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The intended use of the Stryker Visum™ LED Surgical Lighting System is to illuminate the operative site during surgical procedures with high intensity light.

The Stryker Visum™ LED Surgical Lighting System is intended to illuminate the operative site during surgical procedures. Light functions can be controlled from within the sterile field, from a wall mounted control panel, or through the Stryker SIDNE™ device (K022393). The Stryker Visum™ LED Surgical Lighting System will be used in indications the same as other surgical lights currently offered for commercial distribution in the United States.

The Stryker Visum™ LED Surgical Lighting System is suitable for all major and minor surgical procedures throughout the hospital. The light moves via an easy to move pivoting suspension and has a completely sealed lighthead for safety and hygiene. Intensity is variable from 50,000 Lux to 160,000 Lux and each lighthead has redundant light sources that are not affected by individual source failure. The light quality is based upon a multiple reflector design combined with a heat removing conductive path to provide shadow free, cool light.

All systems are ceiling, wall, or mobile mounted lights and each provides sufficient illumination for all types of surgical procedures. The ceiling mounted lights are available in single, dual, and triple configurations and may also be combined with a separate arm to hold a viewing monitor.

The provided text, K060802, describes a 510(k) premarket notification for the Stryker Visum™ LED Surgical Lighting System. This document focuses on demonstrating substantial equivalence to predicate devices, rather than presenting a detailed study with specific acceptance criteria and detailed performance data. Therefore, many of the requested details about acceptance criteria, study design, and ground truth establishment are not present in this type of regulatory submission.

However, based on the information provided, here's a breakdown of what can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance:

The document states that the device "meets the requirements set forth in FDA Guidance for Surgical Lamps, as well as electrical safety standards IEC 60601-1 and IEC 60601-2-41." It also mentions meeting "the sterility requirements of AAMI ST37 to achieve a SAL of 10^-6." The primary performance claim is its ability to "illuminate the operative site during surgical procedures with high intensity light."

While specific, quantifiable acceptance criteria are not presented in a table form in this document, the following can be inferred:

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

This document does not describe a clinical study with a "test set" in the context of an AI/algorithm-driven device. It's a 510(k) submission for a physical medical device (surgical lighting system). Therefore, information on sample size and data provenance for a test set is not applicable or provided.

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

Not applicable, as this is not a study requiring expert ground truth for an AI algorithm. The device's performance is likely evaluated against engineering specifications, standards, and comparative testing to predicate devices, rather than expert-established ground truth on a dataset.

4. Adjudication Method:

Not applicable for a 510(k) submission for a physical device.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

No, an MRMC comparative effectiveness study is not mentioned or implied, as this is not an AI-assisted diagnostic or interpretive device.

6. Standalone (Algorithm Only) Performance Study:

No, a standalone algorithm performance study was not done. This device is a physical surgical lighting system, not an algorithm.

7. Type of Ground Truth Used:

The "ground truth" for this device's acceptance would be based on:

• Engineering Specifications: Adherence to design criteria for light intensity, color temperature, heat dissipation, maneuverability, etc.
• Regulatory Standards: Compliance with IEC 60601-1, IEC 60601-2-41, and AAMI ST37.
• Comparative Performance Data: Showing equivalence in performance characteristics to the predicate devices (K031068 and K042382).
• Safety Testing: Verifying electrical safety, sterility, and other physical safety parameters.

8. Sample Size for the Training Set:

Not applicable, as this is not an AI/machine learning device. The "training" for a physical device would involve design, prototyping, and iterative testing, not the use of a "training set" in the computational sense.

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

Not applicable, as there is no "training set" in this context. The "ground truth" for the device's design and development comes from established engineering principles, international performance standards, and the performance characteristics of existing, legally marketed predicate devices.

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The Smith & Nephew Control Digital Operating Room System is indicated for use with compatible endoscopic and surgical equipment for centralized control of these devices and display of device status. The control system provides centralized touch panel and voice control of medical devices for use by the surgeon and O.R. staff.

The proposed Smith & Nephew Control Digital Operating Room System is a computer based system that enables centralized status display and control of multiple medical and non-medical devices through touch panel activation or through an optional voice recognition feature. The primary system consists of a Medical Device Controller, Medical Device Hub, Primary Touch Panel Interface (TPI-P), Surgical Touch Panel Interface (TPI-S), Ethernet Router and AVB network hub and AVB Power Supply. Optional components include: speech recognition engine, a wireless microphone for speech recognition, a wireless touch screen interface that can be bagged and placed in the sterile field, a display controller which allows device settings and conditions to be displayed on the surgeon's monitor.

Here's an analysis of the provided text regarding the Smith & Nephew Control Digital Operating Room System, addressing the requested information:

1. Table of Acceptance Criteria & Reported Device Performance

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

This information is not provided in the document. The submission references "performance testing" but does not detail the methodology, sample sizes, or data provenance (e.g., country of origin, retrospective/prospective nature) for any specific tests performed beyond adherence to general safety and EMC standards.

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

This information is not provided in the document. The submission focuses on substantial equivalence to predicate devices and adherence to regulatory standards, not on clinical-performance-based ground truth established by experts.

4. Adjudication Method for the Test Set

This information is not provided in the document. Given the nature of the device (a control system for existing medical devices) and the focus on substantial equivalence to predicate devices and adherence to regulatory standards, a formal adjudication method for a "test set" in the sense of clinical image or data interpretation is unlikely to have been a primary component of this submission.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

This information is not provided and is not applicable to this device. The Smith & Nephew Control Digital Operating Room System is a control system for medical devices, not an AI-powered diagnostic or interpretive tool that would involve "human readers" or "AI assistance" in the typical MRMC study context.

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

This information is not provided and is not entirely applicable in the context of an algorithm's interpretive performance. The device itself is a standalone system for controlling other medical devices. Its "performance" would be assessed in terms of its ability to correctly send commands and display status, which is inherent in its function. No separate "algorithm-only" study examining diagnostic accuracy (as typically implied by this question) would be relevant here.

7. The Type of Ground Truth Used

The "ground truth" used for this submission appears to be:

• Adherence to recognized voluntary standards: IEC 60601-1, IEC 60601-1-1, IEC 60601-1-2, UL 60601-1, CAN/CSA 22.2 No. 601.1 regarding safety and EMC.
• Functional equivalence to predicate devices: The ability of the system to provide "centralized and remote control of medical devices in the O.R." in a manner deemed equivalent to existing, legally marketed systems (Olympus EndoALPHA, HERMES, Sidne™). This implies that the accepted functionality of the predicate devices serves as a benchmark for "ground truth" performance.

No pathology, expert consensus on diagnostic outcomes, or patient outcomes data is mentioned as ground truth.

8. The Sample Size for the Training Set

This information is not provided in the document. As this is a control system for operational devices rather than a machine learning algorithm that is "trained" on data to perform a specific task (e.g., image classification), the concept of a "training set" in the context of AI/ML is not applicable here. Its development would involve software engineering and hardware testing, not a data-driven training process.

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

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

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The Stryker Wireless Universal Footswitch System (SWUFS) is indicated for use with compatible endoscopic and general surgery devices. It will utilize a single footswitch to selectively control multiple devices, which typically each have their own dedicated footswitch. The system includes a wireless footswitch and receiver. The SWUFS will be an accessory to and provide footswitch input control for the Stryker Total Performance System, the SERFAS (Stryker Endoscopy Radio Frequency Ablation System) consoles, and the Valleylab Electrosurgical Generator.

The Stryker Wireless Universal Footswitch System (SWUFS) is indicated for use with compatible endoscopic and general surgery devices. It will utilize a single footswitch to selectively control multiple devices, which typically each have their own dedicated footswitch. The system includes a wireless footswitch and receiver. The SWUFS will be an accessory to and provide footswitch input control for the Stryker Total Performance System, the SERFAS (Stryker Endoscopy Radio Frequency Ablation System) consoles, and the Valleylab Electrosurgical Generator.

This document is a 510(k) Summary of Safety and Effectiveness for the Stryker Wireless Universal Footswitch System (SWUFS). It focuses on establishing substantial equivalence to predicate devices, rather than presenting a study with specific acceptance criteria and detailed performance metrics as one might find for a novel diagnostic AI device.

Therefore, many of the requested sections regarding acceptance criteria, study design, ground truth establishment, sample sizes for test/training sets, expert adjudication, and MRMC studies are not applicable or cannot be extracted from this type of regulatory submission. The document primarily highlights adherence to voluntary safety standards and functional equivalence.

Here's an attempt to answer the questions based on the provided text, with clarifications where information is not available or relevant to a 510(k) for an accessory device:

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

This document does not present a table of specific quantitative acceptance criteria and corresponding performance metrics in the way one would for a diagnostic accuracy study. Instead, it demonstrates compliance with recognized safety and electrical standards and functional equivalence to predicate devices. The "performance" is implicitly meeting these standards and functioning as intended.

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

Not applicable. This is a 510(k) submission for a non-diagnostic accessory device establishing substantial equivalence, not a clinical study on a "test set" of patient data. The evaluation focused on engineering compliance and functional testing, not data-driven performance metrics on patient samples.

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)

Not applicable. Ground truth as typically defined in diagnostic AI studies (e.g., confirmed diagnosis, pathology) is not relevant for this type of device. The "ground truth" here is adherence to engineering standards and successful operation.

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

Not applicable. There was no "test set" in the context of patient data that would require expert 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

Not applicable. An MRMC study is relevant for diagnostic AI devices where human readers interpret medical images or data. The SWUFS is a hardware accessory (wireless footswitch) and does not involve AI or human "readers" interpreting medical cases.

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

Not applicable. The SWUFS is a hardware device; it does not have a "standalone algorithm" performance to evaluate. Its function is to facilitate human operators' control of other medical devices.

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

Not applicable. The "ground truth" for this device's regulatory clearance is compliance with recognized voluntary standards related to electrical safety, electromagnetic compatibility, and functional equivalence to existing legally marketed devices. Its performance is verified through engineering tests to ensure it meets these standards and accurately controls the intended surgical devices.

8. The sample size for the training set

Not applicable. The SWUFS is a hardware device; it does not involve machine learning or a "training set" of data.

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

Not applicable. As there is no training set for a machine learning algorithm, there is no ground truth to establish for it.

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