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C-Sailor Pro: This device is intended for use in dental oral surgery and dental implant. The main unit is designed to be used with a specific dental micromotor that drives dental handpieces fitted with appropriate tools to cut hard tissues in the mouth. It must only be used in hospital environments, clinics or dental offices by qualified dental personnel.

C-PUMA MASTER: The Dental Electrical Motor is intented for use in dental implant. The main unit is designed to be used with a specific dental micromotor that drives dental handpieces fitted with appropriate tools to the mouth. This device is designed for use by a trained professional in the filed of general dentistry.

The proposed device is used to provide the driving force of dental mobile phone for dental surgery. The functions corresponding to the dental operation steps are preset through the host or foot switch, and the electric energy and signal are transmitted to the motor through the motor cable. The motor drives the mobile phone, and the mobile phone drives the dental operation instruments to perform the operation.

The Dental Implantation Systems(C-Sailor Pro) consists of the Foot Control, AC Electrical Cord, Motor (With Cable), Handpiece Stand, Tube Holder, Spare Fuse, Handle (Foot control), and Stand for use with specific Motors. The Dental Electrical Motors(C-PUMA MASTER) consists of the Control Unit, Electrical Motor, Adaptor, Power Cord, Handpiece Stand and Motor Shaft Plug for use with specific Motors.

The provided text describes a 510(k) premarket notification for "Dental Implantation Systems, Dental Electrical Motors." This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, primarily through non-clinical testing and comparison of technical specifications.

It's crucial to understand that this document does not describe a study involving an AI/ML algorithm or its performance criteria. The device in question is a dental electromechanical system, not a software-as-a-medical-device (SaMD) or an AI-enabled device that would require the types of acceptance criteria and performance studies detailed in the prompt's request.

Therefore, many of the requested points, such as "effect size of how much human readers improve with AI vs without AI assistance," "standalone (i.e. algorithm only without human-in-the-loop performance)," "number of experts used to establish ground truth," and "sample size for training set," are not applicable to this submission.

However, I can extract information related to the closest concept of "acceptance criteria" and "study" as presented for this type of medical device submission.

Acceptance Criteria and Device Performance (as inferred from a 510(k) for an electromechanical device)

For this type of device, "acceptance criteria" are typically the standards compliance and functional equivalence to the predicate device. The "study" proving this involves non-clinical bench testing to demonstrate adherence to specific performance and safety standards, and a comparison of key technical specifications with the predicate device.

Here's an interpretation based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: The document does not specify a "sample size" in terms of patient data or clinical cases, as no clinical study was conducted. For non-clinical bench testing, the "sample size" would refer to the number of devices or components tested. This is typically determined by the testing standard requirements but is not explicitly stated here (e.g., "1 device tested for electrical safety," etc.).
• Data Provenance: The data comes from non-clinical bench testing performed by the manufacturer (Foshan COXO Medical Instrument Co., Ltd.) in China. The testing validates compliance with international standards (e.g., ANSI, IEC, ISO). The tests were conducted to verify that the device "met all design specifications" and was "Substantially Equivalent (SE) to the predicate device." It is retrospective in the sense that it's a report of completed tests, not prospective patient enrollment.

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

• Not Applicable. For this type of electromechanical device and 510(k) submission, "ground truth" as established by medical experts for diagnostic accuracy is not relevant. The "ground truth" in this context is the compliance with engineering and safety standards, verified through objective laboratory measurements and tests, and the functional specifications of the predicate device.

4. Adjudication Method for the Test Set

• Not Applicable. Adjudication methods (like 2+1, 3+1) are used to resolve discrepancies in expert readings for diagnostic accuracy studies. This submission relies on objective engineering and performance conformity with standards and the predicate device.

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

• No. No clinical study, and therefore no MRMC study, was conducted or submitted. The document explicitly states: "No clinical study is included in this submission."

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Not Applicable. This is an electromechanical dental device, not an algorithm. Therefore, "standalone algorithm performance" is not a concept relevant to this submission.

7. The Type of Ground Truth Used

• The "ground truth" for this submission is based on:
  • Compliance with recognized international standards (e.g., ANSI, IEC, ISO) for medical device safety, electrical performance, EMC, biocompatibility, and specific dental equipment requirements.
  • Technical specifications and performance data of the legally marketed predicate device (NAKANISHI INC.'s Surgic Pro, Surgic Pro+ K173905).
  • Bench test results demonstrating the proposed device's adherence to its design specifications and functional equivalence.

8. The Sample Size for the Training Set

• Not Applicable. There is no "training set" in the context of an AI/ML algorithm. This is an electromechanical device.

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

• Not Applicable. As there is no training set, there is no ground truth establishment for one.

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