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The Medrobotics Flex® Robotic System is intended to provide robot-assisted control of the Flex® Transabdominal Drive.

The Flex® Transabdominal Drive is intended to be used with ancillary equipment for endoscopic surgery. The Flex® Transabdominal Drive is indicated to provide robot-assisted visualization within the thoracic and abdominal cavities including female reproductive organs.

This instrument must not be used for observation of the heart and must not contact the heart or any area near the heart. This instrument must not contact with any device or therapeutic accessory that contacts the heart or any area near the heart.

The Flex® Robotic System and Flex® Transabdominal Drive make up the Flex Robotic Transabdominal System. The system includes three (3) major components: Flex Console; Flex Cart/Base; and Flex Transabdominal Drive with camera. The Flex console is the primary user interface for controlling functionality of the Flex Transabdominal System. The Flex Cart/Base positions and manipulates the Flex Transabdominal Drive. The Flex Camera is a sterile, reusable component that is attached to the Flex Transabdominal Drive. The Flex Transabdominal Drive is attached to the Flex Base and is introduced to the patient through a commercially available trocar. The physician provides input to manipulate the Flex Transabdominal Drive via the Physician Controller located on the Flex Console. The input from the Physician Controller generates the desired motion in the Flex Base resulting in driving and articulation of the endoscope inside the patient's anatomy. Manipulation of available camera controls allows the physician to achieve appropriate visualization of the target site. The Flex® Robotic Transabdominal System is an operatorcontrolled flexible endoscope that provides the benefits of both a rigid endoscope and a computer-assisted controller. The Flex® Robotic Transabdominal System is a software-controlled device. The Flex® Robotic Transabdominal System allows for the endoscope to be introduced via an operator-controlled user interface easily providing visualization of structures in the thoracic and abdominal cavities, including female reproductive organs. Visualization is provided by a 3D camera attached at the distal end of the endoscope. The Flex® Robotic Transabdominal System is intended for professional use only in a hospital setting. The Flex® Robotic System is provided non-sterile and reusable. The Flex® Transabdominal Drive is provided sterile through EtO sterilization and is intended for single patient use. The patient-contacting components of the proposed system are all composed of biocompatible materials.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Medrobotics Flex® Robotic System and Flex® Transabdominal Drive, guided by your requested information points.

Important Note: The provided document is a 510(k) summary for a medical device. This type of submission focuses on demonstrating "substantial equivalence" to a legally marketed predicate device, rather than proving a novel device's effectiveness through large-scale clinical trials in the same way a drug or a Class III device might. Therefore, many of your requested points (like MRMC studies, training set details for AI, and explicit "acceptance criteria" presented as targets for the device's performance vs. reported performance) are not typically included in this type of submission. The "acceptance criteria" for a 510(k) device are generally that it performs comparably or better than the predicate device in relevant non-clinical tests.

Description of Acceptance Criteria and Study:

The Medrobotics Flex® Robotic System and Flex® Transabdominal Drive (collectively, the Flex® Robotic Transabdominal System) demonstrated substantial equivalence to its predicate device, the Olympus LTF-190-10-3D, Endoeye Flex 3D Deflectable Videoscope [K123365], through a series of non-clinical performance tests. The acceptance criteria are implicitly met by demonstrating that the device performs equivalently or acceptably within established medical device standards and compared to the predicate.

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

As explained, a 510(k) emphasizes substantial equivalence through comparison to a predicate device and adherence to recognized standards. The following table extracts relevant performance characteristics and reported values. Explicit "acceptance criteria" are not given as numerical targets in this document, but rather a demonstration of performance consistent with the predicate and relevant standards.

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

The document describes bench testing, mechanical and system verification testing, software evaluation, ship testing, electrical safety/EMC testing, biocompatibility testing, and sterilization validation. These are non-clinical (laboratory/simulated) studies.

• Sample Size for Test Set: The document does not specify a numerical sample size for individual tests (e.g., how many units were tested for resolution or distortion). It refers to "testing" or "results from this testing," implying sufficient samples were used to meet regulatory requirements for non-clinical validation.
• Data Provenance: The studies are non-clinical, likely conducted at the manufacturer's facilities (Medrobotics Corporation, Raynham, MA 02767) or by contracted testing laboratories. As they are bench tests, "country of origin" of data or "retrospective/prospective" does not apply in the same way it would for clinical data.

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 information is not applicable to the provided document. The Flex® Robotic Transabdominal System is a surgical visualization device, not an AI diagnostic tool that requires human expert ground truth for its performance evaluation in this context. The testing described is hardware and software verification against engineering specifications and regulatory standards.

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

This is not applicable. Adjudication methods are typically used in clinical studies or AI performance evaluations where human interpretation of medical images or data requires a consensus "ground truth." The tests performed here are objective physical and software verifications.

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

This is not applicable. The device is a robot-assisted surgical visualization system, not an AI-assisted diagnostic tool for image analysis. Therefore, an MRMC study comparing human reader performance with and without AI assistance is irrelevant to this submission.

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

This is not applicable in the context of an AI algorithm assessing medical data. The Flex® Robotic System has software, but it controls the physical endoscope; it does not perform standalone diagnostic assessments akin to an AI algorithm evaluating images. The software itself was assessed for its classification as "moderate level of concern" and its compliance with FDA guidance for software in medical devices.

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

For the non-clinical tests described:

• Resolution, Distortion, Mechanical/System Testing, Electrical Safety, EMC, Ship Testing: The "ground truth" and acceptance criteria are based on engineering specifications, recognized national/international standards (e.g., BS ISO 8600-1, IEC 60601-1, IEC 60601-1-2, ISTA standards), and comparison to the predicate device.
• Biocompatibility: Based on compliance with ISO 10993-1 standards.
• Sterilization: Based on validation to a specific sterility assurance level (SAL) of 10⁻⁶ following standards like ISO 11135 and AAMI TIR 28.

There is no "expert consensus," "pathology," or "outcomes data" ground truth referenced for these non-clinical evaluations.

8. The sample size for the training set

This is not applicable. This device is a robotic surgical system, not an AI diagnostic tool trained on a dataset. The software within the device is control software, not a machine learning model that requires a "training set" in the conventional sense.

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

This is not applicable for the reasons stated in point 8.

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