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The monitors are intended to be used for monitoring, storing, recording of, and to generate alarms for, multiple physiological parameters of adults, pediatrics and neonates. The monitors are intended for use by trained healthcare professionals in hospital environments.

The monitored physiological parameters include: ECG, respiration (RESP), temperature (TEMP), oxygen saturation of arterial blood (SpO2), pulse rate (PR), non-invasive blood pressure (NIBP), invasive blood pressure (IBP), carbon dioxide (CO2), cardiac output (C.O.).

The arrhythmia detection and ST Segment analysis are intended for adult patients. The monitors are not intended for MRI environments.

The X8 X10 X12 Patient Monitor (hereinafter called X series) can perform long-time continuous monitoring of multiple physiological parameters. Also, it is capable of storing, displaying, analyzing and controlling measurements, and it will indicate alarms in case of abnormity so that doctors and nurses can deal with them in time.

The provided text is a 510(k) Premarket Notification summary for the Edan Instruments, Inc. Patient Monitor (Models X8, X10, X12). This document focuses on demonstrating substantial equivalence to a predicate device, rather than proving the device meets specific acceptance criteria through a clinical study of an AI algorithm's performance.

Therefore, the information required to answer the prompt (acceptance criteria, study details for an AI algorithm, expert ground truth, MRMC study, standalone performance, training set details) is not present in the provided document. The document describes a traditional medical device (patient monitor) and its compliance with general safety and performance standards.

Here's a breakdown of why the requested information cannot be extracted from the given text:

1. Table of acceptance criteria and reported device performance: The document lists various physiological parameters (ECG, RESP, NIBP, SpO2, Temp, IBP, CO2, C.O.) and their measurement ranges and accuracies, comparing them to a predicate device. These are performance specifications, not "acceptance criteria" in the context of an AI algorithm's performance study. There's no specific numerical performance target for an AI algorithm provided.

2. Sample size used for the test set and the data provenance: Not applicable. The document refers to "bench testing" and "software verification and validation testing," which are not described as using specific test sets of patient data for AI algorithm evaluation.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth establishment by experts is relevant for AI algorithm studies, which are not detailed here.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable. This pertains to expert review in AI studies, which is not described.

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. No MRMC study is mentioned. This device 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: Not applicable. No standalone algorithm performance is described. The device's "arrhythmia detection and ST Segment analysis" are features of the patient monitor, not explicitly a separate AI algorithm being evaluated for standalone performance.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable. The "ground truth" for the device's measurements (e.g., blood pressure accuracy) would be derived from calibrated reference instruments, not expert consensus or pathology in the context of an AI algorithm.

8. The sample size for the training set: Not applicable. There is no mention of a training set for an AI algorithm.

9. How the ground truth for the training set was established: Not applicable. There is no mention of a training set for an AI algorithm.

In summary, the provided FDA 510(k) summary for the Edan Instruments, Inc. Patient Monitor focuses on establishing substantial equivalence to existing predicate devices based on design features, performance specifications (e.g., accuracy of physiological measurements), and compliance with electrical safety and EMC standards. It does not describe a study involving an AI algorithm that would require the detailed information requested in the prompt.

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