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.

Device Description

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.

AI/ML Overview

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

Metric	Acceptance Criteria (Threshold for "high association")	Reported Device Performance
Zmachine Specificity (Wake)	Not explicitly stated, but implied by overall Kappa	91.6%
Zmachine Sensitivity (Sleep)	Not explicitly stated, but implied by overall Kappa	95.8%
Overall Kappa Agreement	0.75	0.8275

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.

Summary

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K101830

Zmachine® 510(k) Summary

Submitter	Consolidated Research of Richmond, Inc.
Address	26250 Euclid Avenue, Suite 024Euclid, Ohio 44132
Contact Person	Richard F. Kaplan, Ph.D., PresidentPhone: (216) 289-2331Fax: (216) 393-0079E-mail: kaplan@cri-systems.com
Date Prepared	March 28, 2011
Trade Name	Zmachine®
Common Name	Sleep monitoring system
ClassificationName	Electroencephalograph
Classification	21 CFR (882.1400)
Product Codes	OLV and OMC
510(k) Number	K101830
Indicationsfor Use	The CRI Zmachine is a single-channel, EEG acquisitiondesigned for use in the home or clinical environmentintended to be used by qualified healthcare practitioners

ition and analysis system, ts. This device is ners to monitor the wake and sleep states of adult patients and as an adjunct to their diagnosis of sleep disorders.

MAR 3 1 20i1

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Device Description

Substantial Equivalence

The Zmachine is substantially equivalent to the Oxford Biosomnia device, manufactured by Oxford Biosignals Limited (K021485). The table below summarizes the technological characteristics of the Zmachine in comparison to the predicate device.

Device	Zmachine	BioSomnia
Classification	21 CFR (882.1400)	21 CFR (882.1400)
Product Code(s)	OLV and OMC	GWQ
Indications for Use	The CRI Zmachine is a single-channel, EEG acquisition andanalysis system, designed for use inthe home or clinical environments.This device is intended to be usedby qualified healthcare practitionersto monitor the wake and sleep statesof adult patients and as an adjunctto their diagnosis of sleep disorders.	The Oxford BioSignals BioSomniais a single channel ambulatory EEGwith a software package designedfor use as an adjunct for thephysician in their diagnosis of sleepdisorders and to quantify sleep andwakefulness on a second by secondbasis. The device is designed to beused overnight in the patient's homeenvironment to assist the physicianin diagnosing sleep disorders.
Patient Population	Adults	Adults
Type of Device	EEG-based sleep monitor	EEG-based sleep monitor
No. of EEG Channels	1	1
Electrode Placement	Mastoid	MastoidFrontalEOG UpperCentral
Analyzes EEG Data inReal Time	Yes	Yes
Sleep Classification	Wake and Sleep	Wake and Sleep (light sleep, deepsleep, and REM sleep)
EEG AnalysisMethodology	Proprietary adaptive algorithmusing time and frequency domainfeatures	Proprietary artificial neuralnetwork-based algorithm
Can ProvideInformation to Assistthe Physician inDiagnosis of SleepDisorders?	Yes	Yes
Can ProvideInformation to Assistthe Physician in theApplication ofTreatment?	Yes	Yes

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Device	Zmachine	BioSomnia
Provides Informationto Assist Physician inthe Evaluation ofTreatment Efficacy?	Yes	Yes
Calculates SummarySleep Statistics?	Yes	Yes
Battery Powered?	Yes	Yes

Performance Testing - Nonclinical

The Zmachine system has been assessed against the following standards:

Electrical safety in accordance with IEC 60601-1, Medical Electrical Equipment - Part 1: General Requirements for Safety: Safety Requirements for Medical Electrical Systems;

Electromagnetic compatibility in accordance with IEC 60601-1-2, Medical Electrical Equipment -Part 1-2: General Requirements for Safety - Collateral Standard: Electromagnetic Compatibility --Requirements and Tests. (General).

In addition, software testing was performed in accordance with FDA guidance, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices- Document issued on: May 11, 2005" regarding a moderate level of concern device:

Performance Testing - Clinical

A ninety-nine subject (99) clinical study was conducted in which polysomnographic (PSG) data was acquired and analyzed by human scorers, and simultaneously data from the mastoid was acquired and processed by the Zmachine wake/sleep algorithm. Each PSG record was scored independently by at least two (2) certified polysomnographic technologists (3 records scored by 2 technologists, 16 records scored by 3 technologists, and 80 records scored by 4 technologists) using the Rechtschaffen & Kales (R&K, 1968) visual sleep scoring rules. The performance of the Zmachine was evaluated by comparing wake/sleep as determined by the Zmachine algorithm to the consensus of human scorers. The analysis demonstrates substantial agreement for wake/sleep determination, on an epoch-by-epoch basis, between the Zmachine algorithm and the consensus of human scorers. Of the 16,908 epochs indicated by the consensus of human scorers as wake, the Zmachine algorithm correctly identified 91.6% as wake (Zmachine specificity). Similarly, of the 65.873 epochs indicated by the consensus of human scorers as sleep, the Zmachine algorithm correctly identified 95.8% as sleep (Zmachine sensitivity). The overall Kappa agreement between the consensus of human scorers and the Zmachine algorithm is 0.8275, exceeding the 0.75 threshold for "high association". In conclusion, the Zmachine algorithm demonstrates accurate performance in detecting wake and sleep from a single channel (mastoid) of EEG data.

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Conclusion

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This submission demonstrates that the Zmachine is substantially equivalent to the predicate device based on descriptive information, non-clinical and clinical performance testing.

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Image /page/4/Picture/1 description: The image shows the logo for the U.S. Department of Health & Human Services. The logo consists of a circular seal with the text "DEPARTMENT OF HEALTH & HUMAN SERVICES - USA" around the perimeter. Inside the circle is a stylized image of an eagle or bird-like figure with three overlapping profiles.

Food and Drug Administration 10903 New Hampshire Avenue Document Control Room W-066-0609 Silver Spring, MD 20993-0002

Consolidated Research of Richmond, Inc. President % Richard Kaplan, Ph.D. 26250 Euclid Ave. Suite 024 Euclid, OH 44132

Re: K101830

MAR 3 1 2011

Trade/Device Name: ZMachine, Model DT-100 Regulation Number: 21 CFR 882.1400 Regulation Name: Electroencephalograph Regulatory Class: Class II Product Code: OLV and OMC Dated: February 1, 2011 Received: February 4, 2011

Dear Dr. Kaplan:

We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.

If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.

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Page 2 - Richard Kaplan, Ph.D.

Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting (reporting of medical device-related adverse events) (21 CFR 803); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820); and if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.

If you desire specific advice for your device on our labeling regulation (21 CFR Part 801), please go to http://www.fda.gov/AboutFDA/CentersOffices/CDRH/CDRHOffices/ucm117800 html fou the Center for Devices and Radiological Health's (CDRH's) Office of Compliance. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to

http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/default.htm for the CDRH's Office of Surveillance and Biometrics/Division of Postmarket Surveillance.

You may obtain other general information on your responsibilities under the Act from the Division of Small Manufacturers, International and Consumer Assistance at its toll-free number (800) 638-2041 or (301) 796-7100 or at its Internet address http://www.fda.gov/MedicalDevices/ResourcesforYou/Industry/default.htm.

Sincerely vours.

Malvina B. Eydelman, M.D. Director Division of Ophthalmic, Neurological, and Ear. Nose and Throat Devices Office of Device Evaluation Center for Devices and Radiological Health

Enclosure

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Indications for Use Statement

510(k) Number: K101830

Device Name: Zmachine

Indications for Use: 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.

Prescription Use Over-The-Counter Use X AND/OR (Part 21 CFR 801 Subpart D) (21 CFR 801 Subpart C) (PLEASE DO NOT WRITE BELOW THIS LINE-CONTINUE ON ANOTHER PAGE IF NEEDED)

Concurrence of CDRH, Office of Device Evaluation (ODE)

KRISTEN BOWSHER

(Division Sign-Off) (Division Sign-Orr)
Division of Ophthalmic, Neurological and Ear, Nose and Throat Devices

KIO| 830 510(k) Number,

Regulation Number and Section

§ 882.1400 Electroencephalograph.

(a)
Identification. An electroencephalograph is a device used to measure and record the electrical activity of the patient's brain obtained by placing two or more electrodes on the head.(b)
Classification. Class II (performance standards).