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Connected OR Hub with Device and Voice Control:
The use of the Connected OR Hub with Device and Voice Control is to allow for voice control and remote control of medical device settings by surgeons or operating room personnel, thereby eliminating the need to manually operate those devices compatible with the Connected OR Hub with Device and Voice Control or to rely on verbal communication between the surgeon and other operating room personnel in order to adjust the surgical equipment. It also has additional digital documentation functionality to electronically capture, transfer, store and display medical device data (non-medical device function), which is independent of the functions or parameters of any attached Stryker device.

SDC4K Information Management System with Device and Voice Control:
The use of the SDC4K Information Management System with Device and Voice Control is to allow for voice control and remote control of medical device settings by surgeons or operating room personnel, thereby eliminating the need to manually operate those devices compatible with the SDC4K Information Management System with Device and Voice Control or to rely on verbal communication between the surgeon and other operating room personnel in order to adjust the surgical equipment. It also has additional digital documentation functionality to electronically capture, transfer, store and display medical device data (non-medical device function), which is independent of the functions or parameters of any attached Stryker device.

The Connected OR Hub with Device and Voice Control and SDC4K Information Management System with Device and Voice Control are network compatible hardware platforms that carry out Medical Device Data System (MDDS) functionalities and allows the user to control the state, selection, and settings of compatible connected devices both wired and wirelessly.

The Connected OR Hub with Device and Voice Control and SDC4K Information Management System with Device and Voice Control consists of the following components:

• 1. Base Console which includes:
  • a) Medical Device Data System (MDDS) functionalities
  • b) Optional Device Control feature
  • c) Optional Voice Control feature
  • d) Optional Video Image Processing (VIP) feature
• 2. Device Control Package (software activation USB dongle and a handheld Infrared (IR) remote control)
• 3. Voice Control Package (software activation USB dongle and a wireless headset and base station)
• 4. Video Image Processing package (software activation USB dongle)
• 5. Connected OR Spoke (MDDS)

The provided FDA 510(k) summary for the Stryker Connected OR Hub with Device and Voice Control and SDC4K Information Management System with Device and Voice Control describes the acceptance criteria and the study that proves the device meets them. However, it does not involve an AI system for diagnostic or prognostic purposes, but rather a control system for medical devices. Therefore, some of the requested information regarding AI-specific criteria (like effect size of AI assistance for human readers, ground truth type for training, etc.) is not applicable.

Here's an analysis based on the available information:

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

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

The document does not specify a "test set" in the context of a dataset for an AI model. Instead, it refers to various engineering and validation tests. The "Performance - Bench" tests would have involved specific test cases and scenarios, but the sample size (number of tests, number of voice commands, etc.) is not explicitly detailed. The provenance is internal to Stryker's development and validation processes. Given the nature of software and hardware validation, these tests are typically conducted in a controlled environment as part of the manufacturing and R&D process.

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

This information is not explicitly provided in the document. For non-AI device validation, "ground truth" is typically established by engineering specifications, recognized standards (e.g., IEC, AAMI), and user needs. The validation process would involve qualified engineers and testers to confirm the device performs according to these pre-defined specifications. For "Usability," expert users (e.g., surgeons, OR personnel) or human factors engineers would likely be involved, but their number and specific qualifications are not detailed.

4. Adjudication method for the test set

The document does not describe an adjudication method in the context of multiple observers or interpretations for a test set, as would be common for AI performance evaluation. For the various "Pass" results, internal validation protocols and test reports would have been followed, likely involving engineering review and sign-off based on predefined success criteria for each test.

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, a multi-reader multi-case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance was not done. This device is a control system (voice and remote control) for other medical devices and not an AI diagnostic or prognostic tool that assists human readers in interpreting medical images or data.

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

The device's core functionality involves control of medical devices, including "voice control of medical device settings." While this incorporates voice recognition, it's not a standalone AI algorithm for medical diagnosis or interpretation. The "Voice Recognition Performance" was tested, implying a standalone evaluation of this component, but it's part of a human-in-the-loop control system. The other listed tests (Electrical Safety, EMC, etc.) are inherent to the device's standalone hardware and software performance.

7. The type of ground truth used

The ground truth for this device's validation is based on:

• Recognized Standards: e.g., IEC 60601-1 for electrical safety, IEC 60601-1-2 for EMC, AAMI TIR69 for wireless technology, IEC 62304 for software, IEC 62366-1 for usability.
• Device Input Specifications: Internal engineering requirements for video compatibility, environmental robustness, voice recognition accuracy, and overall system design.
• User Needs and Intended Uses: The device must meet the functional requirements for surgeons and operating room personnel to control medical devices effectively and safely.

8. The sample size for the training set

This information is not provided. For the voice recognition component, a training set would have been used to develop the voice models. However, the document does not specify its size or characteristics, as it's not the primary focus of the 510(k) summary for this type of device.

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

Not explicitly stated. For the voice recognition feature, the ground truth for training would typically involve a large dataset of spoken commands, explicitly transcribed and labeled, to train the voice recognition model to accurately identify the intended commands. This process is standard for developing speech recognition systems.

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