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The NaviCam Stomach Capsule is intended for visualization of the stomach of adults (>/=22 years) with BMI

The NaviCam Capsule and NaviCam Tether are disposable sterile products, which serve as an accessory to the NaviCam Capsule Endoscope System and the NaviCam Xpress Stomach Capsule Endoscope System to allow for examination of the esophagus prior to releasing the NaviCam Capsule into the stomach. The NaviCam Tether is comprised of a tube which on one end is attached to a capsule cradle and on the other end is attached to a syringe connector. The capsule cradle holds the capsule in place while examining the esophagus. The tube is used to control the downward speed of the capsule in the esophagus. The syringe connector serves for releasing the capsule by attaching to it a standard syringe filled with air. After the examination of the esophagus is accomplished, the syringe piston is pushed to release the capsule for examining the stomach with the NaviCam Capsule Endoscope System or the NaviCam Xpress Stomach Capsule Endoscope System.

The provided text does not describe an AI-powered device or a study proving its performance against specific acceptance criteria. Instead, it is a 510(k) summary for a NaviCam Capsule Endoscope System with NaviCam Stomach Capsule and NaviCam Tether. This system is a medical device for visualizing the stomach and esophagus, and the submission focuses on demonstrating its substantial equivalence to previously cleared predicate devices.

Therefore, I cannot provide the information requested in the prompt, as it pertains to AI-specific performance criteria and studies, which are not present in the provided document.

Here's an analysis of why the requested information cannot be extracted from the given text:

• No mention of AI/ML: The document does not describe the device as having any artificial intelligence or machine learning components. It's a hardware device (capsule endoscope and tether) for aiding visualization.
• No acceptance criteria for AI performance: Since there's no AI, there are no acceptance criteria related to its performance (e.g., sensitivity, specificity, AUC).
• No study proving AI performance: Consequently, there's no study described that would prove the device meets AI-specific acceptance criteria. The performance data section focuses on non-clinical (biocompatibility, bench testing) and clinical experience (references to scientific literature demonstrating safety and value, and a meta-analysis on battery life), not AI performance.
• No data provenance for AI testing: Without AI, there's no test set, training set, or related data provenance for AI models.
• No experts for AI ground truth: The concept of experts establishing ground truth for AI model performance isn't applicable here.
• No MRMC study: The document does not describe a multi-reader multi-case study, which is typically done to assess the impact of AI assistance on human readers.
• No standalone algorithm performance: As it's not an algorithm, there's no standalone performance to report.
• No ground truth type for AI: The "ground truth" discussed in the context of AI (e.g., pathology, expert consensus for disease detection) is not relevant for this device's submission.

In summary, the provided FDA 510(k) summary is for a physical medical device (capsule endoscopy system) and does not involve AI. Therefore, the questions related to AI-specific performance criteria and studies cannot be answered from this text.

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