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The Multiflex Tinnitus Technology is a tool to generate sounds to be used in a Tinnitus Management Program to relieve patients suffering from tinnitus. The target population is primarily the adult population over 18 years of age.

The Multiflex Tinnitus Technology is targeted for healthcare professionals, which are treating patients suffering from tinnitus, as well as conventional hearing disorders. The fitting of the Multiflex Tinnitus Technology must be done by a hearing professional participating in a Tinnitus Management Program.

Multiflex Tinnitus TechnologyTM (Tinnitus Multiflex) is designed to generate noise that can optionally periodically fluctuate in amplitude and frequency to provide relief for patients suffering from tinnitus.

Tinnitus Multiflex is a firmware program code (algorithm) that is embedded as part of the integrated circuit (IC) in the Digital Signal Processing (DSP) stage of a hearing-aid. More specifically, Tinnitus Multiflex is an added branch of code that is separate from the normal existing hearing-aid firmware. As such, hearing-aid operating characteristics (besides tinnitus-stimulus functionalities) are not impacted by the Tinnitus Multiflex branch of code. Tinnitus Multiflex may be deployed across all Starkey hearing-aid models.

Tinnitus Multiflex functionalities and parameters are enabled and adjusted by a hearing-care professional utilizing the Starkey proprietary hearing-aid programming software, Inspire. The Tinnitus Multiflex can be manually adjusted to a patient's stimulus needs or automatically adjusted via the new audiogram shaping functionality.

The provided text describes a 510(k) premarket notification for a Tinnitus Masker device (Multiflex Tinnitus Technology) and does not contain detailed information about a clinical study involving experts, test sets, or ground truth establishment in the context of typical AI/ML device evaluations. The submission primarily focuses on demonstrating substantial equivalence to a predicate device (K122876) based on technological characteristics and performance specifications for non-clinical testing.

Therefore, many of the requested items (2, 3, 4, 5, 6, 7, 8, 9) cannot be answered directly from the provided text as they pertain to clinical evaluations that were explicitly stated as not being performed for this submission.

Here is the information that can be extracted from the document:

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

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
Not applicable. No clinical test set data was reported. The device is a "firmware program code (algorithm)" embedded in a hearing aid, and the testing described is non-clinical (risk analysis, verification, and validation testing for the audiogram-shaping functionality).

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)
Not applicable. No clinical expert review for ground truth was reported.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. No clinical adjudication method was reported.

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
Not applicable. No MRMC study was reported. The device is a "Tinnitus Masker" technology, not an AI assistance tool for human readers.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
Not applicable in the context of typical AI/ML algorithm-only performance studies. The Multiflex Tinnitus Technology is described as an algorithm embedded in a hearing aid, but its "performance" is primarily related to its ability to generate specific sound characteristics and adjust based on audiograms, rather than an AI-driven diagnostic or interpretative function. The evaluation focuses on meeting predefined acoustic output limits and maintaining safety and effectiveness.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
Not applicable. For the non-clinical testing performed, the "ground truth" consisted of predetermined acoustic specifications and safety/effectiveness criteria for the device's functionality.

8. The sample size for the training set
Not applicable. This document is a 510(k) submission for a non-AI/ML device (firmware for a tinnitus masker) and does not describe a machine learning training process or training set.

9. How the ground truth for the training set was established
Not applicable, as there was no reported machine learning training set.

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The Multiflex Tinnitus Technology™ is a tool to generate sounds to be used in a Tinnitus Management Program to relieve patients suffering from tinnitus. The target population is primarily the adult population over 18 years of age.

The Multiflex Tinnitus Technology™ is targeted for healthcare professionals, which are treating patients suffering from tinnitus, as well as conventional hearing disorders. The ncating patients barrering from themnology™ must be done by a hearing professional participating in a Tinnitus Management Program.

The Starkey Multiflex Tinnitus Technology™ provides the hearing care professional with an option to treat those patients suffering from tinnitus. It is a firmware functionality option embedded in the signal processing stage of a digital hearing aid. The Multiflex Tinnitus Technology™ firmware generates broadband white noise that periodically fluctuates in amplitude and frequency to provide relief for those suffering from timitus.

The Multiflex Tinnitus Technology™ functionalities and parameters are enabled and adjusted by a hearing care professional to meet the individual needs of the patient.

The provided text does not contain detailed information about specific acceptance criteria, study methodologies, or performance results for the Starkey Laboratories Multiflex Tinnitus Technology. The document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than providing a standalone performance study with detailed acceptance criteria and results.

Here's a breakdown of what can be extracted and what is missing:

The submission states:
"Starkey Laboratories has conducted a risk analysis and performed the necessary verification and validation activities to demonstrate that the design outputs meet the design inputs. Results from this testing provide assurance that the proposed device has been designed and tested to assure conformance to the requirements for its intended use."

However, no specific acceptance criteria or quantitative performance data from these verification and validation activities are provided in the extracted text. Therefore, a table of acceptance criteria and reported device performance cannot be generated from the given input.

Regarding the other requested information:

1. A table of acceptance criteria and the reported device performance: Not available in the provided text. The document only generally states that testing was performed and confirmed the device meets design inputs for its intended use.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): Not available in the provided text. The 510(k) summary doesn't disclose details about sample sizes or data provenance for any 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): Not applicable/available. This type of information is typically relevant for studies involving human interpretation (e.g., image analysis, diagnoses). Since the device is a tinnitus masker generating sound, the "ground truth" would likely relate to objective sound characteristics or subjective patient feedback, though no details are provided.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable/available. See point 3.

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: Not applicable. This device is a sound generator for tinnitus, not an AI-assisted diagnostic tool that would involve human readers.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: The device itself is a "firmware functionality option embedded in the signal processing stage of a digital hearing aid" that "generates broadband white noise." Its performance as a standalone algorithm would likely involve objective acoustic measurements (e.g., frequency response, amplitude stability, output levels) and potentially subjective patient feedback studies. However, no specific details of such standalone performance studies are provided.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not available. For a tinnitus masker, ground truth could involve objective acoustic properties of the generated sound, or validated patient-reported outcome measures for tinnitus relief. The document generically mentions "verification and validation activities" but doesn't specify the ground truth used.

8. The sample size for the training set: Not applicable/available. This sounds like an AI/machine learning term. While the device has "firmware functionality," the description doesn't suggest it's a machine learning algorithm that requires a "training set" in the typical sense. It seems to be a more deterministic signal generation process.

9. How the ground truth for the training set was established: Not applicable/available. See point 8.

In summary: The provided 510(k) summary focuses on demonstrating substantial equivalence to a predicate device based on similar intended use and technological characteristics, as well as general statements about risk analysis and verification/validation. It explicitly states: "The schedule of use is supported by an FDA consensus standard with amplitude/frequency fluctuation being supported by a number of research studies included in this submission." However, the details of these research studies, their methodologies, acceptance criteria, or quantitative results are not included in the extracted text.

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