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The Dental Handpiece, Wireless Endodontic Handpiece, endoit, model no. (EH-C500) is intended for the removal of carious material, reducing of hard tooth structure, cavity and crown preparations, root canal preparations, removal of fillings, processing and finishing tooth preparations, and restorations for polishing teeth.

Dental Handpiece, Wireless Endodontic Handpiece, endoit (model number: EH-C500) consists of a Main Body, connectable Contra Angle, Charging Cradle, and AC/DC Adapter. The Main Body of the handpiece is used for transmitting rotational force required in general dental treatment. The torque transmitted from a wireless electric micro-motor gets further transmitted to the joint part of the device. The rotational force is then decelerated according to the speed reducer of the gear which is transmitted to the head of the dental handpiece. The rotational force is transmitted under the permitted rotation mechanism.

Based on the provided FDA 510(k) summary, the device in question is a Dental Handpiece, Wireless Endodontic Handpiece, endoit (model number: EH-C500). This document primarily focuses on demonstrating substantial equivalence to predicate devices, rather than presenting a clinical study of AI performance. Therefore, many of the typical acceptance criteria and study details for AI/ML-driven medical devices (e.g., Sensitivity, Specificity, MRMC studies, ground truth establishment for images) are not applicable here.

This device is not an AI/ML-driven diagnostic or therapeutic device. It is a traditional medical device (a dental handpiece). The "acceptance criteria" and "study" described in the document relate to engineering and performance testing to ensure the device meets established safety and performance standards for dental handpieces, and demonstrates substantial equivalence to predicate devices.

Here's an attempt to answer your questions based on the provided text, while noting where AI/ML-specific criteria are not relevant:

Acceptance Criteria and Device Performance for the Dental Handpiece, Wireless Endodontic Handpiece, endoit (Model EH-C500)

This device is a dental handpiece, and its acceptance criteria are primarily related to its mechanical, electrical, and material safety and performance, rather than diagnostic accuracy as would be the case for an AI/ML algorithm. The "study" described is a series of engineering design verification and validation tests, along with biocompatibility testing.

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a non-AI device, the acceptance criteria are not typically expressed as traditional metrics like sensitivity, specificity, or AUC. Instead, they are related to compliance with recognized standards and successful completion of pre-defined engineering tests. The document states that "The favorable test results of the proposed device which confirmed to meet the FDA recognized standards as well as ISO standard demonstrate that the proposed Dental Handpiece, Wireless Endodontic Handpiece, endoit (model number: EH-C500) retains the substantially equivalent profile in safety and essential performance of medical electrical equipment as the predicate (K220577) Dental Handpiece model CA160L and predicated (K123582) Endo A Class."

Here's a summary of the types of criteria and the general performance statement:

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

• Sample Size: Not explicitly stated as a number of "cases" or "patients" as would be for an AI study. The testing for this device involves:
  • Biocompatibility: Likely conducted on samples of device materials, not a "test set" of patients. The document references testing done on a previous predicate device (K192809) which results were applied.
  • Design Verification and Validation: This typically involves testing a certain number of manufactured units of the device (e.g., several units tested for rotational speed, noise, durability, etc.). The exact number is not specified in the summary but would be detailed in the full test reports.
  • Electrical/EMC Testing: This would be conducted on device units in specialized labs.
• Data Provenance: Not applicable in the sense of patient data origin. The testing is laboratory and bench testing of the physical device and its materials. This is effectively "prospective" testing of the new device's engineering performance.

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

• Not applicable. For this type of device, "ground truth" is established by engineering specifications, recognized industry standards (e.g., ISO, IEC), and scientific principles, not by expert interpretation of clinical data or images. The "ground truth" is that the device must meet the specified performance parameters (e.g., a certain rotational speed, torque, noise level) and safety requirements (e.g., electrical safety, material biocompatibility). These are verified through objective measurements and accepted testing methodologies.

4. Adjudication Method for the Test Set

• Not applicable. As there are no human interpretations of data (e.g., images) that require consensus, there is no need for an adjudication method. Test results are objective measurements against established engineering and safety thresholds.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and Effect Size

• No. This is not an AI/ML diagnostic device, so an MRMC study comparing human reader performance with and without AI assistance is not relevant or performed for this type of 510(k) submission.

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

• No. This is a hardware medical device with an electromechanical function, not a software algorithm. Therefore, "standalone algorithm-only performance" is not a relevant concept for this product. The device's "standalone performance" is its ability to meet its engineering and safety specifications on its own, which is what the various design verification tests confirm.

7. The Type of Ground Truth Used

• Engineering Specifications and Recognized Standards: The "ground truth" is defined by the requirements outlined in the relevant ISO and IEC standards (e.g., ISO 14457 for handpieces and motors, IEC 60601-1 for electrical safety, ISO 10993-1 for biocompatibility) and the manufacturer's own pre-defined design requirements for functional performance (e.g., rotational speed range, noise limits). Successful completion of tests against these standards constitutes meeting the "ground truth."

8. The Sample Size for the Training Set

• Not applicable. This device does not use an AI/ML algorithm that requires a "training set" of data.

9. How the Ground Truth for the Training Set was Established

• Not applicable. As there is no AI/ML algorithm or training set, this question is not relevant.

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