(286 days)
Intended for use under the direct supervision of a licensed healthcare practitioner or by personnel trained in its proper use. The BIS Monitor is intended for use on adult and pediatric patients within a hospital or medical facility providing patient care to monitor the state of the brain by data acquisition of EEG signals.
The BIS may be used as an aid in monitoring the effects of certain anesthetic agents; and its usage with certain anesthetic agents may be associated with a reduction in primary anesthetic use and a reduction in emergence and recovery time.
Use of BIS monitoring to help guide anesthetic administration may be associated with the reduction of incidence of awareness with recall in adults during general anesthesia and sedation.
The BIS EEG Monitor, VIEW, is an EEG Monitor that displays EEG, as well as reports and graphs the BIS valuc by acquiring two channels maximum of EFG from sensors attached to the patient's head, and performing the computations necessary to produce the Bispectral Index (BIS). The BIS is then numerically displayed for the clinician's use.
It also displays other parameters such as SQI (signal quality) and EMG.
The provided documentation describes a Special 510(k) Summary for the Aspect Medical Systems BIS EEG Monitor, VIEW. This type of submission is typically used for devices that are substantially equivalent to a previously cleared predicate device, but may have minor changes in technology or indications for use.
Based on the document, the device is considered substantially equivalent to its predicate, the Aspect Medical Systems A-3000 EEG Monitor with BIS (K052362). The focus of the submission is to demonstrate that the new device performs similarly and is as safe and effective as the predicate, despite having fewer features (e.g., no secondary data trending, soft keys in place of touch screen, smaller screen, different housing color).
Therefore, the "acceptance criteria" for this submission are primarily focused on equivalence to the predicate device, rather than specific performance metrics against a defined ground truth for a novel AI algorithm. The study for this type of submission is typically limited to demonstrating that the core functions (EEG signal acquisition, BIS value computation, display of parameters) are equivalent and that the changes do not introduce new safety or effectiveness concerns.
Here's an analysis based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
Since this is a Special 510(k) for a device with fewer features that is substantially equivalent to a predicate, the acceptance criteria are not explicitly stated as quantitative performance metrics (e.g., sensitivity, specificity) against a clinical ground truth. Instead, the "performance" is demonstrated through equivalence to the predicate device in its core function and safety.
| Acceptance Criteria Category | Reported Device Performance (Summary of Testing) |
|---|---|
| Functional Equivalence to Predicate | The BIS EEG Monitor, VIEW has the "same intended use and fundamental scientific technology as the predicate device." It displays EEG, reports and graphs the BIS value by acquiring two channels of EEG and performing necessary computations to produce the Bispectral Index (BIS). It also displays SQI and EMG. No explicit performance metrics (e.g., accuracy of BIS value compared to a gold standard) are provided, as the core algorithm is assumed to be the same as the predicate and previously validated. |
| Safety and Effectiveness (Non-inferiority) | "Results indicate the device meets its performance specifications and validation test requirements, and is safe for its intended use." This implicitly means the device performs its core functions (EEG acquisition, BIS calculation, display) reliably and safely, similar to the predicate. The document highlights that the new device has "a lesser number of features," "soft keys in place of touch screen," "a smaller screen," "no trend review screen," and a "different housing color" compared to the predicate. The implication is that these changes do not negatively impact safety or effectiveness. |
| Software Validation | "Software Validation" was completed. While specific acceptance criteria for the software validation aren't provided, it implies adherence to established software development life cycle (SDLC) processes and testing to ensure the software performs as intended and is reliable. |
| Hazard Analysis and Risk Assessment | "Hazard Analysis and Risk Assessment" was completed. This indicates that potential risks associated with the device, especially due to any changes from the predicate, were identified and mitigated, and deemed acceptable. |
2. Sample Size Used for the Test Set and Data Provenance
The document does not specify a separate "test set" sample size or data provenance for a clinical performance study. This is because the submission is a Special 510(k) focusing on equivalence to a predicate with fewer features, not a de novo submission for a novel algorithm requiring extensive clinical validation against a new dataset. The "testing" mentioned is primarily focused on engineering verification and validation (software, risk assessment) to ensure the changed product still functions as intended and is safe.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
This information is not applicable or provided in the document. For a Special 510(k) focused on technological equivalence of a monitor, there isn't typically a ground truth established by medical experts in the way it would be for an AI diagnostic device. The "ground truth" for previous BIS monitor validations (likely the predicate) would have involved correlations between BIS values and clinical states (e.g., level of consciousness, anesthetic depth), but these studies are not detailed here.
4. Adjudication Method for the Test Set
This information is not applicable or provided for the same reasons as above. There is no mention of a human expert adjudication process for this type of submission.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No MRMC study was done or reported. The device is an EEG monitor that calculates and displays a Bispectral Index (BIS) value; it's not an AI diagnostic tool that human readers would use in conjunction with to improve their performance. The improvement for clinicians comes from the information the device provides, not from an AI assistance paradigm relative to human interpretation of raw EEG.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study
This is implicitly the type of performance being claimed for the core BIS algorithm, though not detailed as a separate study in this document. The BIS algorithm's output is the "standalone" performance. The document states the device "performs the computations necessary to produce the Bispectral Index (BIS)." The effectiveness of the BIS algorithm itself would have been established in prior studies for the predicate device, demonstrating its correlation with anesthetic depth and awareness. This current submission assumes the core algorithm remains unchanged and effective. No new standalone study specifically for the "VIEW" monitor's algorithm is described.
7. Type of Ground Truth Used
For the original validation of the BIS algorithm (part of the predicate device, K052362), the ground truth for measuring the "state of the brain" and "effects of anesthetic agents" would typically involve:
- Clinical Endpoints/Outcomes Data: e.g., patient movement in response to surgical stimulus, recall of intraoperative events (for awareness studies), emergence and recovery times.
- Expert Consensus/Clinical Judgment: Anesthesiologists' assessment of anesthetic depth.
- Other Physiological Markers: Though not mentioned, other physiological parameters (heart rate, blood pressure) might be correlated.
However, for this specific submission (K062613), the document does not describe establishing a new ground truth as it relies on the predicate's established performance.
8. Sample Size for the Training Set
This information is not applicable or provided. The BIS algorithm, while complex, operates on principles of EEG signal processing and largely uses fixed mathematical models rather than being a deep learning AI model that requires a training set in the modern sense. There is no mention of retraining or a "training set" for the "VIEW" monitor itself.
9. How the Ground Truth for the Training Set Was Established
This information is not applicable or provided for the reasons stated above (not a modern AI deep learning algorithm requiring a "training set").
§ 882.1400 Electroencephalograph.
(a)
Identification. An electroencephalograph is a device used to measure and record the electrical activity of the patient's brain obtained by placing two or more electrodes on the head.(b)
Classification. Class II (performance standards).