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The Zmachine Synergy is an EEG and respiratory signal recorder. The device is intended for use by adult patients in the home or clinical environment, under the direction of a qualified healthcare practitioner, to aid in the diagnosis of sleep disorders.

The Zmachine Synergy system is a portable, battery operated, medical device housed within an ABS enclosure. The system combines the single-channel EEG recording capability of the Zmachine DT-100 (K101830) with the respiratory signal recording capability of the Resmed ApneaLink Air (K143272). The Zmachine Synergy is thereby capable of recording EEG, respiratory airflow, respiratory effort, blood oxygen saturation, pulse rate, and body position during sleep.

The provided text focuses on establishing substantial equivalence for the Zmachine Synergy device by comparing it to predicate devices (Zmachine DT-100 and ApneaLink Air) through technical and bench testing. It does not contain information about clinical study data, ground truth establishment by experts, or MRMC studies that would typically be associated with AI/algorithm performance claims.

Therefore, many of the requested categories cannot be fully addressed based on the provided document.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

The document describes "bench comparison testing" where the Zmachine Synergy was compared against predicate devices. The "acceptance criteria" are implied to be "substantially equivalent" or "high agreement" between the Zmachine Synergy and the predicate devices for each measured parameter.

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

The study described is bench testing, not a clinical study involving patients or a test set of data in the typical sense for algorithm performance. The "test set" consisted of:

• A multi-channel EEG analog playback system for EEG.
• A variable pressure air pump for Respiratory Airflow.
• Controlled belt stretching and relaxing against a linear scale for Respiratory Effort.
• A patient simulator for Pulse Oximetry.
• Rotation against an angular reference for Body Position.

Therefore, traditional "sample size" is not applicable, as these were controlled bench tests. Data provenance is specific to the synthetic signals generated by the test equipment.

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

Not applicable. The "ground truth" for these bench tests was established by the precise outputs of the test equipment (e.g., specific frequencies, known pressure values, specific angles) and the design specifications of the devices themselves. No human expert adjudication was involved in establishing this "ground truth."

4. Adjudication Method for the Test Set

Not applicable. There was no human adjudication as the tests were performed against known physical inputs from laboratory equipment.

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

No. The provided text does not describe an MRMC study. The study focuses on comparing the fundamental signal acquisition characteristics of the Zmachine Synergy with its predicate devices at a technical, hardware level, not on assessing how human readers perform with or without AI assistance.

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

Partially applicable, but for hardware performance, not an algorithm's diagnostic output. The "standalone" performance described is the ability of the Zmachine Synergy's hardware components to accurately acquire and record various physiological signals, as compared to predicate devices or known inputs, without human interpretation of derived diagnostic information. The device is an "EEG and respiratory signal recorder" intended to "aid in the diagnosis of sleep disorders," implying subsequent human interpretation of the recorded signals. The described tests confirm the accuracy of the recording capabilities, which is a form of standalone performance for the signal acquisition hardware. Specific algorithm performance for detecting sleep disorders based on these signals is not detailed.

7. The Type of Ground Truth Used

The ground truth used was synthetic signals from laboratory equipment and design specifications/known outputs.

• For EEG: Broad spectrum shaped white noise and zero-level output signal.
• For Respiratory Airflow: Stepped variable air pressure signal.
• For Respiratory Effort: Controlled belt stretching and relaxing against a linear scale.
• For Pulse Oximetry: Specified calibrator output levels from a patient simulator.
• For Body Position: An angular reference the device was rotated against.

8. The Sample Size for the Training Set

Not applicable. This document describes a pre-market notification for a medical device (Zmachine Synergy), focusing on demonstrating substantial equivalence through technical bench testing of hardware components. It does not involve a training set for an AI or machine learning algorithm.

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

Not applicable. As there is no training set mentioned or implied for an AI/ML algorithm within this document, the method of establishing its ground truth is irrelevant here.

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The CRI Zmachine is a single-channel, EEG acquisition and analysis system, designed for use in the home or clinical environments. This device is intended to be used by qualified healthcare practitioners to monitor the wake and sleep states of adult patients and as an adjunct to their diagnosis of sleep disorders.

The CRI Zmachine is a battery-operated, single-channel, EEG acquisition and analysis system. The Zmachine system includes the Zmachine device, disposable EEG sensors, sensor cable, and a wall charger. The device operates on data from the differential-mastoid EEG channel to determine the wake and sleep states (wake, light sleep, deep sleep and REM) of the patient every 30 seconds.

Here's the breakdown of the acceptance criteria and study information for the Zmachine DT-200, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the Zmachine DT-200 are implicitly established by demonstrating substantial equivalence to predicate devices, particularly the Sleep Profiler (K120450). The performance metrics used for comparison are P1 (sensitivity) and P2 (positive predictive value) for each sleep stage.

Note: "Similar to Predicate" is the implicit acceptance criterion. The document states, "The P1 and P2 values obtained during clinical validation of the Zmachine Algorithm are similar to those obtained by the predicate Sleep Profiler algorithm."

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

• Sample Size: 99 subjects (52 female / 47 male, 18-60 years, median age 32.7 years).
• Data Provenance: The document does not explicitly state the country of origin. It indicates the study subjects included those reporting normal sleep and those with complaints consistent with various sleep disorders. The study is described as "clinical," suggesting it's prospective, but this is not explicitly stated. It is a clinical study in which overnight laboratory polysomnographic (PSG) data was acquired.

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

• Number of Experts: Two to four (2-4) certified polysomnographic technologists.
• Qualifications of Experts: Certified polysomnographic technologists.

4. Adjudication Method for the Test Set

• Adjudication Method: Majority voting rule. The individual score files from the 2-4 technologists were combined, on a 30-second epoch basis, using a majority voting rule to generate a single score file per subject ("Human Scores").

5. 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 MRMC comparative effectiveness study was done involving human readers with and without AI assistance. This study focused on the standalone performance of the Zmachine algorithm compared to human consensus.

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

• Yes, a standalone study was done. The Zmachine Algorithm's performance was evaluated by directly comparing its output to the "Human Scores" (ground truth). The objective was to assess the algorithm's ability to determine wake and sleep states independently.

7. The Type of Ground Truth Used

• Type of Ground Truth: Expert consensus. The ground truth, referred to as "Human Scores," was established by comparing the Zmachine Algorithm's output against the scores generated by multiple certified polysomnographic technologists using a majority voting rule, based on standard PSG channels. The scoring guidelines used were Rechtschaffen and Kales (R&K) visual sleep staging guidelines.

8. The Sample Size for the Training Set

• The document does not provide information regarding the sample size used for the training set for the Zmachine DT-200. It focuses on the clinical performance testing sample.

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

• The document does not provide information on how the ground truth for any training set was established for the Zmachine DT-200.

Ask a specific question about this device

The CRI Zmachine is a single-channel, EEG acquisition and analysis system, designed for use in the home or clinical environments. This device is intended to be used by qualified healthcare practitioners to monitor the wake and sleep states of adult patients and as an adjunct to their diagnosis of sleep disorders.

The CRI Zmachine is a battery-operated, single-channel, EEG acquisition and analysis system. The Zmachine system includes the Zmachine device, disposable EEG sensor cable, and a wall charger. The device operates on data from the differential-mastoid EEG channel to determine the wake and sleep states of the patient every 30 seconds.

Here's a summary of the acceptance criteria and the study proving the device meets them, based on the provided text:

Zmachine® Acceptance Criteria and Performance Study

The Zmachine® is a single-channel EEG acquisition and analysis system designed to monitor wake and sleep states in adult patients and as an adjunct to the diagnosis of sleep disorders. Its performance was evaluated against human scoring consensus.

1. Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance for Test Set

• Sample Size: 99 subjects.
• Data Provenance: Not explicitly stated, but implied to be from a clinical study where polysomnographic (PSG) data was acquired. The location (country) is not specified. The study was prospective in the sense that the Zmachine data was acquired simultaneously with PSG data for the purpose of the study.

3. Number and Qualifications of Experts for Ground Truth

• Number of Experts: At least two (2) certified polysomnographic technologists per PSG record (3 records scored by 2, 16 records scored by 3, and 80 records scored by 4 technologists).
• Qualifications: Certified polysomnographic technologists. No specific experience level (e.g., "10 years of experience") is mentioned.

4. Adjudication Method for Test Set

The adjudication method used was a consensus of human scorers. Specifically:

• 3 records were scored by 2 technologists.
• 16 records were scored by 3 technologists.
• 80 records were scored by 4 technologists.
  The consensus was then used as the ground truth.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No, an MRMC comparative effectiveness study examining the effect size of human readers improving with AI vs. without AI assistance was not conducted or reported. The study focused on the standalone performance of the Zmachine algorithm against human consensus.

6. Standalone (Algorithm Only) Performance Study

Yes, a standalone performance study was conducted. The performance metrics (specificity, sensitivity, and Kappa agreement) directly reflect the Zmachine algorithm's ability to determine wake/sleep states without human intervention, compared to the expert ground truth.

7. Type of Ground Truth Used

The ground truth used was expert consensus based on visual sleep scoring rules (Rechtschaffen & Kales R&K, 1968) of polysomnographic (PSG) data.

8. Sample Size for the Training Set

The document does not specify the sample size used for the training set. It only describes the clinical study for performance testing.

9. How Ground Truth for Training Set Was Established

The document does not provide details on how the ground truth for the training set was established. It describes the Zmachine's EEG analysis methodology as a "Proprietary adaptive algorithm using time and frequency domain features," but offers no information regarding its development or the data used for training.

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