The Neurometric Analysis System (NAS) is to be used by qualified medical professionals for the post-hoc statistical evaluation of the human electroencephalogram (EEG).

Device Description

The Neurometric Analysis System (NAS) is a software program for the post-hoc statistical analysis of the human electroencephalogram (EEG). Digital EEG data from a host system is transferred to the NAS for display and user-review. The system requires that the user select approximately 2.00 minutes of artifact-free, eyes-closed, resting EEG from the recording for analysis. Analysis consists of the Fast-Fourier Transformation (FFT) of the data to extract the spectral power for each of the four primary frequency bands (delta, theta, alpha, and beta), and frequency information from the EEG. The results of this analysis are then subjected to univariate, bivariate, and multivariate statistical analyses and displayed in statistical tables and topographical brain maps of absolute and relative power, power asymmetry, and coherence for 19 monopolar and 8 selected bipolar derivations of the EEG. In all over 1200 measures are derived for comparison against a carefully constructed and statistically controlled age-regressed, normative database in which the variables have been transformed and confirmed for their Gaussian distribution. Each variable extracted by the analysis is compared to the database using parametric statistical procedures that express the differences between the patient and their appropriate age-matched reference group in the form of Z-scores. Multivariate features are compared to the normative database using Mahalanobis Distance Statistics. The Mahalanobis Distance statistic controls for the interrelationship of the measures of brain cortical function in the feature set, and provides an accurate estimate of their difference from normal. The multivariate measures permit an evaluation of regional indices of brain function that reflect the perfusion fields of the brain. Extracted feature sets are further analyzed to determine if the pattern of 'hits' (statistically, significant feature score values identified for the patient) are consistent with patterns of 'hits' identified in prior neurometric evaluations of clinical patients with known disorders. A step-wise discriminant analysis program classifies the patient in terms of their similarity to known neurometric-defined patterns of abnormality, providing a probability estimate of the patient's profile with the average profile of groups of individuals constituting the normative and clinical database. The discriminant classification program is restricted by confiniters potential outcomes to specific patient symptoms derived from the patient history. profile. Established discriminant functions were evaluated through the use of Receiver Operating Characteristic (ROC) curves for their sensitivity and specificity. The outcome of the statistical analysis is presented in report form that includes (a) patient demographic and history information, (b) selected EEG epochs, (c) statistical tables of monopolar, the lastery and multivariated feature values, and topographical brain maps. This information is to be read and interpreted within the context of the current clinical assessment of the patient by the attending physician. The decision to accept or reject the results of the neurometric analysis, and incorporate these results into their clinical appraisal of the patient, is dependent upon the judgment of the attending physician.

The Neurometric Analysis System is complete in a set of five 3.5 diskettes, which contains. a demonstration program with sample neurometric studies, the NAS program, and the a demonstration program. The NAS was designed for implementation under DOS and Windows, and programmed using C++. The user interface was carefully designed and implemented to programmed comb procedures are used to record steps used in program usage, and the conduct of the analysis to insure appropriate function and operation of the software. The NAS can be installed in any appropriately configured IBM-compatible computer system, including systems designed specifically for the recording of digital EEG. The system functions with systems access of standard computer platforms and input-output devices, and printers.

AI/ML Overview

The provided text describes the Neurometric Analysis System (NAS) and its evaluation. However, it does not explicitly state quantitative acceptance criteria or a formal study designed to demonstrate compliance with such criteria in the way a modern medical device submission might. Instead, it focuses on demonstrating substantial equivalence to predicate devices and verifying the system's consistency and accuracy with established methods.

Here's an attempt to extract the requested information based on the provided text, acknowledging where specific details are not available:

1. Table of Acceptance Criteria and Reported Device Performance

As explicit, quantitative acceptance criteria are not presented in the document, this table will reflect the qualitative criteria and claims made about the device's performance based on consistency with established methods and existing data.

Acceptance Criteria (Inferred from text)	Reported Device Performance
Non-clinical:
- Accuracy of signal generation and frequency/power analysis.	Control signals (generated waveforms) were analyzed for frequency and power, and EEG signals were analyzed for conformity between the host digital EEG system and the NAS. The NAS accurately reproduced the sampling frequency in the host digital EEG system and allowed correct translation of EEG waveforms.
- Consistency and accuracy of NAS analysis compared to prior neurometric methods/software using stored subject data.	Analysis of stored subject data had to conform to that of prior analyses conducted using the same method, procedures, algorithms, and analysis as implemented on the NAS. This consistency and accuracy was confirmed.
Clinical:
- Agreement of NAS analysis results (statistical tables, topographical brain maps) with results from the host system at Brain Research Laboratory.	The results of the NAS analysis (statistical tables and topographical brain maps) were in agreement with the results of the analysis conducted on the host system used in processing patient information at BRL.
- Consistency of discriminant analysis outcome without misclassification errors compared to the host system at BRL.	The outcome of the discriminant analysis was consistent, not resulting in misclassification errors (i.e., classification on NAS was consistent with that of the host system at BRL).
- Reproducibility of results within an acceptable degree of variation when using artifact-free, eyes-closed, resting EEG.	When eyes-closed, resting, and artifact-free EEG was selected for analysis, the results were reproducible within an acceptable degree of variation consistent with reliability estimates identified in normative studies.
- Safety and effectiveness as an adjunctive aid for diagnosis, treatment planning, and follow-up.	Demonstrated through 20 years of non-clinical and clinical testing, concluding the NAS is safe and effective for quantitative analysis of eyes-closed resting EEG in alert human subjects, providing complementary and supplementary information to traditional EEG. When properly used as an adjunctive aid, it significantly reduces the likelihood of introducing error into diagnosis and treatment.

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

Test Set Sample Size: The document does not specify a distinct "test set" sample size for the clinical testing in terms of a specific number of individuals for a standalone validation study. Instead, it refers to "individuals who ranged in age from 6 to 90 years, and who were either volunteers or clinical patients referred for neurometric evaluation to the Brain Research Laboratory."
Data Provenance: The data used for clinical testing originated from the Brain Research Laboratory (BRL) at New York University's Medical Center. This involved a 20-year effort to construct a normative and clinical database. The data appears to be retrospective in the sense that the initial development and evaluation were based on this existing, large database and methods developed at BRL over time. The "clinical testing" section describes confirming the NAS's output against the "host system" used at BRL, suggesting re-analyzing existing patient data.

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

The document does not explicitly state the "number of experts" used to establish ground truth for a discrete test set. The ground truth appears to be implicitly established by the long-standing clinical practice, established neurometric methods, and accumulated knowledge within the Brain Research Laboratory (BRL) at New York University's Medical Center, including comparisons to "known disorders" and established "patterns of abnormality."
Qualifications of Experts: The initial development and database construction involved "numerous government and privately funded normative and clinical database projects" carried out at the BRL. This implies highly qualified researchers and medical professionals (including those from the Department of Psychiatry and Department of Neurology at NYU Medical Center) were involved in generating and interpreting this data over 20 years. The interpretation of the NAS's output is also left to the "attending physician" who is a "qualified medical professional."

4. Adjudication Method for the Test Set

The document does not describe a formal adjudication method (e.g., 2+1, 3+1) for establishing ground truth for a specific test set. The clinical evaluation primarily focused on ensuring the NAS's results were consistent with analyses performed on the "host system" at the Brain Research Laboratory, which itself utilized discriminant analysis evaluated by Receiver Operating Characteristic (ROC) curves for sensitivity and specificity. The "ground truth" seems to be derived from the extensive pre-existing normative and clinical database and established methods at BRL, rather than a de novo expert adjudication process for this specific submission.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and the effect size of how much human readers improve with AI vs. without AI assistance

No MRMC comparative effectiveness study was described. The evaluation focused on the device's consistency with established methods and its utility as an adjunct to clinical assessment, rather than a direct comparison of human performance with and without the device. The text emphasizes that the NAS provides information that "complements and supplements the outcome of the analysis of a traditional EEG" and that "the decision to accept or reject the results... is dependent upon the judgment of the attending physician." It also warns against using the device as a "standalone diagnostic tool."

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

Yes, a form of standalone performance evaluation was done, specifically in the non-clinical and clinical testing where the NAS's output was compared directly against the results from the "host system" at the Brain Research Laboratory. The non-clinical testing involved analyzing generated waveforms and ensuring conformity between the host digital EEG system and the NAS, as well as confirming consistency with prior analyses of stored subject data. The clinical testing confirmed the agreement of statistical tables and brain maps, and the consistency of discriminant analysis with the BRL host system. This suggests an evaluation of the algorithm's output in isolation compared to a known reference standard (the BRL-established methods and system).

7. The Type of Ground Truth Used

The ground truth used is primarily expert consensus and established clinical practice/data from a long-standing research institution (Brain Research Laboratory at NYU Medical Center). This includes:
- Comparison against a "carefully constructed and statistically controlled age-regressed, normative database."
- Comparison of 'hits' against "patterns of 'hits' identified in prior neurometric evaluations of clinical patients with known disorders."
- Discriminant analysis based on known neurometric-defined patterns of abnormality.
- ROC curves for sensitivity and specificity of established discriminant functions.

8. The Sample Size for the Training Set

The document does not explicitly delineate a "training set" in modern machine learning terms with a specific sample size. Instead, it refers to a "carefully constructed and statistically controlled age-regressed, normative database" and a "clinical database" developed over a 20-year effort at the Brain Research Laboratory. This extensive database served as the foundation for the statistical models and comparisons used by the NAS. While no single number is given, the implication is a very large and comprehensive dataset accumulated over two decades.

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

The ground truth for this extensive database (which effectively serves as the "training" and "reference" for the NAS) was established through:
- Rigorous data collection: "numerous government and privately funded normative and clinical database projects."
- Careful construction of normative data: "carefully constructed and statistically controlled age-regressed, normative database in which the variables have been transformed and confirmed for their Gaussian distribution."
- Clinical validation: Inclusion of "clinical patients with known disorders" whose "patterns of 'hits'" (statistically significant feature score values) were identified in prior neurometric evaluations.
- Statistical methods: Use of parametric statistical procedures, Z-scores, Mahalanobis Distance Statistics, and step-wise discriminant analysis.
- Expert experience: The entire process was guided by the "extensive, 20-year effort" and expertise at the Brain Research Laboratory, involving medical professionals from Neurology and Psychiatry departments who defined clinical reference groups and patterns of abnormality.

Summary

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0.03

JUL 10 1998

K974748
FDA 510(k) Summary

Section 807.92

(a)(1). Submitter's Name: NxLink, Ltd., 1706 Gaillard Place, Richland, WA. 99352. Phone: (509)-943-1023; Fax: (509)-946-1208; email: nxduane@oneworld.owt.com.

Contact Person: Duane Shuttlesworth, Ph.D. NxLink, Ltd., 1706 Gaillard Place, Eichland, WA. 99352. Phone: (509)-943-1023; Fax: (509)-946-1208; email: nxduane@oneworld.ow.com.

Date of preparation: 10/25/97

(a)(2). Name of the Device: Neurometric Analysis System (NAS). Classification name: EEG Frequency Spectrum Analyzer.

(a)(3). Predicate/legally marketed devices upon which substantial equivalence is (a)(a); I resicatellerie any and acter to PDA information available); TECA Corporation Neurolab I, II (K844481), Brain Mapper (K890-881), Neuromapper 386 (K894889); Nicolet BEAM I, II (no FDA 510(k) information available); Pathinder II (K801604) Brain Functional Map (K843598); Cadwell Laboratories, Inc. 8400 (K860801) and Spectrum 32 (K860801 reference); Lexicor Medical Technology Neurosearch-24 Specuran 22 (200000 1 (42020038); Neuroscience, Inc. Map-10 EEG (K840430), (1990-209); 1620 (K870263); Biologics Systems Corporation, Inc., Modified Brain Nethomapper 1020 (107-1209), Automatic Event Analysis (K951594); Quantified Signal Imaging, Inc. QS1-9500 (K904294), QS1-9200 (FDA Š10(k) information not available); Stellate Systems, Inc. Rhythm Software (K912938).

(a)(4). Device Description: The Neurometric Analysis System (NAS) is a software (4)(9). Device Desting statistical analysis of the human electroencephalogram (EEG). program for the poor noo sective (i.e., the host system) is transferred to the NAS for display and user-review. The system requires that the user select approximately 2.00 minutes of artifact-free, eyes-closed, resting EEG from the recording for analysis. Analysis consists of the Fast-Fourier Transformation (FFT) of the data to extract the spectral power for each of the four primary frequency bands (delta, theta, alpha, and beta), and frequency information from the EEG. The results of this analysis are then subjected to univariate, bivariate, and multivariate statistical analyses and displayed in statistical tables and topographical brain maps of absolute and relative power, power asymmetry, and coherence for 19 monopolar and 8 selected bipolar derivations of the EEG. In all over 1200 measures are derived for comparison against a carefully constructed and statistically controlled age-regressed, normative database in which the variables have been transformed and confirmed for their Gaussian distribution. Each variable extracted by the analysis is compared to the database using parametric statistical procedures that express the differences between the patient and their appropriate age-matched reference group in the form of Z-scores. Multivariate features are compared to the normative database using

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l 2

Mahalanobis Distance Statistics. The Mahalanobis Distance statistic controls for the interrelationship of the measures of brain cortical function in the feature set, and provides an accurate estimate of their difference from normal. The multivariate measures permit an evaluation of regional indices of brain function that reflect the perfusion fields of the brain. Extracted feature sets are further analyzed to determine if the pattern of 'hits' (statistically, significant feature score values identified for the patient) are consistent with patterns of 'hits' identified in prior neurometric evaluations of clinical patients with known disorders. A step-wise discriminant analysis program classifies the patient in terms of their similarity to known neurometric-defined patterns of abnormality, providing a probability estimate of the patient's profile with the average profile of groups of individuals constituting the normative and clinical database. The discriminant classification program is restricted by confiniters potential outcomes to specific patient symptoms derived from the patient history. profile. Established discriminant functions were evaluated through the use of Receiver Operating Characteristic (ROC) curves for their sensitivity and specificity. The outcome of the statistical analysis is presented in report form that includes (a) patient demographic and history information, (b) selected EEG epochs, (c) statistical tables of monopolar, the lastery and multivariated feature values, and topographical brain maps. This information is to be read and interpreted within the context of the current clinical assessment of the patient by the attending physician. The decision to accept or reject the results of the neurometric analysis, and incorporate these results into their clinical appraisal of the patient, is dependent upon the judgment of the attending physician.

(a)(5). Statement of Indications of Use: Indications for the use of the Neurometric Analysis System (NAS) are as follows:

Indications of Use

The Neurometric Analysis system is to be used by qualified medical profedssionals for the post-hoc statistical evaluation of the human electroencephalogram (EEG).

(a)(6). Comparison to Predicate Devices: The Neurometric Analysis System uses accepted methods of data selection and analysis to extract the feature measures upon which statistical determination of normal/abnormal are made, and from which derivations of probability estimates of clinical classification are derived. The neurometric method of

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EEG selection, analysis, and interpretation have been previously implemented, in whole on in part, in a variety of digital EEG and analysis systems marketed in prior years for the quantitative analysis of the EEG in Man. The NAS database was carefully constructed to quandtative andiyas of the BLG M. H. J. Type II errors in the use of database comparisons in clinical electrophysiological assessment of the human EEG. The compansons in childed clectrophysions of the NAS has been enhanced relative to these purposendi, caby to ass the careful consideration of user interactions with this technologically advanced method of analysis.

(b). Non-clinical and Clinical Tests: The Neurometric Analysis System's design and implementation was based upon the results of an extensive, 20-year effort to construct a implementative and clinical database at the Brain Research Laboratory (BRL) at New York University's Medical Center. The NAS incorporates the basic methods of data Your children data selection, analysis, and interpretation developed at the BRL during the conduct of numerous government and privately funded normative and clinical database projects.

(b)(1). Non-clinical Testing: Non-clinical testing of the NAS included the evaluation of (0)(1). Non-cannear restlug. Non oneed for data analysis. Specifically, control signals, in the form of signal generated waveforms, were analyzed for frequency and power. EEG signals were analyzed for conformity between the host digital EEG system and the NAS. signals were and your to reproduces sampling frequency in the host digital EEG The 1070 menoves a learing and evaluation of the EEG waveforms for accuracy System, and permans the MAS translation. In addition, data obtained in previous implementations of the neurometric method were evaluated for consistency and accuracythe results of the NAS's analysis of stored subject data had to conform to that of the prior analysis (which was conducted using the same method and procedures, algorithms and method of analysis as that implemented on the NAS).

(b)(2). Clinical Testing: The ability of the NAS to accurately translate and present EEGs from clinical patients was confirmed by the nonclinical testing. In order for the NAS to be an effective implementation of the neurometric method for clinical use, the results of the analysis (both statistical tables and topographical brain maps) had to be in agreement with the results of the analysis conducted on the host system used in the processing of patient information at the Brain Research Laboratory. In addition, the outcome of the discriminant analysis had to be consistent, not resulting in errors of misclassification (that is, the classification on the NAS had to be consistent with that of the host system used to perform the neurometric analysis at the BRL). These tests confirmed that when eyes-closed, resting, and artifact-free EEG was selected for analysis, the results were reproducible within an acceptable degree of variation consistent with reliability estimates identified in the normative studies.

Subjects upon which this device has been tested included individuals who ranged in age from 6 to 90 years, and who were either volunteers or clinical patients referred for neurometric evaluation to the Brain Research Laboratory by the Department of Psychiatry

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and Department of Neurology at New York University Medical Center. The results of the and Department of Neurology at New York Une visa asked to use the information as analysis were conveyed in the recenting prysicial who neaditional EEG. The information
an adjunct to their clinical interpretation of the patiented for statistical tables an adjunct to their clinical interpreation of the poches selected for analysis, staistical tables
was provided in report form (including EPG epochs selected for analysis) to was provided in report form (including LLC Cfreedinant and diagnosis or treat and topographic brain maps, and the result of the clises and disgnosis or treatment
physician to determine its relevance to the clinical evaluation and disgrosis of treatment of the patient. When the results are used in this manner, the likelihood of introducing of the patient. When the results are used in the mannely reduced. That is, the test is viewed as error into diagnosis and treatment is substantially resease. " which he subsidiary basis for the diagnosis.

Potential adverse effects of the use of the device are known if the Neurometric Analysis Potential adverse entects of the use of the Sevien (a use that is specifically contraindicated System is used as a stata-alone angliopers) in the absence of other clinical data from more by NXLMK and the system's developed by this a only upon the use of a single index (such thatitional means of patient overaphical maps alone) without reviewing the traditional as relative power, or the topograpisca inthe complete set of statistical summary tables is
and epochs selected for analysis, or the complete set of statistical summers of sp also contraindicated and a source of potential error. Additional sources of error could arise from the inappropriate selection of EEG (selecting artifacted EEG epochs, or selecting EEG representative of other states, such as drowsiness or eyes-open EEG, or by selecting ECO representative of other than those specified. Additionally, it is purposely selecting concirculars through the purposeful falsification of symptoms in the patient history, and patient age.

(b)(3) Conclusions Drawn From Non-Clinical and Clinical Testing: The appropriate (0)(0) Concellent Dransysis System as an adjunct to the traditional visually-appraised ase of the Noardinonia is and your with the ability to quantify EEG variables and use them to answer questions drawn from their clinical experience with the patient. When used by an experienced, qualified practitioner, or under the proper supervision of a qualified medical professional, the NAS is concluded to be a useful and beneficial addition to the array of clinically accepted medical tests and devices used to evaluate brain structure and finction.

The results of non-clinical and clinical testing conducted over the past 20 years demonstrates that the NAS is both safe and effective for the quantitative analysis of the eyes-closed resting EEG in the alert human subject. Used to determine if the EEG is normal or abnormal, and if abnormal, to statistically characterize the distribution of selected neurometrically-derived features by their probability of being similarly distributed in specified groups of clinical patients, the NAS provides information that both complements and supplements the outcome of the analysis of a traditional EEG. This information, when properly used in conjunction with other clinical tests as a safe and effective adjunctive aid to diagnosis, treatment planning, and treatment follow-up of the neurologic and psychiatric patient.

Compared to its predicate devices, the Neurometric Analysis System's inclusion of specific, appropriate, and effective statistical controls over the method of data selection

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-5 .

and analysis, the scientific rigor involved in the construction, refinement, and application and analysis, the scientific rigor involved in the constition, resulting providers with alle the normative indices of brain structure and finction that is oth safe of the notificative indices of brain structure and tunction the fish of our and of comments.
and effective and suggests hat the NAS is a significant advancement in the use of and effective, suggests that the NAS is a signinoun. Count

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Image /page/5/Picture/1 description: The image shows the logo for the Department of Health & Human Services USA. The logo consists of a circle with the text "DEPARTMENT OF HEALTH & HUMAN SERVICES USA" around the perimeter. Inside the circle is a stylized image of three human profiles facing right, with flowing lines representing hair or clothing.

Food and Drug Administration 10903 New Hampshire Avenue Document Control Room -WO66-G609 Silver Spring, MD 20993-0002

Duane Shuttlesworth,Ph.D. NxLink, Ltd. 1706 Gaillard Place Richland, Washington 99352

Re: K974748

Trade/Device Name: Neurometric Analysis System Regulation Number: 21 CFR 882.1400 Regulation Name: Electroencephalograph Regulatory Class: II Product Code: OLU Dated (Date on orig SE ltr): April 8, 1998 Received (Date on orig SE Itr): April 13, 1998

Dear Mr. Shuttlesworth:

This letter corrects our substantially equivalent letter of July 10, 1998.

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.

APR - 9 2012

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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/ucm115809.htm for 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 yours,

Kesia Alexander

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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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Page 1 of 1

. . . . . .

510(k) Number (if known): K974748

Device Name: Neurometric Analysis System

Indications For Use: The Neurometric Analysis System (NAS) is to be used by qualified medical professionals for the post-hoc statistical evaluation of the human electroencephalogram (EEG).

(PLEASE DO NOT WRITE BELOW THIS LINE-CONTINUE ON ANOTHER PAGE IF NEEDED)

Concurrence of CDRH, Office of Device Evaluation (ODE)
(Division Sign-Off)
Division of General Restorative Devices
510(k) Number	K994748
Prescription UsePer 21 CRF 801.109	OR	Over-The-Counter Use

(Optional Format 1-2-96)

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).