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The Flexset system is intended for prescription use in a healthcare facility, home, and specific transport environments to acquire, transmit, display and store EEG and auxiliary signals for adults and children, not including newborns. The Flexset system acquires, transmits, displays and stores electroencephalogram (EEG), and optionally electrocardiogram (ECG), electrooculogram (EOG), electromyogram (EMG), orientation sensor data, photic sensor data, external trigger signals and video.

The Flexset System is intended to acquire, transmit, display and store primarily EEG and optionally auxiliary signals. Specific transport environments in the Indications for Use include ambulances, cars, buses, trains, boats and via air, per stipulation in the user manual of the device. The Flexset headset is designed to record a full montage EEG, with optional external references and additionally up to 8 auxiliary channels using lead wires for EEG, EOG, ECG or EMG. The device consists of the following components:

• Flexset (Headset) .
• Electrodes
• Charger with cable ●
• Display Unit ●
• Extension Unit ●
• Lead wires ●
• Software ●
  • Display Unit firmware o
  • Data center application (same as K172735) O
  • O Client application (same as K172735)

The provided 510(k) summary for the Zeto, Inc. Flexset System does not contain the specific details about the acceptance criteria or a dedicated study proving the device meets those criteria in the way typically expected for an AI/ML-driven diagnostic device.

This document describes a device for acquiring, transmitting, displaying, and storing EEG and auxiliary signals. It focuses on demonstrating substantial equivalence to a predicate device (WR19 System) and a secondary predicate device (X-Series System) based on technological characteristics and intended use. The performance data section refers to compliance with general medical device standards (e.g., IEC 80601-2-26:2019 for EEG performance) rather than specific acceptance criteria for diagnostic performance outcomes.

Therefore, many of the requested items cannot be extracted directly from this document. However, I can infer some information based on the provided text.

Here's a breakdown of what can and cannot be answered:

1. A table of acceptance criteria and the reported device performance

Limitations: The document does not specify quantitative acceptance criteria (e.g., "EEG noise must be

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The WR19 System is intended for prescription use in a health care facility or clinical research environment to acquire, transmit, display and store primarily EEG and optional auxiliary signals for adults and children, not including newborns.

The WR19 System requires operation by a healthcare professional familiar with EEG.

The WR19 System acquires, transmits, displays and stores electroencephalogram (EEG), and optionally electrocardiogram (ECG), accelerometer, photic sensor, external trigger signals and video.

The WR19 System is primarily intended to acquire, transmit, display and store EEG and optionally do so for auxiliary signals. WR19 headset is designed to perform Routine or Outpatient EEG using 19 dry signal electrodes and 1 dedicated dry ground/driven-right-leg (DRL) electrode, adjusted and placed to comply with the 10-20 EEG system.

The device consists of the following components:

• . Headset
• Electrodes (affixed to the underside of the headset) ●
• Charger
• Charging cable .
• Software ●
  • Headset firmware -
  • Client application -
  • Data center application

Here is an analysis of the acceptance criteria and supporting study for the WR19 System, based on the provided document:

Acceptance Criteria and Device Performance

The document does not explicitly present a table of acceptance criteria with corresponding performance metrics in a single, clear format as might be desired for a device performance study. Instead, it describes performance testing outcomes and comparisons to a predicate device. The primary performance criteria are implicitly related to the ability of the WR19 System to acquire EEG signals comparably to a legally marketed predicate device (XLTEK EMU40EX) and meet established electrical and safety standards.

Here's an attempt to synthesize the acceptance criteria and stated performance based on the "510(k) Summary" and "PERFORMANCE DATA" sections, particularly "8. CLINICAL PERFORMANCE TESTING":

Study Details

1. Sample size used for the test set and the data provenance:

   • Test Set Sample Size: 7 subjects.
     • 2 cohorts: EEG patients and healthy volunteers.
     • Recording durations: 15-30 minutes for 2 subjects (EEG patients and healthy volunteers) and 2 hours for 3 healthy volunteers.
   • Data Provenance: The study was conducted "at a United States hospital." This indicates prospective data collection for this specific study.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • The document does not specify the number of experts used to establish ground truth or their qualifications. The phrase "qualitative waveform comparisons" suggests expert review, but details are absent.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

   • The document does not describe any specific adjudication method for the test set.

4. 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:

   • No. This was not an MRMC comparative effectiveness study involving AI assistance for human readers. The study compared the signal quality of the WR19 System (which is an EEG acquisition device) to another EEG acquisition device. There is no mention of AI in the context of improving human reader performance.

5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:

   • Yes, in essence, but not in the context of an "AI algorithm." The "standalone" performance here refers to the device's ability to acquire and produce EEG signals. The clinical performance testing ("8. CLINICAL PERFORMANCE TESTING") evaluates the device's inherent signal quality and functionality (e.g., contact quality detection feature, various auxiliary signals). This is a standalone evaluation of the device's performance characteristics.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • The "ground truth" for the clinical performance study was established by comparing the WR19 System's EEG signals to those obtained from a "common EEG device cleared in K163163 - XLTEK EMU40EX." This implies a comparison to an established, legally marketed predicate device's output considered to be the standard for EEG signal quality. The evaluation metrics included "qualitative waveform comparisons, Likert scoring, and spectral correlation and SNR comparisons." This suggests expert qualitative review and quantitative signal analysis relative to the predicate.

7. The sample size for the training set:

   • The document does not mention a training set in the context of the clinical performance study. The WR19 System is an EEG acquisition device, not a diagnostic AI algorithm that typically requires a large training dataset. The software components are described as firmware, client application, and data center application, performing functions like presenting waveforms, controlling sessions, and standard EEG transformations (filters, montages), not complex pattern recognition that would necessitate a traditional "training set."

8. How the ground truth for the training set was established:

   • Not applicable as no training set (in the AI/machine learning sense) is described for the clinical performance study.

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