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The use of the Connected OR Hub with Device and Voice Control system is to allow for voice control and remote control of medical device settings by surgeons or operating room personnel, 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.

The Connected OR Hub with Device and Voice Control is a medical device that allows the surgeon to control the state, selection, and settings of any compatible device attached to it. It also has operating room documentation functionalities (Class I device function) to electronically capture, transfer, store and display medical device data independently of the functions or parameters of the connected medical device.

The Connected OR Hub with Device and Voice Control consists of the following:

• A Connected OR Hub Console a.
• A Device control package b.
• A Voice control package C.

The Connected OR Hub with Device and Voice Control with the Video Image Processing (VIP) software feature incorporates and automates an enhanced image algorithm which detects and digitally removes smoke from surgical images; and, automates the detection and initiates smoke evacuation through compatible laparoscopic insufflator(s) during endoscopic procedures.

The provided text describes a 510(k) premarket notification for the "Connected OR Hub with Device and Voice Control" and mentions its general performance testing. However, it does not contain the detailed information necessary to answer most of your specific questions about acceptance criteria, study methodologies, or ground truth establishment relevant to an AI/ML device.

This submission is primarily focused on demonstrating "substantial equivalence" of the device to legally marketed predicates based on design, intended use, principles of operation, technological characteristics, and safety features. While it mentions an "enhanced image algorithm which detects and digitally removes smoke from surgical images," the documentation does not delve into the specifics of how this algorithm (or any AI/ML component) was validated against defined performance criteria.

Here's an analysis based on the limited information available in the provided text, and what is missing:

The device being reviewed is primarily an OR integration system, not an AI/ML diagnostic or assistive device that would typically have the kind of acceptance criteria you're asking about. The mention of the "enhanced image algorithm which detects and digitally removes smoke from surgical images" is the closest it gets to an AI/ML-like function, but the provided text does not detail its validation as a separate component with specific performance metrics.

Acceptance Criteria and Reported Device Performance

The document does not provide a table of acceptance criteria with reported device performance for an AI/ML component. The "Performance - Bench" test indicates "PASS" against "device input specifications and comparative testing to currently legally marketed device." This is a general statement, not specific to an AI/ML algorithm's performance metrics.

Missing Information for AI/ML Specifics:

1. A table of acceptance criteria and the reported device performance: This information is not present. The document focuses on broad "PASS" results for standards compliance (IEC, ANSI/AAMI) and general bench testing, not specific performance metrics for an image processing algorithm.
2. Sample sized used for the test set and the data provenance: Not specified for the image algorithm.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not specified.
4. Adjudication method for the test set: Not specified.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done: Not indicated. The document states, "The Connected OR Hub with Device and Voice Control with the VIP feature does not require clinical studies to support the determination of substantial equivalence." This strongly implies no MRMC study was conducted specifically for the AI/ML-like image processing feature.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not detailed. While bench testing was done, the specific performance of the smoke detection/removal algorithm in isolation is not reported with quantitative metrics.
7. The type of ground truth used: Not specified.
8. The sample size for the training set: Not specified.
9. How the ground truth for the training set was established: Not specified.

Summary of what is present:

• Device: Connected OR Hub with Device and Voice Control, including a Video Image Processing (VIP) software feature that "automates an enhanced image algorithm which detects and digitally removes smoke from surgical images; and, automates the detection and initiates smoke evacuation through compatible laparoscopic insufflator(s) during endoscopic procedures."
• Regulatory Pathway: 510(k) Premarket Notification.
• Predicate Device: Stryker's Connected OR Hub with Device and Voice Control (K192172, K181258) and ZMED VP4000 Video Processor (K130929).
• Testing Conducted:
  • Software Validation & Verification (IEC 62304:2015) - PASS
  • Usability (IEC 62366-1:2015) - PASS
  • Electrical Safety (ANSI/AAMI ES60601-1:2005/(R)2012 and A1:2012) - PASS
  • EMC (IEC 60601-1-2:2014) - PASS
  • Performance - Bench: "In accordance with device input specifications and comparative testing to currently legally marketed device." - PASS
• Clinical Studies: "The Connected OR Hub with Device and Voice Control with the VIP feature does not require clinical studies to support the determination of substantial equivalence." This is a key statement indicating that the detailed AI/ML validation metrics you're looking for were likely not part of this specific 510(k) submission process, as the agency determined it was substantially equivalent without needing such data for this particular feature in this context.

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