(178 days)
The ConnectedOR Hub is indicated for use with compatible endoscopic and general surgery devices. The ConnectedOR Hub can be used in general laparoscopy, nasopharyngoscopy, sinuscopy, and plastic surgery wherever a laparoscope, endoscope, or an arthroscope is indicated for use. A few examples of the more common endoscopic surgeries are laparoscopic cholecystectomy, laparoscopic hernia repair, laparoscopic appendectomy, laparoscopic pelvic lymph node dissection, laparoscopically assisted hysterectory, laparoscopic anterior spinal fusion, anterior cruciate ligament reconstruction, knee arthroscopy, small joint arthroscopy, decompression fixation, wedge resection, lung biopsy, pleural biopsy, dorsal sympathectomy, pleurodesis, internal mammary artery dissection for coronary artery bypass, coronary artery bypass grafting where endoscopic visualization is indicated and examination of the evacuated cardiac chamber during performance of valve replacement. ConnectedOR Hub users are general surgeons, gynecologists, cardiac surgeons, thoracic surgeons, orthopedic surgeons, ENT surgeons, and urologists.
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. A Connected OR Hub console b. A Device control package (contains an optional software upgrade and a handheld Infrared (IR) remote control) c. A Voice control package (contains an optional software upgrade and a headset and base station)
The provided text describes a 510(k) premarket notification for the "ConnectedOR Hub with Device and Voice Control." This submission seeks to demonstrate substantial equivalence to a predicate device and does not involve clinical studies to establish new device performance. Therefore, the information typically requested regarding acceptance criteria and a study proving a device meets them for a novel medical AI/ML device is not directly applicable in this context.
However, based on the non-clinical testing summary, we can infer some "acceptance criteria" through the tests performed to show equivalence:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria (Implied from Test Method) | Reported Device Performance |
|---|---|
| Device and Voice Control Performance: Performance of device and voice control functionalities with compatible devices in accordance with device performance specifications. | Pass |
| Compatibility with Connected OR Spoke: Compatibility with Connected OR Spoke in accordance with device performance specification. | Pass |
| Environmental Performance: Functionality validated for specified operating temperature and humidity range. | Pass |
| Video Compatibility: Compatibility with supported Cameras, Monitors, and peripherals. | Pass |
| Memory Profiling and Performance: Performance and system response times of Class II Medical Device functionality (Voice and Device Control functionality) while Class I documentation functionalities are in use, in accordance with device performance specifications. | Pass |
| Voice Recognition Performance: Voice recognition performance of the proposed system when voice commands are issued to the system in accordance with device performance specification. | Pass |
| Voice Accuracy Benchmark: Voice recognition accuracy of the proposed system when voice commands are issued is equivalent to or better than the predicate system. | Pass |
| Wireless Technology Performance: Performance and coexistence of wireless technology in accordance with AAMI TIR 69:2017, ANSI C63.27:2017, and FDA guidance. | Pass |
| Electrical Safety: In accordance with ANSI/AAMI ES60601-1:2005/(R)2012 and A1:2012, C1:2009/(R)2012 and A2:2010/(R)2012 (Consolidated Text). | Pass |
| EMC Testing: In accordance with IEC60601-1-2 Edition 4.0 2014-02. | Pass |
| Usability: Designed and tested per IEC 60601-1-6 Edition 3.1 2013-10 and ANSI/AAMI/IEC 62366-1:2015. | Pass |
| System Validation and Simulated User Testing: Validated system performance in accordance with defined user needs and device performance specifications. | Pass |
| Software Validation & Verification: In accordance with IEC 62304 and FDA Guidance Document Principles of Software Validation. | Pass |
| Cybersecurity Verification and Network scan: In accordance with device performance specifications, cybersecurity risk assessment and FDA guidance documents. | Pass |
2. Sample size used for the test set and the data provenance:
- The document does not specify a "test set" in the context of clinical data or patient samples. The testing described focuses on engineering, performance, and regulatory compliance.
- The "Voice Accuracy Benchmark" test compares the proposed system's voice recognition accuracy to the predicate system's accuracy. While it implies a test set of voice commands, the size and provenance (e.g., country of origin, retrospective/prospective) of this specific test set are not provided. Given it's a benchmark against an existing system, the data would likely be internally generated for verification purposes rather than external clinical data.
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):
- The document does not describe the establishment of ground truth by external experts for a clinical "test set." The "ground truth" for the engineering performance tests would be defined by the technical specifications of the device itself and established industry standards.
- For the "Voice Accuracy Benchmark," the "ground truth" for each voice command would be the intended action if the command was correctly recognized. The process of establishing this ground truth (e.g., human transcription of voice commands, predefined correct responses) and the involvement of experts are not described.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- No explicit adjudication method is described, as the testing is primarily technical performance verification, not an interpretation of medical images or clinical outcomes requiring expert consensus.
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, an MRMC comparative effectiveness study was explicitly NOT done. The document states: "The Connected OR Hub with Device and Voice Control does not require clinical studies to support the determination of substantial equivalence." This is a device for surgical control and documentation, not an AI diagnostic aid for human readers.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:
- The device's core functions (device and voice control, documentation) inherently involve "human-in-the-loop." The voice control relies on a human speaking commands, and device control involves a human using an IR remote. While the voice recognition algorithm itself performs "standalone" within its module, its performance is measured in how effectively it responds to human input. The "Voice Accuracy Benchmark" test can be considered a standalone performance assessment of the voice recognition algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- For technical performance tests, the "ground truth" is defined by the device's technical specifications and relevant industry standards (e.g., for electrical safety, EMC, software validation).
- For the "Voice Accuracy Benchmark," the ground truth for individual voice commands would be the correct interpretation or expected device action based on the command. The specific method for establishing this correct interpretation is not detailed. It is highly likely based on predefined command sets and expected responses.
8. The sample size for the training set:
- The document does not refer to a "training set" in the context of machine learning. The device utilizes a voice recognition software engine, which would have been trained. However, the details of this training (e.g., sample size of voice data, types of voices) are not provided in this regulatory submission, as the focus is on the equivalence of the current device's voice recognition performance to a predicate.
9. How the ground truth for the training set was established:
- As no training set details are provided, the method for establishing its ground truth is also not described. For a voice recognition system, this would typically involve large datasets of spoken words or phrases, meticulously transcribed or annotated to serve as the ground truth for the machine learning model.
§ 876.1500 Endoscope and accessories.
(a)
Identification. An endoscope and accessories is a device used to provide access, illumination, and allow observation or manipulation of body cavities, hollow organs, and canals. The device consists of various rigid or flexible instruments that are inserted into body spaces and may include an optical system for conveying an image to the user's eye and their accessories may assist in gaining access or increase the versatility and augment the capabilities of the devices. Examples of devices that are within this generic type of device include cleaning accessories for endoscopes, photographic accessories for endoscopes, nonpowered anoscopes, binolcular attachments for endoscopes, pocket battery boxes, flexible or rigid choledochoscopes, colonoscopes, diagnostic cystoscopes, cystourethroscopes, enteroscopes, esophagogastroduodenoscopes, rigid esophagoscopes, fiberoptic illuminators for endoscopes, incandescent endoscope lamps, biliary pancreatoscopes, proctoscopes, resectoscopes, nephroscopes, sigmoidoscopes, ureteroscopes, urethroscopes, endomagnetic retrievers, cytology brushes for endoscopes, and lubricating jelly for transurethral surgical instruments. This section does not apply to endoscopes that have specialized uses in other medical specialty areas and that are covered by classification regulations in other parts of the device classification regulations.(b)
Classification —(1)Class II (special controls). The device, when it is an endoscope disinfectant basin, which consists solely of a container that holds disinfectant and endoscopes and accessories; an endoscopic magnetic retriever intended for single use; sterile scissors for cystoscope intended for single use; a disposable, non-powered endoscopic grasping/cutting instrument intended for single use; a diagnostic incandescent light source; a fiberoptic photographic light source; a routine fiberoptic light source; an endoscopic sponge carrier; a xenon arc endoscope light source; an endoscope transformer; an LED light source; or a gastroenterology-urology endoscopic guidewire, is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 876.9.(2) Class I for the photographic accessories for endoscope, miscellaneous bulb adapter for endoscope, binocular attachment for endoscope, eyepiece attachment for prescription lens, teaching attachment, inflation bulb, measuring device for panendoscope, photographic equipment for physiologic function monitor, special lens instrument for endoscope, smoke removal tube, rechargeable battery box, pocket battery box, bite block for endoscope, and cleaning brush for endoscope. The devices subject to this paragraph (b)(2) are exempt from the premarket notification procedures in subpart E of part 807of this chapter, subject to the limitations in § 876.9.