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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 opersonnel 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 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 endoscopic and general surgery devices both wired and wirelessly.

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

• 1. Base Console which includes:
  • a) Class I 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 (Class I MDDS)

The Connected OR Hub and SDC4K consoles carry out the Medical Device Data System (MDDS) functionalities (i.e. Class I device function or Non-medical function) and can be marketed as standalone devices. When upgraded with the Device Control and/or Voice Control package, the consoles extend their functionalities to control compatible devices from their touchscreen graphical user interface (GUI), spoken commands via headset (voice control input), and an IR remote control or directional keypad from a camera head (device control input). The received user commands are then processed and communicated with the connected controllable devices, allowing the user to control the state, selection, and settings of those devices.

In addition, the Connected OR Hub with Device and Voice Control and SDC4K Information Management System with Device and Voice Control also provide compatibility with the Connected OR Spoke (also referred to as "Spoke") which is a standalone Class I Medical Device Data System. Once the Connected OR Hub with Device and Voice Control or SDC4K Information Management System with Device and Voice Control is connected to the Spoke, Device Control can be extended to compatible devices which are directly connected to the Spoke.

When upgraded with the Video Image Processing (VIP) package, the Connected OR Hub automates an image enhancing algorithm, and removal of surgical smoke through a compatible insufflator.

The provided text describes a 510(k) premarket notification for the "Connected OR Hub with Device and Voice Control" and "SDC4K Information Management System with Device and Voice Control." This submission asserts substantial equivalence to predicate devices and focuses on performance data derived from bench testing and adherence to various standards. However, the document does not contain the level of detail typically found in a clinical study report regarding acceptance criteria for diagnostic accuracy, sample size of a test set, expert qualifications for ground truth, adjudication methods, MRMC studies, or specific training set information.

Based on the provided information, here's what can be extracted and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not specify quantitative acceptance criteria in terms of diagnostic performance metrics (e.g., sensitivity, specificity, accuracy) for an AI or imaging device, as this device primarily focuses on device control and information management rather than diagnostic interpretation. The "Performance - Bench" criterion is qualitative.

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

The document indicates that the devices underwent "Performance - Bench" testing. However, it does not specify a numeric sample size for a test set, nor does it detail the provenance of any data used (e.g., country of origin, retrospective or prospective). This is expected given the nature of the device as a control and information management system, rather than an AI-enabled diagnostic imaging device that processes patient data.

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 the involvement of experts to establish ground truth. As the device functions relate to controlling medical equipment and managing data, and not to diagnostic interpretation of medical images or patient conditions, such an expert-based ground truth assessment would not be applicable or expected. The "Pass" results for the listed tests (Electrical Safety, EMC, Software Validation, Usability, Bench Performance) imply that the device met pre-defined engineering and functional requirements, which are typically verified by engineers and quality assurance personnel against specifications, rather than by medical experts establishing diagnostic ground truth.

4. Adjudication method for the test set

No adjudication method is mentioned, as there is no expert-driven ground truth establishment described for a test set.

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 MRMC comparative effectiveness study was conducted or mentioned in this submission. The device is not an AI-assisted diagnostic tool that would typically warrant such a study. Its function is to facilitate device control and information management in the operating room.

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

The document describes "Software Validation & Verification" (IEC 62304:2015) and "Performance - Bench" tests. These tests would involve evaluation of the device's functions, including its algorithms for device/voice control and data management, in a standalone manner without human intervention for diagnostic interpretation. The reported result for these tests is "Pass," indicating that the algorithms and system components performed as specified. However, it's not a standalone performance for diagnostic purposes.

7. The type of ground truth used

The concept of "ground truth" in the diagnostic sense (e.g., pathology, outcomes data) is not applicable or stated. For the types of tests described (Electrical Safety, EMC, Software, Usability, Bench Performance), the "ground truth" would be defined by engineering specifications, regulatory standards, and predefined functional requirements. A "Pass" result indicates compliance with these established criteria.

8. The sample size for the training set

The document does not provide any information about a training set size. This is because the device described is not an AI/ML-driven diagnostic or predictive model that typically undergoes a training phase with a distinct dataset. Its functionalities are primarily based on deterministic software logic for control and data management.

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

As no training set is mentioned or applicable in the context of this device's functionalities, there is no information on how ground truth for a training set was established.

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