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Dental Electric Motor NL400-1 is intended to convert pneumatic output from a dental treatment center to electrical energy to drive an electric micro motor and to operate electrically- driven dental handpieces.it is for use in general dental applications with use of a straight, right-angle, ISO E-type handpiece attachment of equal, gear-reducing, or gear-increasing speed. This system is designed for use by a trained professional in the field of general dentistry.

Dental Electric Motor NL400-1 is a system attached to dental treatment center to operate electrically driven low speed handpieces. It consists of the components Control Unit, Micromotor, Motor Cable, and AC Adaptor. The common gear ratio is 1:1, 16:1 and 1:5, the speed range is from 2000 to 40,000 rpm.

The Control Unit provides the operation panel to achieve different operation functions, such as turn on/off the motor, adjust the motor speed, select memory setting, choose the motor work ratio, and the motor rotate direction.

The Motor Cable is connected to the Control Unit and the Micromotor, and contains lead wires to power the motor and tubing to transmit air/water/spray provided and controlled by the dental treatment center.

The Micromotor is built in with a three-phase DC motor and an LED light, and contains air and water outlet, which can drive the electrically-driven handpiece with the set output parameters and transmits the air/water/spray and lights.

The provided text is a 510(k) summary for a "Dental Electric Motor." This document primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study to prove acceptance criteria for an AI/ML powered medical device. Therefore, the information required to answer your questions regarding acceptance criteria and supporting studies for an AI device is largely not present in this document.

Here's an attempt to answer based on the provided text, highlighting what is missing or not applicable:

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

This document does not define specific performance acceptance criteria or report performance in the typical sense for an AI/ML device (e.g., sensitivity, specificity, AUC). Instead, it conducts a comparison to predicate devices, where "performance" is implicitly evaluated by demonstrating that the subject device meets relevant safety and performance standards (like IEC 60601-1, IEC 60601-1-2, ISO 14457).

The closest to "acceptance criteria" for this conventional device are the general safety and performance standards it was tested against. The "reported device performance" would be that it complies with these standards.

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

This information is not provided because the submission describes testing of a physical device against standards, not an AI/ML model for which "test sets" of data are typically defined in this manner. The testing described is lab bench testing of the physical hardware.

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)

This is not applicable as there is no AI/ML model and thus no "ground truth" establishment in the context of expert review of data.

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

Not applicable for a physical device substantial equivalence submission.

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. This device is a dental electric motor, a piece of hardware, not an AI-assisted diagnostic or treatment planning tool.

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

Not applicable. There is no algorithm or AI component in the device description.

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

Not applicable. For a physical device, compliance with standards and functional specifications constitutes the "truth" or verification of its performance.

8. The sample size for the training set

Not applicable. This document pertains to a physical dental electric motor, not an AI/ML algorithm requiring a training set.

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

Not applicable. There is no AI/ML algorithm or training set discussed.

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Endo Motor T-Fine-II is indicated for use in standard endodontic procedures using rotary endodontic files for mechanical and rotary preparation of the root canal.

Cordless endo motor is a professional equipment for root canal preparation. It is a drive for contra angle headpiece which is designed to assist dentists and dental surgeons perform standard endodontic procedures. The endo motor consists of Cordless main unit, Charger station and Adapter. It is intended to use with FDA cleared contra-angle handpiece (transmission ratio of contra angle handpiece: 16:1) which would hold the drill bit or file. However the device do not included the contra angle handpiece and files. The Endo smart is equipped with rechargeable Li-ion battery, which can be recharged using the provided charge station. By means of the different buttons on the main unit, the user could control various functions in the device, such as On/off, Speed, Torque and auto-reverse/auto forward mode. The Endo motor is not sterile and cannot be autoclaved.

The provided document is a 510(k) summary for the Endo Motor Model: T-Fine-II. This type of submission is for demonstrating "substantial equivalence" to a legally marketed predicate device, rather than proving safety and efficacy through extensive clinical studies and setting specific acceptance criteria commonly seen for novel devices or highly complex AI/ML devices.

Therefore, the document does not contain the detailed information typically associated with acceptance criteria and a study proving a device meets these criteria for an AI/ML-based medical device. Specifically, it lacks information on:

• A table of acceptance criteria and reported device performance for an AI/ML system (as this is a mechanical dental device).
• Sample sizes for test sets, data provenance, expert ground truth establishment, or adjudication methods (as no clinical or AI-specific validation studies were conducted for this device beyond bench testing for electrical safety and EMC, and software verification/validation).
• MRMC studies, standalone algorithm performance, or specific ground truth types (pathology, outcomes data) relevant to AI/ML.
• Training set details for an AI/ML model.

What the document does provide in terms of "acceptance criteria" and "proof":

For this specific device, the "acceptance criteria" are compliance with relevant safety and performance standards for dental electrical equipment and demonstrating substantial equivalence to a predicate device. The "proof" involves a combination of bench testing and comparison.

Here's an interpretation based on the provided text, focusing on the available information:

1. Acceptance Criteria and Reported Device Performance (as inferred from the document's purpose):

2. Sample Sizes and Data Provenance:

• No specific sample sizes for test sets (patients/images) are mentioned because this device's validation is primarily through bench testing against engineering standards and comparison to a predicate, not clinical trials or AI/ML model validation with patient data.
• The document implies manufacturing is in Foshan, Guangdong, China (manufacturer location).
• The testing appears to be bench testing for engineering compliance, not retrospective or prospective clinical data collection.

3. Number of Experts and Qualifications:

• Not applicable. This information is relevant for studies establishing ground truth for AI/ML or clinical interpretation, which were not conducted or required for this device's 510(k) submission.

4. Adjudication Method:

• Not applicable. No clinical data interpretation requiring adjudication was performed or described.

5. MRMC Comparative Effectiveness Study:

• No. This type of study is for evaluating human reader performance with and without AI assistance, which is not relevant to this mechanical dental device.

6. Standalone (Algorithm Only) Performance:

• Not applicable. This device is a mechanical Endo Motor, not an AI algorithm. Its software is for controlling the device's functions, not for diagnostic or predictive tasks that would have standalone performance metrics.

7. Type of Ground Truth Used:

• No "ground truth" in the AI/ML sense (e.g., pathology, outcomes data, expert consensus) was used. The validation relies on:
  • Engineering Standards Compliance: The standards (IEC 60601 series, AAMI TIRs) themselves define the "ground truth" for safety and performance (e.g., passing electrical leakage tests, demonstrating specific torque output).
  • Predicate Device Comparison: The predicate device (K090931) serves as a benchmark for "equivalent" safety and effectiveness.

8. Sample Size for Training Set:

• Not applicable. There is no AI/ML model being trained with patient data for this device.

9. How Ground Truth for Training Set Was Established:

• Not applicable. As there is no AI/ML model training, this step is irrelevant.

In summary, the provided document is a 510(k) summary for a Class I mechanical dental device. The "acceptance criteria" and "proof" presented align with the regulatory pathway for such devices, focusing on compliance with recognized electrical and mechanical safety standards and demonstrating substantial equivalence to a predicate device, rather than detailed clinical performance studies or AI/ML validation.

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For light curing polymerization of dental composites, luting materials, cements and other light cured materials.

LED Curing Light is used to restore teeth on dental patient. The device can only be used by the dentist who is qualified and well trained. This product is used on dental patient in the place of hospital or professional medical site.

LED Curing Light adopts the principle of ray radiation to solidify the light sensitive resin by shooting at it in a short time. It is composed of high-power LED, main unit, curing light shield, charger and charge station. The main unit contains the ON/OFF button, display screen, mode button and time button.

LED Curing Light provides TURBO mode and NORMAL mode with different preset exposure time. The high-power LED can produce visible blue light in the 430nm to 490nm waveband of spectrum with a power density of 1000m W/cm² to 1800m W/cm². Using different modes gives dental professionals the flexibility to polymerize virtually almost all types of composites, boding agents and sealants available in the market.

The enclosure of main unit was composed of ABS material and Aluminum, and the light guide base (patient contact part) was made from ABS material.

Here's a breakdown of the acceptance criteria and study information for the LED Curing Light, Model CV-215, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a Class II medical device, the "acceptance criteria" are primarily based on established performance standards and comparability to a predicate device, rather than specific numerical thresholds for diagnostic accuracy. The reported device performance is demonstrated through its compliance with these standards.

2. Sample size used for the test set and the data provenance
The document does not describe a clinical study with a "test set" in the traditional sense of patient data. The evaluations were primarily conducted through lab bench testing by the manufacturer against recognized industry standards. Therefore, there is no information on sample size for a test set or data provenance from patient data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. The evaluations were based on compliance with engineering and biocompatibility standards, not expert-adjudicated ground truth from patient data.

4. Adjudication method for the test set
Not applicable, as there was no test set requiring ground truth adjudication.

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 MRMC comparative effectiveness study was conducted. This device is an LED Curing Light, not an AI-powered diagnostic tool for human readers.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a physical dental device, not an algorithm, so standalone performance in that context is not relevant.

7. The type of ground truth used
The "ground truth" for the device's acceptable performance is defined by its compliance with international and national standards for safety (electrical, EMC, biocompatibility) and performance (light output for dental curing). These standards outline measurable parameters and testing methodologies.

8. The sample size for the training set
Not applicable. This device does not involve a "training set" in the context of machine learning.

9. How the ground truth for the training set was established
Not applicable, as there was no training set.

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Dental high speed handpiece: Is intended for removing carious material, reducing hard tooth structure, cavity and crown preparations, removal of fillings, finishing tooth preparations, restoration and polishing teeth. The device is designed for use by a trained professional in the field of general dentistry. Dental low speed handpiece: Is intended for preparing dental cavities and crown for restorations, and teeth cutting, restorations and polishing teeth. The device is designed for use by a trained professional in the field of general dentistry.

Not Found

The provided document is a 510(k) premarket notification letter from the FDA for a Dental high speed handpiece and Dental low speed handpiece. This document primarily focuses on regulatory approval based on demonstrating substantial equivalence to predicate devices, rather than presenting a performance study with acceptance criteria for an AI/CAD-based medical device.

Therefore, the information required to answer your specific questions about acceptance criteria and a study proving a device meets them (especially in the context of an AI/CAD-based device) is not contained within these documents.

The document states:

• Device Name: Dental high speed handpiece, Dental low speed handpiece
• Regulation Number: 21 CFR 872.4200
• Regulation Name: Dental Handpiece And Accessories
• Regulatory Class: Class I
• Product Code: EFB

This is for a mechanical dental instrument, not a software or AI-driven diagnostic device. The approval is based on demonstrating substantial equivalence in design, materials, and functional principles to existing predicate devices, not on a performance study against specific acceptance criteria for diagnostic accuracy or clinical outcomes.

To provide a comprehensive answer to your questions, a different type of FDA submission document (e.g., a PMA, or a more detailed 510(k) submission for an AI/CAD device that includes clinical study data) would be needed.

Therefore, I cannot populate the table or answer the specific questions based on the provided text.

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