Search Results

The Omega Whole-Cortex MEG System non-invasively measures The magnetoencephalographic (MEG) signals (and, optionally, electroencephalographic (EEG) signals) produced by electrically active tissue of the brain. These signals are recorded by a computerized data acquisition system, displayed, and may then be interpreted by trained physicians to help localize these active areas. The locations may then be correlated with anatomical information of the brain. MEG is routinely used to identify the locations of visual, auditory, somatosensory, and motor cortex in the brain when used in conjunction with evoked response averaging devices. MEG is also used to non-invasively locate regions of epileptic activity within the brain. The localization information provided by MEG may be used, in conjunction with other diagnostic data, in neurosurgical planning.

The Omega Whole-Cortex MEG Systems integrate up to 307 dc-SQUID axial gradiometers with workstation computers and data acquisition software in order to measure the magnetic signals generated by intercellular dendritic currents. These detectors positioned in a helmet shaped array gives the user the ability to record electrical activity of the entire surface of the brain simultaneously without having to move the position of the probe.

The provided text does not contain detailed information about specific acceptance criteria and a study proving the device meets them in the way typically expected for a medical device's performance evaluation (e.g., sensitivity, specificity, accuracy metrics).

The document is a 510(k) summary for a Special 510(k) Device Modification, focusing on changes to an existing device (CTF Whole-Cortex MEG System) and establishing substantial equivalence to a predicate device. It discusses modifications to auxiliary channels, electronics, and software/firmware, along with a new operating system.

The "Indications for Use" and "Intended Use" sections describe what the device does and what it's used for, but these are not quantitative performance metrics or acceptance criteria for a specific clinical outcome or diagnostic accuracy.

Therefore, most of the requested information regarding acceptance criteria, study details, sample sizes, expert qualifications, and ground truth establishment is not present in the provided text.

Based on the available information:

1. A table of acceptance criteria and the reported device performance: Not available. The document describes the device's function and intended use, but not specific performance metrics (e.g., detection rates, localization accuracy) that would be compared against predefined acceptance criteria.
2. Sample size used for the test set and the data provenance: Not available. No clinical or performance study data is presented.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not available.
4. Adjudication method for the test set: Not available.
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: Not applicable. The device described is a Magnetoencephalograph (MEG) system, which measures brain signals. It's not an AI-assisted diagnostic tool for human readers in the way typically evaluated by MRMC studies (e.g., comparing radiologists with and without AI assistance for image interpretation).
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable in the context of an algorithm's diagnostic performance. The device itself acquires and displays signals, which are then interpreted by trained physicians. There's no "standalone algorithm" performance described.
7. The type of ground truth used: Not available.
8. The sample size for the training set: Not available (as no machine learning algorithm development is described in this context).
9. How the ground truth for the training set was established: Not available.

The document mainly focuses on regulatory aspects of a device modification, asserting that the modified device remains substantially equivalent to the predicate device for its stated indications for use. It does not contain a detailed performance study comparing quantitative measures against predefined acceptance criteria.

Ask a specific question about this device