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The Bio-logic Evoked Potential (EP) product family is indicated for use in the recording and analysis of human physiological data necessary for the diagnosis of auditory and hearing-related disorders.

This product, MASTER, like its predicate device, the Navigator Pro, is a diagnostic device intended to be used as part of a set of audiometric test protocols. It is especially indicated for use in defining the configuration of the hearing loss particularly for individuals whose behavioral audiometric results are deemed unreliable, such as infants, young children, and cognitively impaired or uncooperative adults. It allows for the estimation of behavioral hearing threshold at various frequencies, through the use of ABR (Auditory Brainstem Response) or ASSR (Auditory Steady-State Response) test protocols. It is designed to be used as a diagnostic test procedure by individuals who are trained in the performance and interpretation of evoked potentials such as audiologists and physicians. The results of the test will be used by trained hearing health care professionals to make recommendations regarding appropriate intervention strategies.

Bio-logic EP Systems can be used for patients of all ages, from children to adults, including infants and geriatric patients. The use of the Bio-logic EP family of products is to be performed under the prescription and supervision of a physician or other trained health care professional.

The Bio-logic Evoked Potential family of products is intended to be used for the recording and analysis of human physiological data for the purpose of neurological diagnosis and treatment of sensory disorders. The predicate device referenced above is the latest in a series of diagnostic systems of this type marketed by Bio-logic. Other related diagnostic devices in the Evoked Potential family include:

• 510(k) #K803226 Bio-logic Evoked Response Stimulators. 1.
• 510(k) #K842543 Bio-logic Evoked Potential System. 2.
• 510(k) #K844992 Bio-logic Portable Evoked Response System. 3.
• 510(k) #K862690 -- Bio-logic Traveler LT System. 4.
• 5. 510(k) #K930328 - Navigator and Traveler Evoked Potential Product.

The predicate device, the Bio-logic Evoked Potential system with Navigator Pro hardware, performs Evoked Potential recording and analysis functions, including up to 2 channels of data recording and numerous diagnostic protocols and modalities. This new MASTER Evoked Potential with Navigator Pro device performs many of these same functions in essentially the same ways with a one-channel version of the same hardware, but employs a new software application package with significant new capabilities over those of the predicate device. Through the use of the Auditory Steady State Response (ASSR) modality, which is a variant of the MLR / 40 Hz test modality used in the referenced systems already on the market, hearing threshold levels can quickly and reliably be determined based on physiological rather than behavioral means.

The Auditory Steady State Response test is an alternative to tone burst Auditory Brainstem Response (ABR) testing which is used to predict frequency-specific behavioral hearing thresholds particularly for patients who cannot provide a reliable behavioral response. The ASSR technique avoids one of the inherent pitfalls of the tone burst ABR technique which is the problem of "spectral splatter" (distortions in frequency-specific data due to the start/stop actions of the tone burst) of the short duration acoustic stimulus that is required for ABR measurement. The ASSR technique uses a continuous frequency and/or amplitude modulated tone as the stimulus and can combine several stimuli together simultaneously to assess responses to various frequencies all at the same time. The evoked response recorded from scalp electrodes is reflective of the frequency of the modulation envelope of the stimulus. Thus, assessment of the response spectrum can yield information about the presence of the response to stimuli of varying intensities in order to determine the response threshold. ASSR thresholds have a predictable relationship to behavioral thresholds that is dependent on stimulus frequency and the presence and degree of hearing loss.

The MASTER application software is a modification of software originally designed by and exclusively licensed from researchers at the Rotman Research Institute, Baycrest Centre for Geriatric Care, at The University of Toronto. This software was designed originally for research purposes, and Bio-logic made significant modifications to create double fault conditions for any situation that could impact patient safety (e.g. presentation of prolonged, intense acoustic stimuli), to block the user from making parameter changes that are known to result in poor quality data, and to improve overall reliability, performance and ease of use. Additionally, the user interface has been simplified in terms of operation and information display so that only the relevant operations and data are available. More complex functions that do not have clinical relevance were eliminated from the software.

This system will be used to assist in defining the configuration of the hearing loss particularly in populations that are difficult to test using traditional behavioral audiometry. It is designed to be used as a diagnostic test procedure by individuals who are trained in the performance and interpretation of evoked potentials such as audiologists and physicians. The results of the test will be used by trained hearing health care professionals to make recommendations regarding appropriate intervention strategies.

The provided text is a 510(k) summary for the Bio-logic MASTER Evoked Response System. It primarily focuses on demonstrating substantial equivalence to a predicate device and does not contain detailed information about specific acceptance criteria or a dedicated study proving performance against those criteria.

The document states that the modification was designed and incorporated "in accordance with the Bio-logic internal Product Development procedures which are intended to meet ISO-9001. EN-46001 and FDA QSR Design Control specifications." It also mentions a "Hazard/Risk analysis ... performed using the Fault Tree analysis (FTA) approach, and a detailed Risk Assessment was written in accordance with EN-1441." An addendum to this hazard/risk file was written for the new MASTER software.

Therefore, based on the provided text, a comprehensive table of acceptance criteria and reported device performance, as well as the detailed study information requested, cannot be fully generated as such a study is not explicitly described.

However, I can extract information related to the device's design control and risk assessment, which are usually components of meeting acceptance criteria for medical devices:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not provide a table with specific, quantifiable acceptance criteria (e.g., specific accuracy metrics, threshold determination accuracy) and corresponding reported performance metrics from a clinical study. Instead, it focuses on demonstrating that the new MASTER device has "no significant differences which would adversely affect product safety and effectiveness" compared to its predicate.

The closest to "acceptance criteria" are the statements regarding safety and effectiveness, and the comparison table highlighting similarities and differences with the predicate device.

2. Sample Size for Test Set and Data Provenance:

• The document does not specify a sample size for a test set or discuss any clinical data provenance (e.g., country of origin, retrospective/prospective study). The submission is primarily focused on software modification and substantial equivalence to a predicate device, relying on design controls and risk analysis rather than a new clinical performance study.

3. Number of Experts and Qualifications for Ground Truth (Test Set):

• This information is not provided in the document as there is no mention of a clinical test set requiring expert-established ground truth.

4. Adjudication Method (Test Set):

• This information is not provided as there is no mention of a clinical test set requiring adjudication.

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

• The document does not mention a Multi-Reader Multi-Case (MRMC) comparative effectiveness study. The focus is on the device's standalone capability for diagnostic testing by trained healthcare professionals.

6. Standalone Performance Study:

• No specific standalone performance study with detailed metrics is reported in this summary. The document states that the software was "originally designed for research purposes" and Bio-logic "made significant modifications... to improve overall reliability, performance and ease of use." The claim of performance is inferred from the device's design to estimate behavioral hearing thresholds reliably through ASSR, a variant of an existing modality. The safety and effectiveness are established through adherence to design control procedures, hazard/risk analysis, and comparison with the predicate device.

7. Type of Ground Truth Used (if standalone study was done):

• Since no specific standalone study is described, the type of ground truth is not explicitly stated. However, the product's function is to "estimate behavioral hearing threshold," implying that the ultimate ground truth for auditory devices would typically relate to actual behavioral hearing thresholds or objective physiological measures that correlate strongly with them.

8. Sample Size for the Training Set:

• The document does not provide information on a training set sample size. The software was "originally designed by and exclusively licensed from researchers at the Rotman Research Institute... at The University of Toronto" for "research purposes." This suggests it was developed based on existing research data, but the specific size or nature of this "training" data is not detailed as part of the submission.

9. How Ground Truth for Training Set was Established:

• This information is not provided. Given the software's origin in research for "estimating behavioral hearing threshold," the ground truth in the original research would likely have been established through a combination of psychoacoustic behavioral audiometry and physiological measurements (e.g., ABR) that the ASSR technique is designed to complement or predict. However, the document does not elaborate on this for the software's development.

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The Bio-logic Evoked Potential (EP) product family is indicated for use in the recording and analysis of human physiological data necessary for the diagnosis of auditory and hearing-related disorders. This product, the ABaer Cub, like it's predicate device, the ABaer, is especially indicated for use in the screening of infants to determine hearing loss. The Bio-logic EP System can be used for patients of all ages, from children to adults, including infants and geriatric patients. It is especially indicated for use in testing individuals for whom behavioral audiometric results are deemed unreliable, such as infants, young children, and cognitively impaired or uncooperative adults. The use of the Bio-logic EP family of products is to be performed under the prescription and supervision of a physician or other trained health care professional.

The Bio-logic Evoked Potential family of products is intended to be used for the recording and analysis of human physiological data for the purpose of neurological diagnosis and treatment of sensory disorders. The ABaer Predicate Device performs Evoked Potential screening, recording and analysis functions, provides one channel of data recording, and includes the Point Optimized Variance Ratio (POVR) algorithm for optimizing signal quality, implementing the screening function and enhancing speed of test completion. This new ABaer Cub device performs these same functions in essentially the same ways, but has hardware and software modifications and improvements over the Predicate device, primarily to enhance portability and ease of use. The ABaer Cub device incorporates the same POVR algorithm for the same purpose, to yield high-quality test results in the shortest possible time. The feature modifications for this new device include the use of a Personal Digital Assistant (PDA) or "Pocket PC" which can be hand-carried separately or mounted right on the ABaer box, resulting in a completely battery-powered, portable hand-held test instrument. The electronic hardware is very similar in design to the ABaer hardware used in the Predicate Device. The enclosure has been made slightly larger (deeper) to allow space to incorporate a rechargeable battery inside the unit. New circuitry for charging the battery has also been added to the unit, and the small LCD display in the ABaer has been removed from the ABaer Cub. The functions of the hardware are substantially the same as those of the Predicate Device hardware. The ABaer predicate device communicates test information and results to a separate host computer (desktop PC or laptop) through a serial communications port. In the ABaer Cub, this host computer is now a PDA or "pocket PC" (for instance, the Hewlett-Packard Jornada) which can be affixed right on the ABaer unit or hand-carried separately. The ABaer Cub software for control of this device is a simplified subset of the ABaer Predicate Device software, with some GUI changes necessary to enhance the graphics display for use with the smaller PDA LCD screen. The host software for the Predicate Device is Windows 95/98/ME based, whereas the host software for the ABaer Cub is Windows CE based. The C++ programming language is used in both cases. Together, these minor hardware and software changes implement the same functionality and perform the same intended use as the Predicate Device, but with improved portability and ease-of-use.

The provided text is a 510(k) Summary for the Bio-logic ABaer Cub device, which is a modification to an existing Evoked Potential product. The document focuses on demonstrating substantial equivalence to a predicate device and does not contain detailed information about specific acceptance criteria or the comprehensive study design typically found in a clinical performance study report.

Based on the provided text, here's what can be extracted and what information is not available:

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

This information is not explicitly stated in the provided 510(k) summary. The document describes the device modification and its functions but does not present specific acceptance criteria or quantitative performance metrics against those criteria. It emphasizes that the new device performs the "same functions in essentially the same ways" as the predicate device.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not available in the provided text. The document does not describe any specific test set or clinical study conducted with human subjects to evaluate the ABaer Cub's performance.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This information is not available. As there is no described test set or clinical study to establish ground truth, the number or qualifications of experts are not mentioned.

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

This information is not available. Without a described test set or clinical study, there is no mention of an adjudication method.

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

This information is not applicable/not available. The ABaer Cub is described as an "Evoked Response Auditory Stimulator" and "Evoked Potential system" that uses an algorithm (POVR) to optimize signal quality and screening function. It is not an AI-based diagnostic tool for which a MRMC study comparing human readers with and without AI assistance would typically be conducted. The "Pass/Refer recommendations" can be reviewed and overridden by a qualified health care professional, but this is not framed as an AI assistance scenario in the context of improving human reader performance.

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

The device incorporates the "Point Optimized Variance Ratio (POVR) algorithm for optimizing signal quality, implementing the screening function and enhancing speed of test completion." The document states that the ABaer Cub software "does not make any final decisions that result in any direct forms of diagnosis or treatment. The Pass/Refer recommendations of the automated screening process in the ABaer Cub can be reviewed...and may be modified, overridden or deleted as determined by the qualified user." This implies that while the algorithm provides automated recommendations, it is not purely standalone in terms of clinical decision-making. The document doesn't provide a specific study to evaluate the algorithm's standalone performance.

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

This information is not available. No specific ground truth methodology is described for evaluating the device's performance. The device is a modification of a predicate device, and the focus is on demonstrating that the modifications do not adversely affect safety and effectiveness, rather than establishing new performance benchmarks against a gold standard.

8. The sample size for the training set

This information is not available. Since the device is a modification of an existing product and the focus is on hardware and software changes for portability and ease of use, there is no mention of a training set for a new algorithm or model. The POVR algorithm is described as being incorporated from the predicate device.

9. How the ground truth for the training set was established

This information is not available. As there is no described training set, the method for establishing its ground truth is not mentioned.

Summary of available information regarding acceptance criteria and study proving device meets criteria:

The provided document is a 510(k) summary for a device modification, not a clinical study report. Its primary purpose is to demonstrate substantial equivalence to a predicate device. Therefore, it focuses on describing the device, its intended use, and how the modifications do not adversely affect safety and effectiveness compared to the predicate. It states:

• "This new ABaer Cub device performs these same functions in essentially the same ways, but has hardware and software modifications and improvements over the Predicate device, primarily to enhance portability and ease of use."
• The ABaer Cub incorporates "the same POVR algorithm for the same purpose, to yield high-quality test results in the shortest possible time."
• "Together, these minor hardware and software changes implement the same functionality and perform the same intended use as the Predicate Device, but with improved portability and ease-of-use."
• "The Bio-logic Evoked Potential family of products is intended to be used for the recording and analysis of human physiological data for the purpose of neurological diagnosis and treatment of sensory disorders."

The document relies on the established safety and effectiveness of the predicate device and asserts that the modifications do not introduce new safety or effectiveness concerns. The "study" proving the device meets criteria primarily consists of:

• Design and incorporation according to internal Product Development procedures meeting ISO-9001, EN-46001, and FDA QSR Design Control specifications.
• A detailed Hazard/Risk analysis using Fault Tree analysis (FTA) and a Risk Assessment in accordance with EN-1441, with an addendum for the ABaer Cub design.
• Comparison of technological characteristics of the ABaer Cub relative to the predicate ABaer device to "demonstrate that this new ABAER Cub device has no significant differences which would adversely affect product safety and effectiveness."

No specific clinical performance study with defined acceptance criteria, sample sizes, or ground truth methodologies is detailed in this 510(k) summary for the modified device.

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The Bio-logic Evoked Potential (EP) product family is indicated for use in the recording and analysis of human physiological data necessary for the diagnosis of auditory and hearing-related disorders. An auditory stimulus (click, tone, etc.) is presented to the patient's ear through an earphone or headphones, and the Brainstem Auditory Evoked Response from the patient is recorded using EEG electrodes placed on the scalp. Although this Brainstem Response is very low in amplitude (with respect to surrounding EEG "noise"), the stimulus-response cycle is repeated many times and the resulting responses are averaged from the time of the stimuli. The random noise averages to zero, but if the Brainstem Response signal will be easily determined in the averaged signal.

The Bio-logic EP System can be used for patients of all ages, from children infants and geriatric patients. It is especially indicated for use in testing individuals for whom behavioral are deemed unreliable, such as infants, young children, and cognitively impaired or uncooperative adults. The use of the Bio-logic EP family of products is to be performed under the prescription and supervision of a physician or other trained health care professional.

The feature modifications represented in this Special 510(k) are for the use of a redesigned hardware package and a Windowsbased software program to control the hardware. The functions and electronic design of the hardware are substantially the same as those of the Predicate Device hardware. The software for control of this device is a simplified subset of the DOS-based Predicate Device software. Together, they implement the same infant hearing screening functions and perform the same intended use as the Predicate Device, but with improved ease-of-use. The POVR algorithm described in the Predicate Device is implemented in the new Windows software to generally assist in test data interpretation, and specifically assist in the assessment of signal-to-noise ratio and the quality of the Brainstem Auditory Evoked Response in infants. Based on this automatic assessment, the speed of testing may be reduced and/or the quality of the data recording may be improved, without compromising the quality of recorded data or limiting the control and flexibility of the health care professional administering the test.

The Bio-logic Evoked Potential family of products is intended to be used for the recording and analysis of human physiological data for the purpose of neurological diagnosis and treatment of sensory disorders. The Predicate Device performs Evoked Potential recording and analysis functions, provides two channels of simultaneous data recording, and includes the option of applying the Point Optimized Variance Ratio (POVR) algorithm for optimizing signal quality and speed of test completion. This new device has both hardware and software modifications and improvements over the Predicate and related devices. The changes described in this 510(k) are to incorporate a repackaged variation of the previouslydescribed "E" Series hardware (2-channel), along with a new Windows-based software program for the control of this new hardware. This hardware performs the AEP test only, so, correspondingly, the software contains only AEP control and analysis features. The Navigator Pro hardware is very similar in electronics design to the Navigator E hardware used in the Predicate Device, except that the electronics hardware has been re-packaged into a stand-alone box which derives its power from a separate medical-grade power supply and connects to the host computer through a serial port. The host software for the Predicate Device is DOS-based, whereas the host software for the ABAER - Navigator Pro (subject of this Special 510(k)) is WINDOWS-based. The WINDOWS program has much of the same functionality as that of the predicate device, but with improved user interfaces and overall ease-of-use.

The provided text is a 510(k) summary for a medical device modification, specifically the Bio-logic ABAER / Navigator Pro. It primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study with specific acceptance criteria and performance data in the manner typically seen for novel or significantly modified devices involving AI/ML.

Therefore, much of the requested information regarding "acceptance criteria and reported device performance" from a formal study, sample sizes for test/training sets, expert ground truth establishment, adjudication methods, and MRMC comparatives is not present in this document. The document describes a comparison to a predicate device to establish substantial equivalence.

Here's an attempt to extract and interpret the available information according to your request, with significant caveats for the missing data:

Acceptance Criteria and Device Performance

This 510(k) focuses on demonstrating substantial equivalence to a predicate device (Bio-logic Evoked Potential for ABAER I, reference 510(k) #K992807). The "acceptance criteria" are therefore implicitly that the new device performs similarly to the predicate device in terms of safety and effectiveness, and that any differences do not adversely affect safety or effectiveness.

The document uses a comparative table to show that the new device has "no significant differences" in critical performance parameters.

1. Table of acceptance criteria and the reported device performance:

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

• Not explicitly stated. The document describes a design and development process for the modification and a comparison to the predicate device, but it does not provide details on a specific test set, its size, or its provenance for evaluating the quantitative performance metrics of the POVR algorithm or other features. The evaluation appears to be based on the functional equivalence and safety assessment during the design process, rather than a separate clinical performance study with a defined test set.

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

• Not applicable/Not stated. The document does not describe the establishment of ground truth by experts for a specific test set. The assessment relies on the judgment that the modified device's functionality is "substantially the same" as the predicate device.

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

• Not applicable/Not stated. No formal adjudication method for a test set is described.

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. This device is an Evoked Potential system, not an AI/ML diagnostic tool used by human readers for interpretation in the sense of an MRMC study. The POVR algorithm is described as optimizing signal quality and speed of test completion and assisting in test data interpretation, but not in a way that suggests a human reader's performance is being measured with and without its "assistance" in a clinical diagnostic decision-making context that typically warrants an MRMC study.

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

• Not applicable in the typical AI/ML sense. The device performs a signal acquisition and averaging task, and the POVR algorithm optimizes signal quality. The device is not making a "diagnosis" autonomously. It provides data for "review by the EP Technologist or Physician," who can "modify, override or delete" program "recommendations." The document states: "The ABAER / Navigator Pro software does not make any final decisions that result in any automatic forms of diagnosis or treatment."

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

• Not explicitly stated in the context of a performance study. The basis for "ground truth" (or more accurately, validation) appears to be alignment with the known performance and expected physiological responses obtained from the predicate device, and the established principles of Evoked Potential recording and analysis. For instance, the premise of the POVR algorithm is that it "monitors the signal-to-noise ratio," and the "random noise averages to zero, but if the Brainstem Response signal is present, it's signal will be easily determined." This reflects established biophysical principles rather than a specific expert-labeled dataset.

8. The sample size for the training set:

• Not applicable/Not stated. The document describes a device modification, not the development of a de novo AI/ML algorithm that undergoes a training phase with a specific dataset. The POVR algorithm itself was already part of the predicate device.

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

• Not applicable/Not stated. See point 8.

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The Bio-logic Evoked Potential (EP) product family is indicated for use in the recording and analysis of human physiological data necessary for the diagnosis of auditory and hearing-related disorders. An auditory stimulus (click, tone, etc.) is presented to the patient's ear through an earphone or headphoners, and the Brainstem Auditory Evoked Response from the patient is recorded using EEG electrodes placed on the scalp. Although this Brainstem Response is very low in amplitude (with respect to surrounding EEG "noise"), the stimulus-response cycle is repeated many times and the resulting responses are averaged from the time of the stimuli. The random noise averages to zero, but if the Brainstem Response signal is present, it's signal will be easily determined in the averaged signal.

The Bio-logic EP System can be used for patients of all ages, from children to adults, including infants and geriatric patients. It is especially indicated for use in testing individuals for whom behavioral audiometric results are deemed unreliable, such as infants, young children, and cognitively impaired or uncooperative adults. The use of the Bio-logic EP family of products is to be performed under the prescription and supervision of a physician or other trained health care professional.

The primary feature modification represented in this Special 510(k) is for the use of a new algorithm and protocol to generally assist in test data interpretation, and specifically assist in the assessment of signal-tonoise ratio and the quality of the Brainstem Auditory Evoked Response in infants. Based on this automatic assessment, the speed of testing may be reduced and/or the quality of the data recording may be improved. This new feature is used in conjunction with the current EP program, without compromising the quality of recorded data or limiting the control and flexibility of the health care professional administering the test.

The Bio-logic Evoked Potential family of products is intended to be used for the recording and analysis of human physiological data for the purpose of neurological diagnosis and treatment of sensory disorders. The predicate device referenced above is the latest in a series of this type marketed by Bio-logic. Other related devices comprising the Evoked Potential family include:

• 1. 510(k) #K803226 Bio-logic Evoked Response Stimulators.
• 2. 510(k) #K842543 Bio-logic Evoked Potential System.
• 3. 510(k) #K844992 Bio-logic Portable Evoked Response System.
• 4. 510(k) #K862690 Bio-logic Traveler LT System.

The predicate device performs Evoked Potential recording and analysis functions, providing up to 8 channels of simultaneous data recording. This device has both hardware and software modifications and unprovements over the related devices. Related Device #1 above is the first Evoked Potential device marketed by Bio-logic. It provides for up to 4 channels of data recording. Related Device #2 above is a hardware/software modification to the first device. Related Device #3 above is similar to #2, but utilizes a "portable" computer for ease of use and transportability. Device #4 utilizes hardware variations over devices #1, #2 and #3, primarily to enhance size-reduction and portability. It provides for a maximum of 2 channels of data recording. Trade names of "Traveler", "Express" and "LT" are associated with these transportable devices. Data recording hardware is available in three variations: the "E" Series, for up to 2 channels of data recording; the "SE" Series, for up to 4 channels of data recording; and the "Explorer" Series, for up to 8 channels of data recording. The Evoked Potential software is essentially the same for all of these products, with variations in models to accommodate differences in the hardware.

Evoked Potential systems can be used for three different kinds of tests: Auditory Evoked Potentials (AEP), Visual Evoked Potentials (VEP), and Somatosensory Evoked Potentials (SEP). These variations are called "modalities", and are offered as options in all three models of hardware marketed by Bio-logic. Each modality has its own unique hardware requirements. The modifications associated with this new modified device are to the software only, and do not change the hardware in any way. Also, the change only affects the operation of the Auditory Evoked Potential software functionality. There are no changes to any part of the VEP or SEP hardware or software.

The AEP test works on the basis of repeating a stimulus-response cycle. An auditory stimulation (click, tone, etc.) is presented to the patient through the use of an earphone or headphones. The EEG response from the brain is read through the use of scalp electrodes placed on the patient. The response time of interest is approximately from 1 - 20 milliseconds following the stimulus. The response voltage for this time period is amplified, digitized and stored in the AEP system computer's memory. The stimulation is then repeated, the EEG response is read again, and this cycle is repeated many times . Each time the response is read, it is averaged together with all previous responses. The final data record is the result of averaging several thousand (usually 2000-3000) responses. This averaging process is necessary because the EEG signal is very small, much lower in voltage than the surrounding EEG "noise" present in the recording. The noise is averaged out over the many readings, because the noise will have an average net value of zero. The result from the averaging process will be the signal.

Some of the EEG responses may have large amounts of noise or other artifact caused by random events such as patient movement or externally-generated electrical noise. These artifacts are usually characterized by very high amplitude voltages (relative to normal EEG levels). The EP program automatically monitors the response for abnormally-high voltage levels. When a response contains such artifacts, the response is discarded, not averaged, and not counted in the cycle count.

In preparation for running an AEP test, the user (EP Technologist, etc.) defines the test parameters through the use of a test protocol. In standard testing situations, most of these parameters will remain the same from test. One of the parameters is the number of stimulation cycles to be used. In order for the test to be completed as quickly as possible, it is desirable to use the smallest number of cycles. However, if the number of cycles is too small, the average will still contain large amounts of "hoise" and the quality of the data may be lowered. In general, the higher the number of cycles, the better will be the quality and reliability of the data. So, there is a trade-off between the time to perform the test and the quality of the test results.

Using the standard AEP program, the normal procedure would be to setup the number of stimulations for some nominal number at the lower end of the range, say 2000. The test would then be run to completion and the data manually reviewed by the user. If the quality of the data is considered to be too low, the test would be re-run with a higher number of stimulations. Another approach is for the user to set the number of stimulations to be a number on the high end of the range and continually monitor the accumulating average that is continuously displayed on the computer's monitor screen. Because the averaged data is updated to the screen every few seconds, it is possible to manually stop the test after the data looks "good enough" to the user. While this is admittedly a somewhat subjective measure not necessarily consistent from one user to the next, it is acceptable because of the training that a registered EP Technologist or Audiologist receives in the interpretation of such data records.

This Special 510(k) is for a modification to the standard Bio-logic AEP device, adding a software algorithm that automatically runs in the "background" while the AEP data recording is progressing. The purpose of this algorithm is to calculate a statistical value called "POVR", standing for "Point-Optimized Variance Ratio". For several (up to 10) strategically-selected data points at specific time latencies from the time of the stimulus, the algorithm makes a calculation intended to represent signal-to-noise ratio (S/N) at these points. This calculation is run on the accumulated data average every 256 stimulation-response cycles ("sweeps"). The result of the calculation is the POVR number, which is a statistical measure of the "power" level of the signal with respect to the noise. In normal testing, the POVR number will gradually increase as the number of sweeps increases and the resulting S/N ratio gets larger. When the POVR number reaches a specific threshold, the quality of the recording is considered to be high, and the test is automatically ended.

There are two additional conditions to the termination of the test recording:

• 1. The number of artifact sweeps must be lower than a pre-defined percentage of the sweeps, and
• 2. The number of sweeps must be greater than some pre-defined minimal number.

In addition, the maximum number of sweeps is set by the user in the AEP protocol, so that the test recording will also be ended when this maximum is reached. In this case, the POVR calculation will be below the stopping threshold, indicating that the quality of the data may still be too low. A second POVR number, less than the stopping POVR number, is used by the algorithm to make a pass/refer recommendation to the user. In any case, because the standard AEP capabilities still exist in the software, the user may evaluate the data recording and make the determination as to whether or not the recording is of acceptable quality, or if more testing is necessary.

This modification to the standard Bio-logic AEP program allows for a more objective and quantifiable measure of the data recording quality, while also achieving test completion more quickly in many cases. In those cases where the testing time is not reduced, but the POVR threshold is ultimately reached, the resulting data recording quality will likely be higher than if the same test had been performed manually. This is because the manual test is terminated when the number of sweeps reaches the pre-set number in the protocol, regardless of the quality of the result. The modified program with the POVR algorithm will continue the stimulus-response cycle until the POVR threshold is reached.

Below is a description of the acceptance criteria and the study to prove the device meets the acceptance criteria.

1. Table of Acceptance Criteria and Reported Device Performance:

The provided K99 summary does not explicitly define quantitative acceptance criteria for the new POVR algorithm. Instead, it describes qualitative benefits and functional improvements.

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

The document does not specify a separate "test set" in the context of a clinical trial or formal validation study with a defined sample size. The performance claims regarding reduced test time and improved quality are descriptive based on the algorithm's design and expected behavior, rather than formal statistical testing on a distinct dataset.

• Sample Size: Not specified.
• Data Provenance: Not specified. The document implies internal development and testing rather than external clinical data.

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

Given the lack of a formal test set described for a clinical study, there is no mention of experts establishing a "ground truth" for such a set in the traditional sense. The document refers to the role of trained professionals in evaluating data:

• Number of Experts: Not specified.
• Qualifications of Experts: "registered EP Technologist or Audiologist receives in the interpretation of such data records." and "All program 'recommendations' are subject to review by the EP Technologist or Physician."

4. Adjudication Method for the Test Set:

Not applicable, as a formal test set and a related adjudication process are not described in the document. The document highlights that human professionals retain ultimate oversight and decision-making authority: "All program 'recommendations' are subject to review by the EP Technologist or Physician, and may be modified, overridden or deleted as determined by a qualified user."

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

No mention of a multi-reader multi-case (MRMC) comparative effectiveness study. The document focuses on the automated nature of the POVR algorithm and its potential benefits (speed and objectivity) compared to purely manual termination of tests. It does not evaluate human reader performance with and without AI assistance.

6. Standalone Performance Study:

The document describes the POVR algorithm as running "in the background" and making calculations to determine when to automatically end the test. This suggests a standalone functional evaluation of the algorithm's performance in achieving its stated goals (e.g., reaching a statistical threshold correctly and terminating a recording). However, a formal "standalone study" with quantifiable metrics presented is not detailed. The description of its operation serves as the primary evidence of its standalone function.

7. Type of Ground Truth Used:

The ground truth for the device's function is the inherent signal-to-noise ratio within the recorded Auditory Evoked Potential (AEP) data. The POVR algorithm's calculation is intended to statistically represent this signal-to-noise ratio. The ultimate "ground truth" for a meaningful AEP recording is the presence of a discernible Brainstem Auditory Evoked Response, which is assessed by trained professionals. The algorithm aims to objectively quantify this.

• Type of Ground Truth: The intrinsic statistical properties of the AEP signal and noise, as interpreted and validated by expert judgment of AEP recordings.

8. Sample Size for the Training Set:

Not specified. The document does not discuss a "training set" in the context of machine learning, but rather describes the design and optimization of a statistical algorithm ("Point-Optimized Variance Ratio"). The optimization for infants is mentioned, suggesting specific parameter tuning, but not based on a quantified training dataset with ground truth labels.

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

Not applicable, as a classical machine learning "training set" with ground truth establishment is not discussed. The algorithm appears to be designed based on neurophysiological principles and statistical methods to quantify signal-to-noise ratio in AEPs, rather than being trained on a labeled dataset. The statement "The present POVR algorithm is optimized for infants" suggests internal parameter tuning based on understanding infant AEP characteristics, but the method for establishing "ground truth" during this optimization is not detailed.

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