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The L-Bow Arm Restraint fits over the patient's elbow and is intended to limit the patient's movement, particularly away from their face and IV tubing, by keeping their arm in an extended position.

The L-Bow Arm Restraint is constructed of a flexible plastic insert that is covered with soft polyester foam fabric held securely closed with Velcro® fasteners. The L-bow Arm Restraint is wrapped around the patient's elbow and is intended to limit the patient's movement, particularly away from their face and IV tubing, by keeping their arm in an extended position. The Velcro® fasteners are easy to use and offer a secure firm hold. The L-Bow may be machine washed.

The L-Bow is available in three sizes to accommodate various infant, toddler and youth sizes and two sizes to accommodate adults.

This document describes the L-Bow Arm Restraint, a physical medical device, not an AI/ML-driven software device. Therefore, the requested information (acceptance criteria, study details, sample sizes, ground truth establishment, expert involvement, and MRMC studies) which are applicable to AI/ML device evaluations, cannot be found because they are not relevant to this type of product.

The document primarily focuses on establishing substantial equivalence to a predicate device, which is a common regulatory pathway for non-AI/ML medical devices.

Here's what can be extracted from the document based on the provided text, while acknowledging that many of your specific questions are not applicable:

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

   • Acceptance Criteria (Implied for Substantial Equivalence): The device must be identical in intended use, design, materials, manufacturing process, physical and mechanical specifications, and issues of safety and effectiveness to the predicate device. The only permitted difference is revised labeling to comply with agency requirements.
   • Reported Device Performance (as stated in the conclusion): "Based upon the information presented above it is concluded that the proposed Heelbo L-Bow Arm Restraint is safe and effective for its intended use and is substantially equivalent to the predicate device."
   • Note: Specific quantitative performance metrics like accuracy, sensitivity, or specificity are not applicable or reported for this type of physical restraint device in this submission.

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

   • Not applicable. This is a physical device, and the submission does not describe a "test set" in the context of an AI/ML model. The evaluation is based on material properties, design comparison, and intended use to establish equivalence.

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. Ground truth, in the sense of expert consensus on classifications or diagnoses, is not relevant for this device. The "truth" here is whether the physical design and materials perform as intended and are safe.

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

   • Not applicable. No "test set" or adjudication method in the AI/ML context is mentioned.

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 physical device, not an AI-assisted diagnostic or therapeutic tool.

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

   • No. This is a physical device, not an algorithm.

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

   • The "ground truth" for this submission is based on comparison to a legally marketed predicate device and the safety history of its component materials. The claim of safety and effectiveness relies on its similarity to the predicate, whose safety and effectiveness are already established.

8. The sample size for the training set

   • Not applicable. No "training set" is used for a physical device.

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

   • Not applicable. No "training set" is used for a physical device.

In summary, this document is a 510(k) premarket notification for a physical medical device. The evaluation process for such devices focuses on demonstrating substantial equivalence to a predicate device, rather than the performance metrics and study designs typically associated with AI/ML products.

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