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WAV SCAN EEG System is intended for the acquisition, display, and storage of electrical activity of a patient's brain including electroencephalograph (EEG) and event-related potentials (ERP) obtained by placing two or more electrodes on the head to aid in diagnosis.

WAVi™ SCAN EEG system (WAVi™ SCAN 1.0) is intended for the acquisition, display, and storage of electrical activity of a patient's brain including electroencephalograph (EEG) and eventrelated potentials (ERP) obtained by placing two or more electrodes on the head to aid in diagnosis. The medical system includes the "WAVi™ EPU" (Electronic Processing Unit), an EEG amplifier intended to be used with EEG accessories cleared in K162460 and a computer (laptop computer or tablet device with internal battery and power cord). The hardware and ancillary components used in conjunction with WAVI™ SCAN 1.0 include an EEG cap, the WAVI™ EPU, headphones, a Subject Response Device and a Base Station laptop computer. The software on the Base Station laptop computer is intended for device programming. The WAVI EEG System's software includes electronic versions of standardized clinical assessment tools related to psychiatry and neuropsychological evaluation but are provided for convenience and are to be used in accordance with the assessment tools' specific general instructions. These tools do not interact with any other of the EEG system's hardware and software measures and are stand alone.

The WAVi Scan EEG System has acceptance criteria primarily related to its electrical performance and adherence to established medical device standards. The study presented is a pre-market notification (510(k)) submission to the FDA, which demonstrates substantial equivalence to predicate devices rather than a comparative effectiveness study in the traditional sense of human reader improvement.

Here's a breakdown of the acceptance criteria and the study's proof of meeting them:

1. Acceptance Criteria and Reported Device Performance

The acceptance criteria are derived from recognized international standards for electroencephalographs, particularly IEC 80601-2-26:2019, and general electrical safety and electromagnetic compatibility (EMC) standards. The study demonstrates conformance to these standards.

"P" indicates "Pass" in the provided document, meaning the device met the specified requirement. "Conforms" means the device passed the respective EMI/EMC tests.

2. Sample Size Used for the Test Set and Data Provenance

This document primarily describes a technical performance and safety evaluation for a 510(k) submission, not a clinical study with a "test set" of patient data in the typical sense for AI/diagnostic algorithms. The tests conducted were bench tests and electrical/EMC compliance tests performed by accredited laboratories.

• Sample Size for Test Set: Not applicable in the context of patient data. The "sample" here refers to the number of devices or test setups used in laboratory conditions, which is typically one or a small number for device verification.
• Data Provenance: The data provenance for the performance testing is from accredited testing laboratories that conducted the electrical safety and EMC tests. These are laboratory-generated data, not patient-derived data from specific countries. The document does not specify if the testing was retrospective or prospective in the clinical sense, as it refers to device performance under controlled conditions.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

This type of submission for an EEG amplifier (WAVi Scan EEG System) does not involve experts establishing ground truth for a test set of clinical images or signals for diagnostic performance in the way typically seen for AI-driven diagnostic aids. The "ground truth" for the performance testing is the objective measurement against the specifications listed in the IEC standards. These measurements are performed by qualified technicians/engineers at the accredited testing laboratories, not by medical experts like radiologists.

4. Adjudication Method for the Test Set

Not applicable. There's no human interpretation or subjective assessment of a test set that would require adjudication. The results are objective measurements against predefined engineering and performance standards.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, an MRMC comparative effectiveness study was not done. This 510(k) submission is for an EEG acquisition, display, and storage system. The purpose is to demonstrate substantial equivalence to existing legally marketed EEG devices (predicates) based on technical characteristics, intended use, and safety/performance. It is not an AI-based diagnostic device that assists human readers, and therefore, a study on human reader improvement with AI assistance is not relevant to this submission.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) was Done

No, not in the context of an AI algorithm making diagnostic interpretations. This device is an EEG system that acquires and displays physiological signals. While it has software for processing and analyzing EEG/ERP data (e.g., qEEG outputs like Coherence, power bands), its primary function is data acquisition and display "to aid in diagnosis." It does not present as a device that performs standalone diagnostic interpretations requiring performance metrics like sensitivity/specificity for an AI algorithm without human input. The "algorithm" here refers to the device's firmware and software for data handling and signal processing, not a diagnostic AI.

7. The Type of Ground Truth Used

The "ground truth" for this submission is based on:

• International Consensus Standards: Specifically, IEC 80601-2-26:2019 for electroencephalographs and IEC 60601-1 series for general safety and electromagnetic compatibility.
• Technical Specifications: The device's performance metrics (e.g., noise, frequency response, input dynamic range) are measured against the objective requirements dictated by these standards.

It is not based on expert consensus (clinical opinion), pathology, or outcomes data, as this is a technical device clearance, not a diagnostic or prognostic claim verified by clinical evidence.

8. The Sample Size for the Training Set

Not applicable. This device is an EEG acquisition system and does not describe or rely on an AI model trained on a "training set" of clinical data in the manner of deep learning algorithms for image classification or anomaly detection. The software components relate to data acquisition, display, storage, and basic signal processing, not de novo AI model training.

9. How the Ground Truth for the Training Set was Established

Not applicable, as there is no mention of an AI model with a "training set" in the context of this 510(k) submission.

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