(219 days)
The NeuroCap (model DEC18) is an Electroencephalogram (EEG) electrode array intended for use in ER (emergency room), ICU (intensive care unit) and OR (operating room) for recording of STAT EEGs in patients of 18 years of age and older.
The NeuroCap (model DEC18) is an Electroencephalogram (EEG) electrode array intended for use in ER (emergency room), ICU (intensive care unit) and OR (operating room) for recording of STAT EEGs in patients of 18 years of age and older. NeuroCap is intended for use with amplifiers of medical signals equipped with appropriate plug or by special adapter will not be included in subject device). NeuroCap is a disposable electrodes system made of polycarbonate based film with applied conductive paths and sensors. Each sensor is equipped with a sponge with a conductive gel for providing sensor contact with the skin surface. NeuroCap is fixed on the patient by means of adhesive tape. NeuroCap could be connected to amplifier directly or via a special adapter.
The NeuroCap disposable electrode system is 16 channels. The headband is non-sterile and disposable for single patient use and designed to be used with the Neuro EEG device (K173460) for EEG acquisition and recording. NeuroCap is intended for prescription use in healthcare facilities, or clinical research environments.
The NeuroCap (model DEC18) is an Electroencephalogram (EEG) electrode array. The provided text outlines a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed study with specific acceptance criteria and detailed device performance metrics typically found in clinical efficacy trials for AI/ML devices.
However, based on the information provided, we can infer the "acceptance criteria" and "device performance" in the context of the 510(k) submission, which are primarily related to safety and performance through lab bench testing and comparison to a predicate device.
Here's an analysis based on the document:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not explicitly present a table of quantitative acceptance criteria and corresponding device performance values as would be typical for an AI/ML algorithm's diagnostic accuracy. Instead, the "acceptance criteria" are implied by compliance with established standards and the "device performance" is demonstrated through successful completion of these tests and a showing of substantial equivalence to the predicate.
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Biocompatibility: Conformance with ISO 10993-5 and ISO 10993-10 | Device passed biocompatibility tests according to ISO 10993-5 and ISO 10993-10 standards. |
| Risk Management: Conformance with ISO 14971:2012 | Device passed risk management procedures according to ISO 14971:2012 standards. |
| Performance: Conformance with ANSI/AAMI EC12:2000 | Device passed performance tests according to ANSI/AAMI EC12:2000 Disposable ECG electrodes standards. |
| Substantial Equivalence: To predicate device (StatNet) | The NeuroCap's technological characteristics, features, specifications, materials, mode of operation, and intended use are substantially equivalent to the predicate device (StatNet). Differences in physical dimensions (size of caps, surface area, weight, package dimensions) were deemed to have no impact on safety and effect. |
2. Sample Size Used for the Test Set and Data Provenance
The document describes lab bench testing, biocompatibility testing, and risk management assessment. These types of tests do not typically use "test sets" in the same way an AI/ML algorithm evaluation would (i.e., a dataset of patient cases).
- Sample Size for Test Set: Not applicable in the context of a "test set" for an algorithm. The testing described (biocompatibility, performance, risk management) would have involved samples of the device itself and potentially biological samples for biocompatibility, but not a patient-level data test set.
- Data Provenance: Not applicable in the context of patient data provenance. The testing was conducted in laboratories to assess the physical and biological properties of the device.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications
- Number of Experts: Not applicable. The ground truth for these types of engineering and biocompatibility tests is established by adhering to published standards (e.g., ISO, ANSI/AAMI) and engineering specifications, not by expert consensus on clinical cases.
- Qualifications of Experts: N/A. The "experts" involved would be qualified lab technicians, engineers, and quality assurance personnel performing the tests according to the standards.
4. Adjudication Method for the Test Set
- Adjudication Method: Not applicable. Adjudication methods like 2+1 or 3+1 are used for establishing ground truth in clinical datasets, particularly for image interpretation or diagnosis. The tests mentioned are for device performance and safety, not for diagnostic accuracy evaluated against human expert consensus.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done
- MRMC Study: No. The document does not mention any MRMC study. The NeuroCap is an EEG electrode array, a hardware device, not an AI/ML diagnostic software. The evaluation focuses on the safety and performance of the electrodes themselves.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done
- Standalone Performance: Not applicable. The NeuroCap is a hardware device (electrodes), not an algorithm. Its performance is inherent to its physical and electrical properties, not algorithmic output, and it is intended to be used with an EEG device and interpreted by human clinicians.
7. The Type of Ground Truth Used
- Type of Ground Truth: The ground truth for the evaluations conducted (biocompatibility, risk management, performance) is based on established industry standards and regulatory requirements (e.g., ISO 10993, ISO 14971, ANSI/AAMI EC12). For substantial equivalence, the "ground truth" is the established characteristics and performance of the legally marketed predicate device.
8. The Sample Size for the Training Set
- Training Set Sample Size: Not applicable. The NeuroCap is a hardware device; it does not involve machine learning algorithms that require a "training set."
9. How the Ground Truth for the Training Set Was Established
- Ground Truth for Training Set: Not applicable, as there is no training set for a hardware device like the NeuroCap.
§ 882.1320 Cutaneous electrode.
(a)
Identification. A cutaneous electrode is an electrode that is applied directly to a patient's skin either to record physiological signals (e.g., the electroencephalogram) or to apply electrical stimulation.(b)
Classification. Class II (performance standards).