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The device is intended to measure, amplify, and record physiological signals acquired from a patient for archival in a sleep study. The physiological signals and conditioned for analysis and display. The data may be analyzed in real-time or offline on dedicated polysomnography software running on a personal computer by a qualified sleep clinician to aid in the diagnosis of Sleep Disorders.

The device is intended for use by healthcare professionals within a hospital, laboratory, clinic, or nursing home; or outside of a medical facility under direct supervision of a medical professional.

The device is intended for use on both adults and children only under the direction of a physician or qualified sleep technician.

The device or any accessory, does not include alarms, and is not intended to be used as a critical component of an alarm system.

The device or any accessory, is not to be used alone as an apnea monitor or as a component in an apnea monitoring system.

The device or any accessory, is not to be used alone as a life support device or as a critical component of a life support system.

The Polysmith Sleep System, Model NTI6600 is intended to amplify and record physiologic potentials used for Polysomnography (PSG) or Sleep Studies. The device consists of a compatible amplifier, head box, PC, patient sensors, and may include optional external devices, USB DC Box, and audio/video input devices.

Compatible amplifiers may use commercially available sensors and electrodes, an internal SpO2 module, and internal pressure transducers to collect, digitize, and send physiological signals to the host PC.

The Polysmith software may record from video, speaker and microphone equipment. The Polysmith software may also record auxiliary signals from compatible amplifiers or USB DC Box which allow for data inputs from compatible sources.

Polysmith records and displays the data for online or offline review. Qualified practitioners use the information to score Polysomnograms and diagnose Sleep Disorders.

Here's a breakdown of the acceptance criteria and study details for the Polysmith Sleep System, Model NTI6600, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state "acceptance criteria" as separate performance thresholds the device must meet. Instead, it presents the "Automated Analysis Agreement" as the device's performance, which is then compared against "Average Human Scoring Agreement." Assuming the implied acceptance is substantial equivalence to human performance for these metrics, the table is structured as follows:

In the "Additional Sleep Staging Analysis," which seems to be a more detailed analysis, the total agreement for automated scoring against consensus human scoring is:

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

• Sample Size (Automated Analysis): 8,053 recorded epochs, of which 7,606 were scored.
• Sample Size (Additional Sleep Staging Analysis): 20 sleep studies.
• Data Provenance: The studies were chosen at random from existing sleep studies of acceptable signal quality from accredited labs. For the automated analysis, studies were chosen at random from a sleep lab independent of Neurotronics. The document does not specify the country of origin, but given the FDA submission, it's likely US-based or compliant with US standards. The data is retrospective.

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

• Automated Analysis: Two expert scorers from different organizations. Each is a registered sleep clinician with at least 5 years' experience scoring sleep records.
• Additional Sleep Staging Analysis: Three independent scorers. Each is a registered sleep specialist with at least five years' experience in the field. Each had some prior experience using Polysmith to manually score studies.

4. Adjudication Method for the Test Set

• Automated Analysis: The document states "The human scoring was completed by two expert scorers." It then calculates "Average Human Scoring Agreement," implying an average of their individual scores or comparison. It doesn't explicitly describe an adjudication process for disagreements between the two human scorers to establish a single ground truth for direct comparison with the automated analysis. Instead, it compares the automated system's performance against this average human agreement, and also compares the two human scorers' agreement with each other.
• Additional Sleep Staging Analysis: This section explicitly used a majority method (2/3 majority-rule) to establish the "true sleep staging (consensus)." Epochs where there was no agreement among the human scorers were discarded (non-consensus).

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

• No, a direct MRMC comparative effectiveness study "with AI vs without AI assistance" was not explicitly described in the context of improving human reader performance. The study focused on the standalone performance of the automated analysis system compared to human scoring. While humans scored the data, the goal was to assess the device's accuracy relative to human experts, not to measure the improvement in human performance aided by the device.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Yes, a standalone performance analysis was conducted. The "Automated Analysis Agreement" and the "Results" section for "Additional Sleep Staging Analysis" directly report the performance of the algorithm itself against human expert assessments (either average or consensus). The scorers for the "Additional Sleep Staging Analysis" were explicitly provided with a version of Polysmith that "did not have any automated analysis capability," emphasizing that the human scoring served purely as ground truth.

7. The Type of Ground Truth Used

• Expert Consensus / Expert Scoring: For both analyses, the ground truth was established by human expert scorers. In the "Automated Analysis," it's based on two expert scorings. In the "Additional Sleep Staging Analysis," it's based on a 2/3 majority rule consensus of three expert scorers.

8. The Sample Size for the Training Set

• Not provided. The document states, "The studies used for this testing were not used to train the algorithm," but it does not specify the size or characteristics of the training set used for the algorithm's development.

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

• Not provided. The document focuses solely on the ground truth for the test sets and explicitly states the test sets were not used for training. Information on how the training data's ground truth was established is absent.

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The device is intended to acquire, store, and transfer biophysical parameters to EEG machines. The device is intended to acquire, store, record, measure and display cerebral and extracerebral activity for EEG and Sleep Studies. These data, may be used by the clinician in Sleep Disorders, Epilepsies and other related disorders as a diagnostic tool.

The product is comprised of telemetry unit, Electrode junction box and access point to operate with our current commercially available EEG devices. The basic measurement data includes: EEG, EOG, ECG, EMG, respiration, periodic limb movement (PLM), snore, SpO2 and sleep position.

Here's an analysis of the provided text regarding the acceptance criteria and supporting study for the Nihon Kohden Wireless Input Unit (K033475):

Based on the provided text, the device K033475 is a Wireless Input Unit for Electroencephalographs (EEG). The information emphasizes that the device's technological characteristics are the same as the predicate device (Siesta system by Compumedix, K003175) and that it was verified and validated using the same test methods as with the existing device. This strongly suggests that the acceptance criteria are based on equivalence to the predicate device and established performance of existing Nihon Kohden EEG machines, rather than new, independently established performance metrics against a clinical ground truth.

Therefore, the requested information about device performance against specific acceptance criteria, sample sizes for test/training sets, expert adjudication, MRMC studies, or standalone performance against pathology/outcomes data is largely not applicable in the traditional sense of a de novo AI/medical device study. This is a 510(k) submission for a device demonstrating substantial equivalence to a predicate.

Acceptance Criteria and Reported Device Performance

Study Details

Given the nature of a 510(k) submission for substantial equivalence based on a predicate and existing devices, the "study" described is primarily one of verification and validation against established engineering and functional specifications, rather than a clinical trial to determine new performance metrics.

1. Sample Size Used for the Test Set and Data Provenance:

   • Test Set Sample Size: Not explicitly stated as a clinical "test set" in the context of diagnostic performance against a ground truth. The text mentions "operation of the device was appropriately verified and validated." This typically refers to engineering testing (e.g., signal fidelity, wireless range, data transfer integrity, power consumption, software functionality) using test environments and perhaps a limited number of human subjects for usability and basic function checks. No specific number of patient samples is provided for a performance study.
   • Data Provenance: Not applicable. The validation would be against technical specifications and existing device performance, not a specific dataset derived from a country of origin. The testing would have been conducted by Nihon Kohden America, Inc. or its affiliates.

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

   • Not applicable for this type of submission. Ground truth in the sense of expert consensus on clinical diagnoses (e.g., presence of epilepsy, sleep disorders) for a test set is not mentioned, as the device is an input/transfer unit, not a diagnostic algorithm itself. The "ground truth" for its operation would be defined by the technical specifications of the signals it acquires and transmits, and how accurately it correlates with the existing cleared EEG machines.

3. Adjudication Method for the Test Set:

   • Not applicable. Since there's no mention of a diagnostic performance study against a clinical ground truth, no adjudication method would be required.

4. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and its effect size:

   • No, an MRMC study was not done. This type of study is relevant for diagnostic algorithms where human readers interpret medical images or data. The Wireless Input Unit is a data acquisition and transfer device; it doesn't involve human interpretation to arrive at a diagnosis.

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

   • Yes, in essence, standalone technical verification was performed. The phrase "operation of the device was appropriately verified and validated using the same test methods as with the existing device" implies performance testing of the device's technical capabilities (signal acquisition, transmission, storage) independent of a human operator making diagnostic decisions. However, this is for the functionality of the unit, not for a diagnostic algorithm.

6. The type of ground truth used:

   • Technical Specifications and Performance of Predicate/Existing Cleared Devices: The "ground truth" for this submission is the established and cleared performance characteristics of the predicate device (Siesta system) and other Nihon Kohden EEG machines (EEG-1100A, EEG-9100A) to which this wireless unit connects. The wireless unit is intended to perform identically in terms of data acquisition and transfer fidelity to these existing systems.

7. The sample size for the training set:

   • Not applicable. This device does not involve machine learning or AI algorithms that require a "training set."

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

   • Not applicable. See point 7.

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