement, it does not explicitly define the "ground truth" used for these tests. For NIBP, the ground truth would typically be a more invasive or highly accurate reference measurement (e.g., intra-arterial blood pressure), but this is not specified. The phrasing "equivalence to its predicate device" implies the predicate device's measurements served as a reference point for comparison.

8. Sample Size for the Training Set:

The concept of a "training set" is usually associated with machine learning or AI model development. While the CNAP Monitor 500 uses algorithms (e.g., for beat-to-beat changes and waveform measurement, and automatic calibration), the document does not provide any information about a training set size or the development of such algorithms. It's possible the algorithms were developed and validated internally without a formally described "training set" in the context of this 510(k) summary.

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

As no training set is described, the method for establishing its ground truth is also not mentioned.

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