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The GRAEL SYSTEM is intended for use in the recording, displaying, analysis, printing and storage of human biological parameters such as heart and muscle activity, eye movement, breathing and body movements to assist in the diagnosis of various sleep disorders or neurological disorders. The Grael is designed for use in a hospital or other clinical environment. The Grael is only to be used under the direction of a physician.

Grael and Grael EEG are standalone units, which together with sensors and a PC running Compumedics PSG Online and Profusion PSG software for sleep studies and/or Profusion EEG for EEG studies, can record, review and analyze a number of physiological parameters, including EEG, EOG, EOG and respiratory signals. These are then used as an aid in the diagnosis of respiratory and/or neurological related sleep disorders or other neurological conditions by qualified physicians. The system is comprised of hardware and software which, depending on the model type, provides up to 60 separate parameters for recording, review and analysis.

The provided text (K093222 submission for the GRAEL SYSTEM) is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device. It does not contain the detailed information typically found in a clinical study report that would describe acceptance criteria and the methods used to prove the device meets them in the way modern AI/medical device submissions do.

Specifically, the document:

• Identifies predicate devices and states that the GRAEL SYSTEM is substantially equivalent to them.
• Describes the system's hardware and software components and their functions.
• Lists shared technologies with other approved devices, implying that their prior approval supports the safety and effectiveness of these components in the GRAEL SYSTEM.
• States the intended use of the device.

However, it does not include:

• A table of acceptance criteria and reported device performance metrics in the format requested.
• Details about a specific study designed to prove the device meets performance criteria, especially in the context of an AI/ML algorithm's analytical or clinical performance.
• Information on sample sizes, data provenance, expert qualifications, ground truth establishment, or any form of comparative effectiveness study (MRMC or standalone algorithm performance).

Therefore, I cannot fulfill your request for detailed information regarding acceptance criteria and a study proving their fulfillment based on the provided text.

This K093222 submission is from 2010. The regulatory framework and expectations for demonstrating device performance, particularly for AI/ML-driven devices, have evolved significantly since then. For devices like the GRAEL SYSTEM, the "acceptance criteria" at the time would primarily revolve around demonstrating that the device functions as intended, is safe, and is substantially equivalent to existing predicate devices, likely through electrical safety testing, EMC testing, and functional verification. The "study" would often refer to the documentation of these engineering tests and a comparison table establishing substantial equivalence.

Without additional documentation (e.g., a specific verification and validation report or clinical study report), the requested information cannot be extracted from this 510(k) summary.

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