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The Amplaid A724 and A728 are Programmable Admittance Meters which can:

1. Evaluate middle ear functions such as otitis media, glue ear, eardrum scar tissues, perform myringotomy status, ossicular chain discontinuity ear canal volume, otosclerosis, stapes fixation.
2. Perform Acoustic reflex test.
3. Determine acoustic reflex threshold
4. Perform reflex decay test.

They is intended for use by a qualified/trained audiologist on both adult and pediatric subjects for measurement of acoustic impedance.

The Amplaid A724 and A728 ADMITTANCE METERS perform plane and compensated tympanometry; Programmed and manual stimuli for ipsilateral and contralateral acoustic reflex; Automatic reflex threshold; and Decay measurements.

The given text describes the Amplaid A724 and A728 Clinical Automatic Programmable Admittance Meters, which are intended to evaluate middle ear functions and perform acoustic reflex tests. The submission claims substantial equivalence to the predicate device, Amplaid 770 Admittance Meter (K903066).

Here's the breakdown of the acceptance criteria and study information:

Acceptance Criteria and Reported Device Performance

The core of the "acceptance criteria" presented in this 510(k) summary is based on demonstrating substantial equivalence to a predicate device, the Amplaid 770 (K903066). The acceptance criteria are implicitly that the new device performs "as safe and effective as the predicate device" and has no new indications for use.

Study Information:

The provided document is a 510(k) Summary, which typically focuses on demonstrating substantial equivalence rather than presenting extensive clinical study data as would be found in a PMA.

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

   • The document states "results of bench and user testing." It does not provide specific details on the sample size of subjects or cases used for "user testing" or the data provenance (country of origin, retrospective/prospective).
   • Bench testing would involve testing the device's adherence to technical specifications and standards, not human subjects.

2. 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):

   • The document implies "user testing" was performed, but it does not specify the number or qualifications of "users" (audiologists) involved, nor how ground truth might have been established if clinical performance was assessed this way. Given the nature of a 510(k) for an impedance meter, the primary "ground truth" would be the accurate measurement of audiological parameters, likely validated against established calibration standards and potentially against a predicate device.

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

   • Not applicable/Not mentioned. The document does not describe adjudication for a test set in the context of diagnostic interpretation. The evaluation is likely focused on the device's ability to accurately perform its specified measurements.

4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • No MRMC comparative effectiveness study was done. This type of study is not relevant for an auditory impedance meter, which is a measurement device, not an AI-assisted diagnostic interpretation tool.

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

   • The device described is an "Amplaid A724 and A728 Clinical Automatic Programmable Admittance Meters." It is a measurement device operated by a "qualified/trained audiologist." Therefore, it inherently involves a human-in-the-loop for operation and interpretation. The performance evaluation would be of the device itself and its interaction with the user, not a standalone AI algorithm.

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

   • For this device, the "ground truth" for demonstrating safety and effectiveness would primarily be:
     • Adherence to recognized industry standards: ANSI, ISO, IEC, EN standards for audiometric and electrical safety.
     • Comparison to the predicate device: The new device must perform "as safe and effective as the predicate device," implying performance metrics that align with or are better than the predicate's established performance. This suggests comparative testing against the predicate to ensure equivalent measurement accuracy and functionality.
     • Bench testing: Verifying technical specifications of the device itself.

7. The sample size for the training set:

   • Not applicable/Not mentioned. This device is not an AI/ML product that undergoes a "training phase." Its functionality is based on established audiological measurement principles and hardware/software design.

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

   • Not applicable. As noted above, there is no "training set" in the context of an AI/ML algorithm.

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The Amplaid Models A315 and A319 are two channel clinical diagnostic audiometers which can perform all audiometric tests normally performed in a clinical situation. It is intended for use by a qualified/trained audiologist on both adult and pediatric subjects for measurement and diagnosis of various types of hearing losses.

The Amplaid A315 and A319 are two channel clinical diagnostic audiometers which can perform all audiometric tests normally performed in a clinical situation. They provide testing capability for basic evaluation, cochlear versus retrocochlear dysfunction, central dysfunction and non-organic hearing loss. Other diagnostic audiometric tests are: pure tone, Speech, High Frequency, Multifrequency, Bekesy, S.I.S.I., A.B.L.B. (Fowler), D.L.I. (Lüscher), M.L.B., Tone Decay, and M.L.D.(Masking Level Difference).

This document describes the Amplaid A315 and A319 Series clinical diagnostic audiometers and their substantial equivalence to a predicate device, the Amplaid 460 (K971747). The submission focuses on direct comparison to the predicate device rather than presenting a study with specific acceptance criteria and performance metrics for the new device as a standalone entity.

Here's a breakdown of the requested information based on the provided text:

1. Table of acceptance criteria and reported device performance:

The document does not explicitly state specific acceptance criteria in terms of numerical performance metrics (e.g., sensitivity, specificity, accuracy) for the new device. Instead, the acceptance criterion is implied to be "substantial equivalence" to the predicate device in terms of safety and effectiveness.

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

The document mentions "bench and user testing data" but does not specify the sample size for any test set or the data provenance (e.g., country of origin, retrospective/prospective).

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

The document does not mention the use of experts to establish ground truth for a test set. The evaluation was a comparison to a predicate device.

4. Adjudication method for the test set:

The document does not describe an adjudication method for a test set.

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, an MRMC comparative effectiveness study was not done. This device is an audiometer, not an AI-assisted diagnostic tool. Therefore, the concept of "human readers improve with AI vs without AI" is not applicable.

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

No, a standalone (algorithm only) performance study was not done. This describes a medical device, an audiometer, which is operated by a human audiologist. The device itself is not an algorithm that performs diagnosis independently.

7. The type of ground truth used:

The "ground truth" in this context is the performance and safety established by the predicate device, Amplaid 460 (K971747). The new devices are compared against this established benchmark. There is no mention of pathology, outcomes data, or expert consensus being used as ground truth for a novel diagnostic scenario.

8. The sample size for the training set:

Not applicable. This submission describes a hardware medical device (audiometer) and its substantial equivalence to a predicate, not a machine learning model that requires a training set.

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

Not applicable. As above, there is no training set for this type of device submission.

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The Amplaid A311 Series is a two channel clinical diagnostic audiometer which can perform all audiometric tests normally performed in a clinical situation. It is intended for use by a qualified/trained audiologist on both adult and pediatric subjects for measurement and diagnosis of various types of hearing losses.

The Amplaid A311 Series is a two channel clinical diagnostic audiometer which can perform all audiometric tests normally performed in a clinical situation. It provides testing capability for basic evaluation, cochlear versus retrocochlear dysfunction, central dysfunction and non-organic hearing loss. Other diagnostic audiometric tests are: pure tone, speech, Multifrequency, S.I.S.I., A.B.L.B. (Fowler), D.L.I. (Lüscher), M.L.B., and Tone Decay. The A311 Series comes in two models, both using the same internal circuit board: The AM11 which uses a personal computer as the user interface (communicates via RS232), and the A311, with uses a dedicated front panel keyboard with an LCD display.

The provided document [0-3] does not contain specific acceptance criteria or a detailed study proving the device meets said criteria in the way typically expected for a medical device efficacy study (e.g., performance metrics like sensitivity, specificity, accuracy against a gold standard).

Instead, this document is a 510(k) summary for the Amplaid A311 Series audiometer seeking substantial equivalence to predicate devices already on the market. The "acceptance criteria" here are primarily based on demonstrating that the new device performs "as safe and effective as the predicate devices" and conforms to relevant medical device standards.

Here's an analysis based on the information provided:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implied by the comparison to predicate devices and adherence to relevant standards. The "reported device performance" is essentially that it meets these standards and functions similarly to the predicate.

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

The document states: "The results of bench and user testing indicates that the new device is as safe and effective as the predicate devices." [0] and "After analyzing both bench and user testing data, it is the conclusion of Amplifon S.p.A. that the 'Amplaid A311 Series™' is as safe and effective as the predicate device..." [1] However, the specific sample sizes, the nature of the "test set" (e.g., number of subjects, type of data collected, number of test runs), or the data provenance (country, retrospective/prospective) are not disclosed in this 510(k) summary. It implies testing was done, but details are absent.

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

This type of information is not provided in the document. For a 510(k) submission focused on substantial equivalence, the "ground truth" for the device's performance is often established by comparing its output to that of the predicate device, or by confirming its adherence to objective performance standards (e.g., accuracy of dB levels, frequency output). Expert consensus for "ground truth" in terms of clinical diagnosis or outcomes is not explicitly mentioned as a component of this submission type for an audiometer.

4. Adjudication Method for the Test Set

This information is not provided. Given the nature of an audiometer, "adjudication" methods like 2+1 or 3+1 consensus, typically used for image or diagnostic interpretation, are not directly applicable. The "user testing" mentioned might involve comparing measurements from the new device against the predicate device or a calibrated standard.

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

No, an MRMC comparative effectiveness study is not mentioned in the document. This type of study is more relevant for diagnostic devices where human readers interpret outputs (e.g., radiologists reading images) and the AI aims to assist or replace that interpretation. An audiometer directly measures hearing thresholds, and its effectiveness is determined by its measurement accuracy and reproducibility, not by how it improves human reader performance in interpreting its output.

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

The device itself is a standalone clinical diagnostic audiometer. Its primary function is to generate tones and measure responses, guided by a qualified/trained audiologist. The concept of "algorithm only without human-in-the-loop performance" in the context of an audiometer would likely refer to its ability to generate accurate and consistent sounds and register patient responses correctly, independent of operator skill (though an audiologist uses the device). The document broadly implies standalone performance was assessed through "bench and user testing" to confirm it meets audiometric standards, but it doesn't separate an "algorithm-only" performance from the device's operation by a user.

7. The Type of Ground Truth Used

The "ground truth" for an audiometer's performance typically refers to:

• Measurement Accuracy against Calibrated Standards: The device's ability to output precise frequencies and decibel levels, and to accurately record patient responses, as calibrated against known, accepted reference standards (e.g., conforming to ISO and ANSI audiological standards).
• Comparison to a Predicate Device: Demonstrating that the new device produces equivalent results to an already legally marketed and accepted predicate audiometer.

The document emphasizes adherence to:

• Audiometric Standards: ISO 389-1989, ANSI S3.6-1989, IEC 60645.
• Electrical Safety Standards: UL 2601, IEC 60601-1.

This suggests the ground truth was established by verifying the device's technical specifications and performance against these published standards and against the established performance of the predicate device.

8. The Sample Size for the Training Set

This information is not applicable/provided. Audiometers are not typically "trained" in the way AI algorithms are. Their function is based on established physics and electronics to generate and measure sound. Therefore, there is no "training set" in the context of machine learning.

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

This information is not applicable/provided for the reasons stated above.

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The Amplaid MK12 is a multi-channel system for electrodiagnosis capable of performing multisensory evoked potential tests including:

• Electronystagmography
• Visual evoked potentials,
• Auditory evoked potentials, and
• Electrical (somatosensory) evoked potentials.

The Amplaid MK12 Multi-channel system for electrodiagnosis consists of a two or four channel signal acquisition system coupled to a microcomputer which can perform signal averaging, storage and display, along with microcomputer controlled multiple mode evoked potential stimulators: auditory, visual, and electrical. A thermal printer is built in, and laser printer connection is supported.

The provided text describes the Amplaid MK12, an evoked potential electrodiagnostic system, and its substantial equivalence to a predicate device, the Amplaid MK15. However, the document does not contain details about specific acceptance criteria, a dedicated study proving device performance against those criteria, or the methodology typically used for such studies in the context of AI/ML or a new, novel medical device.

The submission is a 510(k) for a device that is stated to be "similar in design and function" to a previously cleared device (K861014). The primary focus of the 510(k) summary is to demonstrate substantial equivalence, rather than to present a de novo performance study against explicit acceptance criteria.

Therefore, many sections of your request cannot be fulfilled by the provided text.

Here is an attempt to address your request based on the available information:

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

The document does not explicitly state quantitative acceptance criteria for performance metrics (e.g., sensitivity, specificity, accuracy). Instead, it relies on demonstrating that the new device is "as safe and effective as the predicate device" through a comparison of characteristics.

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

The document mentions "bench and user testing" but does not provide details on:

• The specific sample size (number of cases, subjects, or data points) used for this testing.
• The data provenance (e.g., country of origin, retrospective or prospective nature).

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

This information is not provided in the document. Given that the testing mainly aimed to establish substantial equivalence based on safety and effectiveness comparable to a predicate, it's unlikely a formal "ground truth" establishment by multiple experts, as understood in an AI/ML context, was performed or detailed.

4. Adjudication method for the test set

This information is not provided in the document.

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

An MRMC study is not mentioned. The device is an evoked potential electrodiagnostic system and does not appear to be an AI-assisted diagnostic tool for human readers in the way an AI-powered image analysis system would be.

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

This concept is not applicable to the device described. The Amplaid MK12 is a multi-channel system for electrodiagnosis, implying human operation and interpretation of the evoked potentials. It's not a standalone algorithm in the sense of AI/ML.

7. The type of ground truth used

The document does not specify the type of ground truth used. For an evoked potential system, "ground truth" would generally relate to the accuracy, reliability, and precision of the physiological signal acquisition and processing compared to established medical benchmarks or the performance of the predicate device.

8. The sample size for the training set

The concept of a "training set" in the context of machine learning is not applicable here, as the device is not described as using AI/ML algorithms that require training data.

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

Not applicable for the same reason as point 8.

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The Amplaid AM50 is a Programmable Admittance Meter which can:

• Evaluate middle ear functions such as otitis media, glue ear, eardrum scar tissues, . perform myringotomy status, ossicular chain discontinuity ear canal volume, otosclerosis, stapes fixation.
• Perform Acoustic reflex test. ●
• Determine acoustic reflex threshold .
• . Perform reflex decay test.

It is intended for use by a qualified/trained audiologist on both adult and pediatric subjects for measurement and diagnosis of various types of hearing losses.

The Amplaid AM50 ADMITTANCE METER performs plan and compensated tympanometry; Programmed and manual stimuli for ipsilateral and contralateral acoustic reflex; Automatic reflex threshold; and Decay measurements.

The provided documentation describes the Amplaid AM50 Clinical Automatic Programmable Admittance Meter and its substantial equivalence to a predicate device, the Amplaid 770 Admittance Meter, rather than outlining specific acceptance criteria or an in-depth study proving its performance against such criteria.

The submission is a 510(k) Summary of Safety and Effectiveness, which typically focuses on demonstrating that a new device is "substantially equivalent" to a legally marketed predicate device. This process often relies on comparisons of intended use, technological characteristics, and performance data to show that the new device is as safe and effective. It explicitly states, "The results of bench and user testing indicates that the new device is as safe and effective as the predicate device." and "After analyzing both bench and user testing data, it is the conclusion of Amplifon S.p.A. that the Amplaid AM50 is as safe and effective as the predicate device, has few technological differences, and has no new indications for use, thus rendering it substantially equivalent to the predicate Device."

Given this, I cannot provide a table of acceptance criteria and reported device performance in the typical format of a clinical trial or performance study, because the document does not present such criteria or detailed results. Instead, the "acceptance criteria" are implicitly met by demonstrating substantial equivalence to the predicate device, which itself would have undergone performance validation.

However, I can extract the information that is present and frame it in response to your request as best as possible given the limitations of the provided text.

1. Table of Acceptance Criteria and the Reported Device Performance

As specific, quantitative acceptance criteria are not explicitly defined in the provided 510(k) summary, the "acceptance" is understood to be the demonstration of substantial equivalence to the predicate device, the Amplaid 770. The "performance" is implicitly deemed equivalent to the predicate.

• Evaluate middle ear functions such as otitis media, glue ear, eardrum scar tissues, perform myringotomy status, ossicular chain discontinuity ear canal volume, otosclerosis, stapes fixation.
• Perform Acoustic reflex test.
• Determine acoustic reflex threshold.
• Perform reflex decay test."
  (Stated as "Same" as predicate in the comparison chart, implying equivalent performance for these functions). |
  | Technical Characteristics: Device must perform plain and compensated tympanometry; Programmed and manual stimuli for ipsilateral and contralateral acoustic reflex; Automatic reflex threshold; and Decay measurements. | Amplaid AM50 Performance: "The Amplaid AM50 ADMITTANCE METER performs plan and compensated tympanometry; Programmed and manual stimuli for ipsilateral and contralateral acoustic reflex; Automatic reflex threshold; and Decay measurements."
  (Stated as "Same" as predicate in the comparison chart, implying equivalent performance for these functions). |
  | Safety and Effectiveness: Device must be as safe and effective as the predicate device (Amplaid 770). | Amplaid AM50 Performance: "The results of bench and user testing indicates that the new device is as safe and effective as the predicate device. The same circuit technology is used in both devices."
  "After analyzing both bench and user testing data, it is the conclusion of Amplifon S.p.A. that the Amplaid AM50 is as safe and effective as the predicate device..." |
  | Standards Compliance: Compliance with relevant audiometric and electrical safety standards (e.g., ANSI 1969, ISO 1975, IEC 61027, UL-544, IEC 601). | Amplaid AM50 Performance: "Audiometric: (Same) [as predicate, which is] ANSI 1969, ISO 1975 for contralateral, 2 cm³ cavity for ipsilateral, IEC 61027"
  "Electrical safety: (Same) [as predicate, which is] UL-544, IEC 601" |
  | Technological Differences: Differences should not raise new questions of safety or effectiveness. | Amplaid AM50 Performance: The only changes noted are "packaging and control software," where "all keyboard, display, and control functions have been moved to the attached (via RS232) personal computer."
  "few technological differences, and has no new indications for use." |

The "study" that proves the device meets (or rather, is substantially equivalent to) these criteria is referred to as "bench and user testing." No specific details on the methodology, sample sizes, or results of these tests are provided in this summary.

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

• Sample Size for Test Set: Not specified. The document only mentions "bench and user testing."
• Data Provenance: Not specified. The manufacturer is Amplifon S.p.A. in Milan, ITALY. It is plausible the "bench and user testing" was conducted in Italy or a region accessible to the manufacturer, but this is not confirmed. The data appears to be retrospective in the sense that it supports a regulatory submission rather than a prospective clinical trial for public dissemination.

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

• This information is not provided. The "user testing" would likely involve qualified audiologists as the device is intended for use by a "qualified/trained audiologist," but the number and specific qualifications are not detailed.

4. Adjudication method for the test set

• Not specified.

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 device is not an AI-powered diagnostic tool, but rather an acoustic admittance meter. Therefore, an MRMC comparative effectiveness study involving "AI vs without AI assistance" is not applicable and was not performed.

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

• This device is a medical instrument and requires human operation ("intended for use by a qualified/trained audiologist"). Therefore, a standalone (algorithm only) performance study is not applicable and was not performed. The performance evaluated was of the device in a user-testing context.

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

• The concept of "ground truth" as typically applied to diagnostic AI models is not directly applicable here. For an admittance meter, "ground truth" would likely refer to the accuracy and reliability of its physical measurements against known standards or against the established performance of the predicate device. This would involve calibrated equipment and possibly clinical comparisons, but the specifics are not detailed.

8. The sample size for the training set

• This device does not utilize a "training set" in the context of machine learning or AI. Its functionality is based on established physical principles and circuit technology, not on learned patterns from a dataset.

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

• As there is no training set for this type of device, this question is not applicable.

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The Amplaid MK22 is a multi-channel system for electrodiagnosis capable of performing multisensory evoked potential tests including:
Electronystagmography
Visual evoked potentials,
Auditory evoked potentials, and
Electrical (somatosensory) evoked potentials.

The Amplaid MK22 Multi-channel system for electrodiagnosis consists of a two channel signal acquisition system coupled to a microcomputer which can perform signal averaging, storage and display, along with microcomputer controlled multiple mode evoked potential stimulators: auditory, visual, and electrical. A thermal printer is built in, and laser printer connection is supported.

The Amplaid MK22 is an evoked potential electrodiagnostic system. The submission establishes substantial equivalence to the Amplaid MK15 (K861014).

1. Table of Acceptance Criteria and Reported Device Performance

For this 510(k) submission, the acceptance criteria are based on substantial equivalence to the predicate device, Amplaid MK15. This means the new device must be as safe and effective as the predicate device and have the same intended uses, with no new indications for use. Performance is implicitly assessed by demonstrating that the key characteristics of the new device are either identical or comparable to the predicate device and that any differences do not raise new questions of safety or effectiveness.

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

The document does not explicitly mention a "test set" in the context of a clinical performance study with human subjects or a defined set of data for algorithm evaluation. The assessment for this 510(k) is based on bench and user testing and a comparative analysis of specifications against the predicate device.

• Sample Size: Not applicable in the context of a traditional performance study. The evaluation focuses on the device hardware and software specifications, and its equivalence to a previously cleared device.
• Data Provenance: Not specified as there isn't a clinical data set being referenced for performance evaluation. The "bench and user testing" information is general and does not refer to specific patient data.

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

Not applicable. This 510(k) submission is for an electrodiagnostic system, and its clearance is based on substantial equivalence to a predicate device, not on diagnostic accuracy against a ground truth established by experts.

4. Adjudication Method for the Test Set

Not applicable. There is no specific "test set" and corresponding adjudication process described for evaluating device performance in this submission.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size

No. An MRMC comparative effectiveness study was not performed or referenced in this 510(k) submission. The device is an electrodiagnostic system and the clearance pathway relies on demonstrating equivalent technical specifications and intended uses to a predicate device, not on improving human reader performance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

Not applicable. The Amplaid MK22 is a medical device (an electrodiagnostic system) that acquires and processes physiological signals for medical diagnosis by a clinician. It is not an AI algorithm that produces a diagnostic output on its own. While it involves signal averaging, storage, and display, this is part of standard electrodiagnostic equipment functionality, not an AI algorithm performing diagnostic interpretation without human input.

7. The Type of Ground Truth Used

Not applicable. The submission does not refer to a ground truth for diagnostic accuracy, as it focuses on demonstrating the device's technical specifications and intended uses are substantially equivalent to a predicate.

8. The Sample Size for the Training Set

Not applicable. The Amplaid MK22 is a hardware and software system for electrodiagnosis; it is not an AI algorithm that undergoes a "training" phase with a dataset.

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

Not applicable, as there is no "training set" for this device.

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The Amplaid 171S is a clinical diagnostic audiometer which can perform all audiometric tests normally performed in a clinical situation. It is intended for use by a qualified/trained audio!ogist on both adult and pediatric subjects for measurement and diagnosis of various types of hearing losses.

The Amplaid 171S is a one channel clinical diagnostic audiometer which can perform all audiometric tests normally performed in a clinical situation. It provides testing capability for basic evaluation, cochlear versus retrocochlear dysfunction, central dysfunction and non-organic hearing loss. Other diagnostic audiometric tests are: pure tone, and speech.

Here's a breakdown of the acceptance criteria and study information for the Amplaid 171S Clinical Audiometer, based on the provided text:

Acceptance Criteria and Device Performance

The acceptance criteria for the Amplaid 171S are primarily based on its equivalence to a predicate device, the Amplaid 308 Clinical Audiometer. The study demonstrated that the new device is "as safe and effective as the predicate device," and the acceptance criteria are met by showing comparable performance, function, and adherence to relevant standards.

Table of Acceptance Criteria and Reported Device Performance:

Study Information

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

   • The document states that "bench and user testing" were performed. However, it does not provide a specific sample size for the test set (number of subjects or assessments).
   • The data provenance (country of origin, retrospective/prospective) is not specified.

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

   • The document mentions "user testing," which implies involvement of qualified users (audiologists, as per indications for use).
   • However, it does not specify the number of experts or their qualifications regarding ground truth establishment for the test set.

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

   • The document does not describe an adjudication method for the test set results.

4. 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, an MRMC comparative effectiveness study was not done. This report is for a medical device (audiometer), not an AI-assisted diagnostic tool.

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

   • No, this is not applicable. The device is a clinical diagnostic audiometer, a human-operated instrument, not an algorithm. Performance is inherently "with human-in-the-loop" (the audiologist).

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

   • Based on "bench and user testing," the ground truth for performance comparison likely involved measurements against established audiometric standards and potentially clinical assessments by audiologists comparing the output/functionality to expected clinical results for diagnosing hearing loss. The document does not explicitly state "expert consensus," but "user testing" implies clinical validation.

7. The sample size for the training set:

   • Not applicable. This device is a hardware instrument, not a machine learning model, so there is no "training set."

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

   • Not applicable. No training set for an algorithm.

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The Amplaid 460 is a two channel clinical diagnostic audiometer which can perform all audiometric tests normally performed in a clinical situation. It is intended for use by a qualified/trained audiologist on both adult and pediatric subjects for measurement and diagnosis of various types of hearing losses.

The Amplaid 460 is a two channel clinical diagnostic audiometer which can perform all audiometric tests normally performed in a clinical situation. It provides testing capability for basic evaluation, cochlear versus retrocochlear dysfunction, central dysfunction and non-organic hearing loss. Other diagnostic audiometric tests are: pure tone, Speech, High Frequency, Multifrequency, Bekesy, S.I.S.I., A.B.L.B. (Fowler), D.L.I. (Lüscher), M.L.B., Tone Decay, and M.L.D.(Masking Level Difference).

The provided text describes the 510(k) submission for the Amplaid 460 Research and Clinical Audiometer. However, it does not contain detailed information about specific acceptance criteria or the study that definitively proves the device meets those criteria. The document is a regulatory submission for substantial equivalence to a predicate device, rather than a detailed scientific study report.

Here's an analysis based on the provided text and what is typically found (or not found) in such 510(k) summaries:

1. A table of acceptance criteria and the reported device performance:
   The document states: "The results of bench and user testing indicates that the new device is as safe and effective as the predicate devices." No specific acceptance criteria (e.g., accuracy, precision, sensitivity, specificity, or specific tolerances for audiometric measurements) are listed, nor are detailed performance metrics reported. The statement refers to a general equivalence to predicate devices, but without quantification.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):
   No information on sample size, data provenance, or study design (retrospective/prospective) is provided for the "bench and user testing."

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 in the provided text. The document mentions the intended use by a "qualified/trained audiologist," but does not specify their role in testing or establishing ground truth for the device's performance.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
   No information about adjudication methods is provided.

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 device is an audiometer, a diagnostic instrument that measures hearing thresholds. It is not an AI-assisted diagnostic tool that would typically involve human readers interpreting results in a MRMC study. Therefore, an MRMC study with AI assistance is not applicable here, and no such study is mentioned.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
   The device is a standalone diagnostic instrument. Its performance would inherently be evaluated without a human-in-the-loop performance study in the context of interpretation, as it generates raw audiometric data. The "user testing" mentioned likely refers to user interaction and functionality, not diagnostic interpretation.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
   Not explicitly stated. For an audiometer, the "ground truth" would typically refer to the instrument's ability to accurately measure sound levels and hearing thresholds against a known standard, often calibrated using established methods. The "bench testing" would likely cover this. For "user testing," the ground truth might be the expected audiogram from a patient with a known hearing status, but this is speculative given the lack of detail.

8. The sample size for the training set:
   This device is not described as utilizing a machine learning algorithm that requires a "training set" in the conventional sense. It's a measurement instrument.

9. How the ground truth for the training set was established:
   As above, the concept of a "training set" and ground truth for it, as typically applied to machine learning, is not relevant to this type of device based on the provided information.

Summary of what is present:

• Predicate Device: Amplaid 309 Clinical Audiometer (K880059)
• Safety and Effectiveness Claim: "The results of bench and user testing indicates that the new device is as safe and effective as the predicate devices." This is a qualitative claim of equivalence, not a detailed report of adherence to specific, quantified acceptance criteria.
• Intended Use: Diagnosis of hearing losses by qualified audiologists on both adult and pediatric subjects.

In conclusion, the provided text from the 510(k) summary focuses on demonstrating substantial equivalence to a predicate device based on design, function, and general safety/effectiveness, rather than detailing a rigorous study with specific acceptance criteria and performance data in the manner typically expected for advanced diagnostic algorithms or AI-driven systems. For a device like an audiometer, "bench testing" would likely involve calibration against known sound pressure levels and electrical signals, and "user testing" would confirm usability and correct functionality in clinical scenarios, but the details are not provided here.

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