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The vital signs monitor is a portable device indicated for use in non-invasively measuring and displaying functional oxygen saturation of arterial haemoglobin (SpO2), pulse rate(PR), Non-invasive measurement of blood pressure(NIBP) of adult and pediatric patients in hospitals, medical facilities, and sub-acute environments. The vital signs monitor is intended for spot-checking and/or continuous monitoring of patients.

The proposed device, MD2000B Vital Signs Monitor, is a portable device, which is intended for measuring and/or cont pulse oxygen saturation (SpO2), pulse rate (PR), systolic pressure (SYS), diastolic pressure (DIA) and mean arterial pressure (MAP) on adult and pediatric.

The provided text describes specific details about a 510(k) submission for the MD 2000B Vital Signs Monitor. However, it does not contain the detailed acceptance criteria for performance, the study that proves the device meets those criteria, or most of the specific study design elements you requested.

The submission states that "Performance testing including clinical and laboratory testing was conducted to validate and verify that the proposed device, MD2000B Vital Signs Monitor met all design specifications and was substantially equivalent to the predicate device." However, the results, acceptance criteria, and methodology of these tests are not present in the provided text.

Therefore, I cannot fulfill your request for a table of acceptance criteria and reported device performance or information regarding sample sizes, ground truth establishment, expert qualifications, adjudication methods, MRMC studies, or standalone performance. This information would typically be found in the detailed test reports attached to the 510(k) submission, not in the summary or cover letters.

Here's what I can extract based on the limited information available in the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

• Not available in the provided text. The document states that "Performance testing... was conducted to validate and verify that the proposed device... met all design specifications..." but does not list those specifications or the quantitative results.

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

• Not available in the provided text. The document mentions "clinical and laboratory testing" but does not specify sample sizes or data provenance (e.g., country of origin, retrospective/prospective).

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

• Not available in the provided text.

4. Adjudication method for the test set:

• Not available in the provided 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:

• Not applicable/available. This device is a vital signs monitor, not an AI-assisted diagnostic imaging device that typically involves human "readers." The text does not mention any MRMC studies or AI involvement.

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

• The device itself is a standalone monitor for vital signs. Performance testing would assess its accuracy in measuring SpO2, PR, and NIBP without human "in-the-loop" interpretation in the way one might consider for an AI CAD system. However, specific performance metrics are not provided.

7. The type of ground truth used:

• Not explicitly stated for the "clinical testing." For vital signs monitors, ground truth for parameters like SpO2, PR, and NIBP is typically established using a reference standard device (e.g., arterial blood gas analysis for SpO2, ECG for PR, invasive arterial line for NIBP, or a highly accurate clinical reference monitor). The document only generally refers to "performance testing including clinical and laboratory testing."

8. The sample size for the training set:

• Not applicable/available. This is a hardware vital signs monitor, not typically a machine learning or AI device that requires a "training set" in the sense of an algorithm being trained on data. Its performance is based on its sensor technology and signal processing, not a trained dataset.

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

• Not applicable/available. (See point 8)

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