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The PRO₂ Pulse Reflectance Oximeter System is indicated for the continuous, non-invasive monitoring of functional oxygen saturation of arterial hemoglobin (SpO₂) and pulse rate (PR). The PRO₂ is intended to monitor arterial saturation on the back or forehead locations in pediatric and adult populations. The PRO₂ is for use in hospitals, hospital-type facilities and intra-hospital transport environment.

The Pro2® Pulse Reflectance Oximeter System consists of a reusable sensor that emits red and infrared light, a disposable sensor holder to attach the Sensor and detect red and infrared light, and a monitor incorporating control, processing, and display units. The Pro2® Monitor contains an internal battery to power the unit when AC power is not available. The Monitor displays the percentage of oxygen saturation in the blood, pulse rate, signal quality, and alarms. The Pro2 Sensor geometry includes light sources that emit light in three different wavelengths, and detection areas defined by two photodetector rings arranged concentrically with a photodetector in the center. The rings constitute an annular shape, which allow a multi-path acquisition of signals from a larger tissue area. The Monitor calculates the oxygen saturation based upon specific wavelengths of light detected by its sensor. The Pro2® device has a disposable sensor holder; Model # AHL-200 for adults and pediatric use. The Pro2 Sensor Holder provides optical isolation for external light and is attached to the patient with adhesive that is incorporated as part of the Sensor Holder.

The provided text describes the PRO2 Pulse Reflectance Oximeter System. Here's a breakdown of the requested information based on the text:

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

The provided document states: "The Pro2® Pulse Reflectance Oximeter System performance was tested with clinical data and the results met the acceptable criteria." However, it does not specify what those "acceptable criteria" were nor does it provide a numerical breakdown of the reported device performance against those criteria. It only makes a general statement of compliance.

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

The document mentions "clinical data" was used for testing but does not provide the sample size of the test set nor its provenance (e.g., country of origin, retrospective or prospective nature).

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

This information is not provided in the text.

4. Adjudication method for the test set:

This information is not provided in the text.

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:

This device is a Pulse Reflectance Oximeter System, which is a medical device for measuring oxygen saturation and pulse rate. It is not an AI-assisted diagnostic imaging system, so an MRMC comparative effectiveness study involving human readers and AI assistance is not applicable in this context.

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

The device is inherently a standalone measurement device. It continuously monitors and displays physiological parameters (SpO2 and pulse rate) without requiring human interpretation for its primary function. The "clinical data" testing would have evaluated the device's accuracy in autonomously deriving these measurements, thus representing standalone performance. However, specific details of this testing are not provided beyond the general statement of meeting acceptable criteria.

7. The type of ground truth used:

The document explicitly states the device measures "functional oxygen saturation of arterial hemoglobin (SpO2) and pulse rate." For oximetry devices, the gold standard for ground truth for oxygen saturation is typically arterial blood gas (ABG) analysis. While not explicitly stated, it is a standard practice in oximeter validation to compare the device's readings against ABG measurements.

8. The sample size for the training set:

Pulse oximeters are typically developed through engineering and calibration processes, not machine learning training sets in the modern sense. Therefore, the concept of a "training set" as understood in AI/ML is not applicable to this device.

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

As mentioned above, the concept of a "training set" in the AI/ML context is not applicable. The device's algorithms for calculating SpO2 and pulse rate would be based on established physiological principles of light absorption by oxygenated and deoxygenated hemoglobin, and these would be validated through engineering and clinical testing against reference methods (like ABG) rather than "training" on a dataset with established ground truth in the AI sense.

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