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The OASYS Surgical Light Controller Software allows the control of surgical lights during a procedure from the OASYS View user interface touch panel. It displays the status of the surgical light and controls the operation of the surgical light.

The OASYS Surgical Light Controller allows the control of surgical lights from the OASYS View user interface touch panel. It displays the status of the surgical light and controls the operation of the surgical light. It works with surgical lights from many vendors.

The OASYS Surgical Light Controller communicates with the target surgical light using serial or Ethernet communications. All communications include error and exception handling. The safety features and controls of the surgical light take precedence over these communications.

This software controlling the Surgical Light is written with C# and XML data structures that run on Windows Embedded 7. The software is an optional module to the OASYS View OR Control application. OASYS View is a medical control application that allows for simple and streamlined management of an operating room. The software allows users to:

• Enable video routing from any source device to any destination device
• Preview selected sources on-screen
• Adjust image settings for video sources
• Change picture-in-picture capabilities on supported displays
• Control camera settings including:
• Panning & tilting
• Zooming
• Focusing
• Presets
• Operate medical-grade video recorders
• Select and listen to audio from an iPod or external audio device
• Engage in video conference calls

The software communicates with the light over a serial connection (RS485). Parameters are passed over a socket. The software manages the send and receive buffers to ensure effective communications. Data transmission is verified through the use of checksums and status commands.

The software allows for the Surgical Light to be initialized at run time. Default settings, such as brightness, are initialised on the Surgical Light. During normal operation, commands are passed back and forth based upon operator interaction with the graphical user interface. There are no patient contacting components.

The provided text describes functionality and technical specifications rather than diagnostic performance, therefore it does not fit the typical format for AI/ML device performance analysis. However, based on the provided text, I can infer the "acceptance criteria" relate to the functional operation of the OASYS Surgical Light Controller and the "study" is the performance testing conducted to confirm these functions.

Here's an adaptation of the requested information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance

The document specifies "Performance Testing" was carried out, but it does not mention the sample size for the test set or the data provenance (e.g., country of origin, retrospective or prospective nature of data). This is a software and hardware control system, not a diagnostic AI/ML device, so the concept of "data provenance" in the usual sense (e.g., patient data) does not apply. The testing would have involved the physical device and a surgical light.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

The document does not mention using experts to establish ground truth. For a control system like this, the "ground truth" would be defined by the functional specifications (e.g., is the light brighter when the "increase brightness" button is pressed?). Testing would likely be performed by engineers or quality assurance personnel against these predefined functional requirements.

4. Adjudication method for the test set

The document does not mention an adjudication method. For functional testing of a control system, formal adjudication by experts is typically not performed in the same way it would be for a diagnostic AI/ML device.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size

Not applicable. This device is a surgical light controller, not an AI/ML diagnostic or assistive tool for human readers. Therefore, an MRMC comparative effectiveness study involving human readers with and without AI assistance is not relevant or described.

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

The performance testing described is inherently "standalone" in function, as it tests the capability of the software to control the surgical light as designed. The software itself is the "algorithm only" aspect, performing its control functions based on user input. The document describes the software communicating with the light and managing operations.

7. The type of ground truth used

The ground truth for this device would be defined by engineering specifications and user requirements for the control of a surgical light. For example, "increasing brightness" means the software sends the correct command and the light responds by becoming brighter. This is a functional truth rather than a clinical ground truth (like a pathology report).

8. The sample size for the training set

Not applicable. This is not an AI/ML device in the sense of requiring a training set for model development. The software is programmed with explicit logic and rules for controlling surgical lights, not "trained" on data.

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

Not applicable. As this is not an AI/ML device requiring a training set, the concept of establishing ground truth for a training set does not apply.

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