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The EQ-M motorized handpiece can be used to enlarge and prepare root canals, remove gutta-percha points. When connected to Apex locator (EQ-PEX), the EQ-M can be used to measure the length of root canals.

EQ-M is micro motor needed to make canal enlargement for root canal treatment. The battery in the motor handpiece is used as a power source and the rotational power generated by rotating the micro motor is transmitted to the crown gear of the angle head through the bevel gear and shaft. The resulting rotational power is transmitted to the file to rotate the file. When connected to Apex Locator (EQ-PEX), the EQ-M indicates the position of the file tip inside the root canal.

The EQ-PEX is Electronic Apex Locator and accessories to be used to treat patients. It consists of the main body and lip hook, probe cord. The device is used to track the position of the file in the root canal based on the impedance of two different frequencies.

The screen displays measurement information of the root canal length at the current location of the file and displays a number and graph. Stainless steel hand files are intended to be used with the subject device. Lip hook is intended to be placed on the opposite lip of the tooth to be worked on. The file is slowly inserted into the root canal. When the file approaches the apex reference value and alarm will beep and the text apex will appear on the measurement screen.

The document provided is a 510(k) summary for a dental device, EQ-M, and does not contain the requested information regarding acceptance criteria and a study proving the device meets those criteria, especially in the context of an AI/ML-based device evaluation.

The 510(k) summary focuses on demonstrating substantial equivalence to predicate devices based on intended use, technological characteristics, and performance properties, rather than establishing and testing against specific acceptance criteria for AI/ML performance.

Therefore, I cannot provide the requested table and study information based on the given text.

Specifically, the document lacks information on:

1. Acceptance criteria and reported device performance (for AI/ML): There are no specific quantitative acceptance criteria or corresponding reported performance metrics (e.g., sensitivity, specificity, AUC) for an AI/ML component. The "Performance 2 - apex locator" listed refers to the accuracy of the root apex locator function, which is a hardware/software integration feature, not an AI/ML performance metric.
2. Sample size for the test set and data provenance: No information is provided about a test set for evaluating an AI/ML component.
3. Number of experts and qualifications for ground truth: No mention of experts establishing ground truth for evaluating an AI/ML component.
4. Adjudication method: Not applicable as there's no AI/ML test set adjudication described.
5. Multi-Reader Multi-Case (MRMC) comparative effectiveness study: No such study is mentioned or implied.
6. Standalone (algorithm only) performance: No standalone performance of an AI/ML algorithm is described.
7. Type of ground truth used: Not applicable as there's no AI/ML component evaluation described.
8. Sample size for the training set: Not applicable as there's no AI/ML component described.
9. How ground truth for the training set was established: Not applicable as there's no AI/ML component described.

The non-clinical studies mentioned are related to electrical safety, electromagnetic compatibility, usability, software lifecycle, battery safety, and biocompatibility, which are standard for medical device approvals, but do not pertain to the performance evaluation of an AI/ML system.

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