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The Peace N Quiet device is indicated for use in the temporary relief of tinnitus symptoms. The device plays customized sounds to relieve patients suffering from tinnitus and can be used in a tinnitus management program. The target population is for patients who are 18 years or older. This device should only be used with the advice of a physician, audiologist or other healthcare professional.

The Peace N Quiet tinnitus device is software as a medical device implemented as a mobile application for patients suffering from tinnitus. The Peace N Quiet tinnitus mobile app can be downloaded from the Apple Store onto a personal Apple iPhone device facilitates a qualified healthcare professional (HCP). i.e., physician or audiologist, to provide professional counseling or education to the patient. The HCPs can direct and assist patients to self-administer customized treatments using the Peace N Quiet tinnitus device.

The provided document is a 510(k) Premarket Notification from the FDA for a device called "Peace N Quiet (0.7.0)", which is a software as a medical device (SaMD) intended for the temporary relief of tinnitus symptoms.

Based on the document, here's an analysis of the acceptance criteria and the study that proves the device meets them:

Crucially, the document states: "SUMMARY OF CLINICAL TESTING: Clinical testing was not performed as part of this submission." This means there is no clinical study described in this document to demonstrate the device's performance against acceptance criteria for clinical efficacy or human user performance.

The document focuses on demonstrating substantial equivalence to predicate devices through a comparison of technological characteristics and non-clinical testing (software verification and validation). It does not present acceptance criteria or a study that proves the device meets clinical performance criteria in the way one might expect for a diagnostic or therapeutic AI/ML device that generates specific outputs for classification or prediction.

Therefore, for many of the requested points, the answer will be "Not applicable" or "Not specified in this document" because the submission is not focused on proving clinical effectiveness through a new clinical trial, but rather on demonstrating equivalence based on existing device classifications and non-clinical software testing.

Here's the breakdown based on the request and the provided text:

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

The document does not specify performance acceptance criteria in terms of clinical outcomes (e.g., reduction in tinnitus severity by X%). Instead, the "acceptance criteria" appear to be met by demonstrating substantial equivalence to the predicate devices and by successfully completing software verification and validation.

The closest to "reported device performance" are the technological characteristics listed in the comparison table, which show it operates similarly to the predicates.

Essentially, the "acceptance criteria" here are that the device is demonstrably substantially equivalent to legally marketed predicate devices, and that its software development conforms to relevant standards for safety and performance (i.e., it is well-engineered and functions as intended without introducing new risks).

2. Sample size 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 or patient data for performance evaluation is described in this submission, as "Clinical testing was not performed as part of this submission." The testing referred to is software verification and validation.

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

• Not applicable. As no clinical test set for performance evaluation was involved, no experts were needed to establish ground truth in this context.

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

• Not applicable. As no clinical test set for performance evaluation was involved, no adjudication method was relevant.

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. The document explicitly states "Clinical testing was not performed as part of this submission." Therefore, no MRMC study or assessment of human reader improvement was conducted or reported.

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

• No. The document explicitly states "Clinical testing was not performed as part of this submission." While the device is "software only," its function is to provide customized sounds for a patient to use with the advice of a healthcare professional as part of a management program. Its performance is relative to its ability to play sounds as intended and match the utility of equivalent predicate devices, not as a standalone diagnostic algorithm. The "testing" primarily involved software verification and validation per IEC 62304:2015.

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

• For the software verification and validation testing, the "ground truth" would be the software requirements specifications and design documents. The tests verify that the software functions as designed and meets these specifications. There is no clinical or biological "ground truth" (like pathology or outcomes data) established for device performance in this submission.

8. The sample size for the training set:

• Not applicable. The document does not describe a machine learning model that requires a training set. The "Peace N Quiet" device is described as "software as a medical device" that plays customized sounds. It's not presented as an AI/ML diagnostic or predictive algorithm that learns from data.

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

• Not applicable. As there is no described training set for a machine learning model, the establishment of ground truth for such a set is not relevant.

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Tinearity G1 is intended to generate noise of sufficient intensity and bandwidth to mask ringing in the ears or internal head noise to provide relief for patients with normal hearing in the home healthcare environment. The device is for prescription use only. The target population is adult population over 18 years of age.

Tinearity G1 is applied on intact skin at the mastoid bone and transfers sound through bone conduction to the cochlea. Hearing health care professional shall be consulted for diagnosis, fitting of devices, and follow-up care.

The Tinearity G1 device is designed to generate sounds to be used in a Tinnitus Management Program to relieve patients suffering from tinnitus.

Tinearity G1 comprises of three components: a sound generator, an adapter and a charger. The sound generator is attached to the skin behind the ear by means of the adapter. The sound generator converts white noise into vibrations that are transmitted via the adapter through the skull to the inner ear. The device generates white noise within the frequency span of 700z-10Khz with a maximum output level of 48dB HL.

The adapter is a disposable device that serves as a mechanical connector between the sound generator and the user. The adapter is made up of a plastic holder that is compatible with the sound generator and a medical grade tape to be attached to the user's skin behind the ear. The adapter is a single use device and is designed to be removed daily after each treatment.

The sound generator uses a re-chargeable battery as power source which is charged with the charger.

The Tinearity G1 sound generator and adapter can be used during all times of the day, during sleep as well as during work and spare time.

The provided text describes the Tinearity G1 device, a tinnitus masker, and the studies conducted to support its substantial equivalence to a predicate device. However, it does not provide specific acceptance criteria or reported device performance in a numerical table format for the clinical or non-clinical studies. Instead, it describes generalized successful completion of tests and qualitative observations.

Therefore, I cannot fulfill all parts of your request with specific numerical data as it is not present in the provided text. I will address what is available and indicate when information is not provided.

Here's a breakdown based on the provided document:

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

The document does not present a formal table of acceptance criteria with numerical thresholds and corresponding reported device performance values. It generally states that tests were "successfully performed" or that performance was "found to be equivalent" to the predicate device.

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

• Test Set Sample Size:
  • Clinical Testing (Customer Survey): The document states "Clinical testing was conducted on adult subjects with normal hearing suffering from tinnitus." However, the specific sample size (N) for this customer survey is not provided.
  • Biocompatibility:
    • In vitro: Not specified beyond "production equivalent samples."
    • In vivo: Conducted on "2 rabbits" and "the third rabbit" for irritation testing.
• Data Provenance:
  • Clinical Testing: The location where the customer survey was conducted is not specified. It is referred to as "Real World Evidence (RWE)." The type of study was a "customer survey... held as an interview with a pre-defined questioner," suggesting a prospective data collection method focused on immediate relief.

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. For the clinical survey, while it mentions "Hearing health care professional shall be consulted for diagnosis, fitting of devices, and follow-up care," it does not specify if experts were used to establish "ground truth" for the survey results or their qualifications. The survey itself was based on self-reported perception of relief.

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

This information is not provided in the document. The clinical survey was based on interviews and self-reported perceptions, implying no formal adjudication process for the "ground truth" of tinnitus relief.

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 MRMC comparative effectiveness study was done as described.
• The device is a direct-to-user therapeutic device (tinnitus masker), not an AI-powered diagnostic imaging tool that would typically involve human readers. Therefore, the concept of "human readers improve with AI vs without AI assistance" does not apply to this device.

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

This question is not directly applicable in the context of this device. The Tinearity G1 is a physical device that generates sound, not a software algorithm that performs diagnostic analysis in isolation. Its performance is inherent in its sound generation capabilities and physiological effect, rather than a "standalone algorithm" performance.

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

• Clinical Performance: The "ground truth" for the clinical study (customer survey) was self-reported user perception of "immediate relief (suppression, masking) from the tinnitus sound." It's a form of outcomes data based on subjective patient experience.
• Non-Clinical Performance: For categories like sound output, biocompatibility, electrical safety, EMC, mechanical, the "ground truth" was established by bench testing against defined standards and specifications, and in the case of biocompatibility, specific ISO standards with in vitro and in vivo testing.

8. The sample size for the training set

The document does not mention any "training set" as this device is not described as being based on a machine learning model that would require a distinct training phase. It describes standard engineering and clinical validation processes for a medical device.

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

As there is no mention of a "training set" or a machine learning model, this information is not applicable and therefore, not provided.

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Tinnitogram™ Signal Generator is a sound generating software used in a Timitus Management Program designed to provide temporary relief for people experiencing timitus symptoms. It is intended primarily for adults over 18 years of ages, but may also be used for children 5 years of age or older.

Tinnitogram™ Signal Generator is for use by hearing healthcare professionals who are familiar with the evaluation and treatment of tinnitus and hearing losses. A hearing healthcare professional should recommend that patient listen to the Timitogram™ Signal Generator signal for 30 minutes twice a day at the barely audible level (minimally detectable level).

GOLDENEAR COMPANY's TINNITOGRAM™ SIGNAL GENERATOR is a software as a medical device recommended to use a PC (desktop or laptop computer). TINNITOGRAM™ SIGNAL GENERATOR is fitted to the patient by the healthcare professional. The software enables qualified professional to create customized sounds with specific frequency range for sound therapy/masking.

Device type is Stand-alone software as a medical device. The tinnitus masking signal is generated through a pre-process of securing the patient's customized signal. The test to find tinnitus frequencies, the pre-process, is performed automatically and this masking signal is generated at patient's barely audible level.

The provided document is an FDA 510(k) clearance letter and summary for the Tinnitogram Signal Generator, a software device intended to provide temporary relief for tinnitus symptoms.

Based on the content, the device functions as a sound generator for tinnitus management. The primary method of demonstrating acceptance and safety/effectiveness for this device is by showing substantial equivalence to an existing predicate device (KW Ear Lab's REVE134, K151719), rather than through a complex clinical study with specific performance acceptance criteria like those seen for diagnostic or therapeutic devices.

Therefore, the requested information about acceptance criteria and a study proving the device meets those criteria (especially regarding performance metrics like sensitivity, specificity, or improvement in human reader performance) is not applicable in the traditional sense for this submission. The "study" here is essentially the non-clinical performance data (software verification and validation) to establish that the new device functions as intended and safely, despite some differences from the predicate.

Here's an analysis based on the document's content, explaining why some sections of your request cannot be fulfilled and providing information where available:

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

This type of table, with quantitative performance metrics (e.g., sensitivity, specificity, accuracy) and corresponding acceptance thresholds, is typically required for diagnostic or AI-driven decision support devices. For the Tinnitogram Signal Generator, which is a sound-generating software for tinnitus masking, the "acceptance criteria" are related to its functional operation, safety, and equivalence to a predicate device.

• Acceptance Criteria (Implied from the submission):

  • The software generates sounds for tinnitus masking as intended.
  • The software's functions (e.g., automated tinnitus frequency finding, signal generation) operate correctly.
  • The software's safety and effectiveness are comparable to the predicate device, despite minor technological differences (e.g., maximum output, how tests are performed).
  • The software adheres to relevant medical device software and risk management standards.

• Reported Device Performance:
  "In all verification and validation process, GOLDENEAR COMPANY's TINNITOGRAM™ SIGNAL GENERATOR functioned properly as intended and the performance observed was as expected."

  Note: Specific quantitative performance metrics (e.g., sound output precision, accuracy of frequency determination) are not provided in numerical form in this summary, beyond the specifications listed (e.g., max output 104 dB SPL, frequency range 262-11840 Hz). The "performance" is primarily demonstrated through successful completion of software verification and validation activities.

Table (Best approximation based on available information):

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

• Sample Size for Test Set: This kind of "test set" (e.g., a set of patient data or images) is not applicable here as this is not a diagnostic or AI-based image analysis device. The "test set" in this context refers to the software testing environment.
• Data Provenance: Not applicable. The "data" being tested is the software's functionality, not patient data.

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

• Not Applicable. This device uses software verification and validation, not clinical experts establishing ground truth from patient data cases.

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

• Not Applicable. As above, this is for software verification, not expert adjudication of clinical cases.

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 study was not done. This device is a sound generator, not an AI-assisted diagnostic tool that would involve human readers.
• Effect Size: Not applicable.

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

• Yes, in spirit, a form of standalone testing was done. The "software as a medical device" was "verified and validated" for its intended functions (e.g., generating signals, performing the automated test to find tinnitus frequencies). This testing assesses the algorithm's performance in isolation from patient interaction, ensuring it produces the correct outputs for given inputs. The summary states: "The software was tested against the established Software Design Specifications for each of the test plans to assure the device performs as intended." This constitutes the "algorithm only" performance assessment.

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

• The "ground truth" for this device is the software's design specifications and expected functional behavior. For instance, if the software is designed to generate a 1 kHz tone at 54 dB SPL, the "ground truth" is that 1 kHz tone at 54 dB SPL, and the testing verifies if the software actually produces it. It's a functional "ground truth" rather than a clinical "ground truth."

8. The sample size for the training set

• Not Applicable. This device is not described as using machine learning models that require a training set of data. It is a rule-based or algorithmic sound generator.

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

• Not Applicable. (See #8).

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The SilentCloud in combination with a Tinnitus Management Program is a therapeutic software tool for the treatment of chronic subjective tinnitus for home use.

The target population for the Universal Tinnitus Management System are adult tinnitus patients over 18 years. The SilentCloud is intended to provide relief from the disturbance of chronic subjective timitus while using the device.

The SlientCloud is fitted and programmed by a qualified healthcare professional familiar with timitus treatment.

Not Found

This looks like a 510(k) clearance letter for a medical device called SilentCloud, a therapeutic software tool for the treatment of chronic subjective tinnitus.

However, the provided document does not contain any information regarding acceptance criteria, device performance studies, sample sizes, ground truth establishment, expert qualifications, or adjudication methods. The letter is a formal notification from the FDA stating that the device has received substantial equivalence and can be marketed, but it doesn't detail the technical performance studies that led to this clearance.

Therefore, I cannot provide the requested information based solely on the provided text. To answer your questions, I would need access to the actual 510(k) summary, clinical study reports, or other documentation detailing the device's technical and clinical performance validation.

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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 Tinnitus Sound Generator Module is a tool to generate sounds to be used in a Tinnitus Management Program to temporarily relieve patients suffering from Tinnitus. The target population is primarily the adult population over 18 years of age. This product may also be used with children 5 years of age or older.

The Tinnitus Sound Generator Module is targeted for healthcare professionals, which are treating patients suffering from Tinnitus, as well as conventional hearing disorders. The Tinnitus Sound Generator Module must be done during an in-office visit by a hearing professional participating in a Tinnitus Management Program. If deemed feasible by the hearing professional, subsequent fittings of the Tinnitus Sound Generator Module may be performed remotely and in real time while having live communication via live audio, video and chat on the user's dedicated app.

The Tinnitus Sound Generator (TSG) Module is software that provides a means for healthcare professionals to create a hearing instrument solution that provides temporary relief for Tinnitus patients. This software solution is embedded into a digital hearing instrument platform, so that the end-user (EU) can wear this device in all environments. The fitting of the digital device, which contains the TSG Module, is performed by a healthcare professional, in order to meet the exact needs of the Tinnitus patient.

A mobile medical application (app) is available as an optional device to use with the TSG. The mobile medical app allows the user to adjust the hearing aid within the limits set by the healthcare professional during fitting of the hearing aid. The app is known as the TSG Tinnitus Manager app and is part of the Smart3D app. The Smart3D app also enables a Health Care Professional (HCP) to remotely adjust the TSG settings using a Remote Fine Tuning Feature (RFT). The Support for the RFT feature for the TSG Module can be enabled by the doctor, audiologist or other hearing healthcare professional, at the time of first fitting. Afterwards, the doctor, audiologist or other hearing healthcare professional is able to remotely make adjustments to TSG Module settings. RFT is only enabled when the doctor, audiologist or other hearing healthcare professional finds it feasible, based on an initial in-office assessment of the user and communication with the user, and the parent or legal guardian in cases where the user is a minor. Subsequent to the in-office assessment, the user, or the parent or legal guardian in cases where the user is a minor, is required to accept to receive the adjustments via the TSG portion of the Smart3D app, called the Tinnitus Manager.

Compared to the Remote Fine Tuning, available in the predicate device, the subject TSG Module additionally supports Remote Fitting, being used for real time, online adjustments, with live communication with the end user. Support for Remote Fitting is a process where the end user (EU) has a scheduled appointment with the hearing Health Care Professional (HCP) while the EU is at a remote location, like at home. HCP and EU meet via an HCP initiated live audio, live video and chat on the user's Smart3D app, and adjustments can be made to the Hearing Aids per agreement and prescription of the HCP. During this process, the HCP can make multiple adjustments in real time to the Hearing Aids, including TSG, while having live communication with the EU as if they were in the same room. The session is similar to an adjustment session done at the HCP office, but with the EU at a remote location. When the final settings are decided, a fitting data package is generated by the HCP, and the Hearing Aids are updated remotely while having the live session with the EU. Subsequent to the in-office assessment, the user, or the parent or legal guardian in cases where the user is a minor, is required to accept the adjustments. The Remote Fitting is only made available and technically working for follow-up sessions when found feasible by the HCP, and not available for the initial first-time fitting of the Hearing Aids, that has to take place at the HCP office.

The provided text describes a 510(k) premarket notification for a Tinnitus Sound Generator Module. However, it does not include information about acceptance criteria or a study that proves the device meets those criteria in the context of typical AI/ML medical device submissions.

The document states that the Tinnitus Sound Generator Module is software embedded into a digital hearing instrument. The 510(k) is specifically for a Special 510(k), indicating a modification to an already cleared device (the predicate device K180495).

The primary focus of this 510(k) is the addition of "Support for Remote Fitting" to the existing TSG Module. The document explicitly states:

• "The TSG software is unchanged, but now claims support for the added Remote Fitting feature." (Page 6)
• "The acceptance criteria were not altered, and no additional types of evaluation was needed." (Page 6)

Therefore, the study design elements you've requested (e.g., sample size for test/training sets, expert ground truth establishment, MRMC studies, standalone performance) are typically associated with performance studies for novel devices or significant algorithmic changes in AI/ML products. This submission is for a feature addition to existing software that, according to the manufacturer, uses "already implemented services" and does not change the "basic operating principle of the TSG module" or raise "new or different questions of safety or effectiveness."

Instead of a clinical performance study with acceptance criteria around diagnostic accuracy or efficacy, the document describes verification and validation activities focused on the software and system functionality related to the new remote fitting feature.

Here's a breakdown of what is reported, in the context of your questions, and what is not:

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

• Acceptance Criteria: The document states: "The acceptance criteria were not altered, and no additional types of evaluation was needed." This implies that the original acceptance criteria for the TSG Module itself still apply, but these are not detailed in the document. For the new remote fitting feature, the acceptance criteria appear to be an implicit set of functional and usability requirements focused on the safe and effective operation of the remote fitting process.
• Reported Device Performance:
  • "The result of the system verification show that tests has passed with no defects critical for function, form, intended use, or pose any user risks." (Page 7)
  • "The successful validation activities related to the Support for Remote Fitting feature were conducted to show that human factors and usability are safe and effective as the predicate device." (Page 7)

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

• Test Set Sample Size: Does not apply in the context of a typical clinical performance study for an AI/ML diagnostic. The "testing" described is system verification and validation. There's no mention of a "test set" of patient data in the sense of clinical images or physiological signals.
• Data Provenance: Not applicable. The "software design model" and "verification and validation method" used are "well-established" and the "same as used in the previously cleared 510(k)." (Page 6)

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

• Not applicable. There is no "ground truth" establishment described in the sense of expert annotation of patient data, as this is a software update for a sound generator, not a diagnostic AI.

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

• Not applicable. No expert adjudication process 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. An MRMC study was not done. The device is a "Tinnitus Sound Generator Module" creating sounds for temporary relief, not a diagnostic aid that would assist human readers in interpreting medical images or data. The human interaction described is with healthcare professionals for fitting adjustments, not "readers" of medical cases.

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

• No. This is software within a hearing aid system, designed to be used by healthcare professionals and patients. Standalone performance as an algorithm without human interaction or device integration is not relevant for this type of device.

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

• Not applicable. The ground truth for a Tinnitus Sound Generator is its ability to generate specific sounds and for the new feature, to allow remote fitting of those sounds safely and effectively. This is assessed through system functional tests, rather than clinical ground truth from patient data.

8. The sample size for the training set

• Not applicable. This is not a machine learning device that requires a "training set" of data in the typical sense. It is software that generates sounds and facilitates remote adjustments.

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

• Not applicable.

Summary of Device Performance and Evidence Provided:

The evidence provided for this 510(k) consists primarily of engineering verification and validation efforts designed to demonstrate that the new remote fitting feature works as intended and does not negatively impact the safety and effectiveness of the existing Tinnitus Sound Generator Module.

• Risk Analysis: Performed to demonstrate that all risks are mitigated to an acceptable level.
• Verification & Validation: "Necessary verification and validation activities" performed to show that "design outputs... meet the design input requirements" for the remote fitting feature.
• System Verification: Included "end-to-end testing and interoperability performance testing" of the integrated system (Hearing Instrument hardware, TSG Module, App, Fitting Software).
• Validation for Remote Fitting: Focused on "human factors and usability" to show they are "safe and effective as the predicate device."

In essence, for this specific 510(k) submission, the "study" proving the device met "acceptance criteria" was a comprehensive software and system verification and validation process demonstrating that the updated software behaves functionally as expected and does not introduce new safety concerns for the remote fitting functionality, relying on the already cleared predicate for the core TSG module's performance.

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The Tinnitus Sound Generator Module is a tool to generate sounds to be used in a Tinnitus Management Program to temporarily relieve patients suffering from Tinnitus. The target population is primarily the adult population over 18 years of age. This product may also be used with children 5 years of age or older. The Tinnitus Sound Generator module is targeted for healthcare professionals, which are treating patients suffering from Tinnitus, as well as conventional hearing disorders. The Tinnitus Sound Generator module must be done by a hearing professional participating in a Tinnitus Management Program.

The Tinnitus Sound Generator (TSG) Module provides a means for healthcare professionals to create a hearing instrument solution that provides temporary relief for Tinnitus patients. This software solution is embedded into a digital hearing instrument platform, so that the end-user (EU) can wear this device in all environments. The fitting of the digital device, which contains the TSG Module, is performed by a healthcare professional, in order to meet the exact needs of the Tinnitus patient. A mobile medical application (app) is available as an optional device to use with the TSG. The mobile medical app allows the user to adjust the hearing aid within the limits set by the healthcare professional during fitting of the hearing aid. The app is known as the TSG Tinnitus Manager app and is part of the Smart3D app. The subject TSG Module has a new feature. i.e., Remote Fine-tuning (RFT) communication software (PC Interface software) that communicates with a healthcare professional's Fitting Software (FSW) via the user's Smart3D app and is part of the general software on the digital signal processor in GN's legally marketed, class II, 510(k) exempt Hearing Aids (Reference Device). The RFT communication software in the Reference device enables the healthcare professional to remotely adjust the Hearing Aid settings for these legally marketed, class II, 510(k) exempt Hearing Aids, including Hearing Aids that are compatible with the predicate TSG Module and the new TSG Module. Similarly, the new TSG Module has a PC Interface Software modification that supports fine tuning of TSG Module settings from a remote location. The new TSG Module's PC Interface Software modification opens a bridge between the general RFT function on the Hearing Aid's digital signal processor and the TSG feature settings, that are also available for adjustments via the user's Smart3D app. Therefore, the RFT communication software part of the general software on the Hearing Aids containing the new TSG Module is also part of new TSG Module device. The Health Care Professional (HCP) can make all of the same changes (Volume/loudness, Pitch/frequency. Nature sounds, and Amplitude modulation) that the user can make. Additionally, the HCP can turn the TSG/tinnitus masker on or off and can set and adjust the Volume Control range and environmental steering sounds. The TSG Volume Control range feature is available only to the HCP. This feature allows the HCP to set a limit on the TSG volume range an EU can adjust. This feature is specifically designed for the safety of the EU, ensuring that an EU cannot increase the TSG volume above a level determined appropriate by the HCP. The system can in no case exceed 100dB SPL for TSG. The TSG Volume Control range has a range of +12dB to -6dB from the TSG fitting by the HCP and can be found in the FSW under the Fitting / Manual Controls / Volume Control Range. For example, if the HCP sets the TSG Volume Control range to +6dB to -6dB, this means an EU cannot set the TSG volume more than 6dB above or below the initial fitting.

The provided text is a 510(k) summary for the Tinnitus Sound Generator Module (K180495). It details the device, its intended use, comparison with a predicate device, and performance data. However, it does not include specific quantitative acceptance criteria or a detailed study proving the device directly meets those criteria with statistical data.

Instead, the document focuses on demonstrating substantial equivalence to an existing predicate device (Tinnitus Sound Generator Module, K181586) and a reference device (LiNX3D hearing aid) by showing that the minor modifications do not raise new questions of safety or effectiveness.

Therefore, the following information is extracted and where specific details are not present, it is noted.

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

The document does not explicitly present quantitative acceptance criteria or performance metrics for the Tinnitus Sound Generator Module itself (e.g., how effectively it reduces tinnitus symptoms in a specific percentage of patients). Instead, it relies on demonstrating that its design, performance, and technological characteristics are safe and effective, and do not differ significantly from a legally marketed predicate device.

The performance data described focuses on verification and validation of the system and its RFT feature, rather than direct clinical efficacy trials with acceptance criteria.

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

The document does not specify a separate "test set" with a given sample size in the context of clinical data or patient studies. The performance data refers to verification and validation activities of the device's design and software, and electromagnetic compatibility (EMC) testing. These are primarily engineering and technical tests.

• Sample Size: Not applicable in a clinical sense. The hardware and software components of the system (Hearing Instruments, App, Fitting Software) were tested.
• Data Provenance: The EMC testing was performed by DEKRA Testing and Certification, S.A.U. in Spain. The nature of the other verification and validation activities (e.g., system end-to-end testing) suggests they were conducted internally by GN Hearing. The document does not specify if any user data was collected for these tests, nor its country of origin or whether it was retrospective or prospective.

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 is not applicable as the document describes technical verification and validation, and EMC testing, rather than a study requiring expert consensus for a ground truth derived from clinical data. The "ground truth" for these tests would be compliance with engineering standards and design requirements, as determined by qualified engineers and testers.

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

This is not applicable. The verification and validation activities described are technical and engineering-focused, not clinical studies requiring adjudication of results based on expert review.

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 is not applicable. The Tinnitus Sound Generator Module is a therapeutic device that generates sounds for tinnitus relief, not an diagnostic AI tool for human readers. No MRMC study was mentioned.

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

The device is a "Tinnitus Sound Generator Module" embedded within a digital hearing instrument platform. It is designed to be used in conjunction with a "Tinnitus Management Program" and involves a healthcare professional for fitting and potentially remote fine-tuning.

While the module generates sounds (an algorithmic function), it is not described as a "standalone algorithm" in the typical sense of AI performing an independent diagnostic or predictive task. It functions as part of a system with human intervention (HCP fitting, patient use, remote adjustments).

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

For the technical performance data, the "ground truth" refers to compliance with established engineering and safety standards (e.g., IEC standards for EMC) and the device's design input requirements. There is no mention of clinical outcomes data, pathology, or expert consensus being used as ground truth for a clinical study within this 510(k) summary. The summary focuses on demonstrating substantial equivalence through technical comparisons and verification activities.

8. The sample size for the training set

This is not applicable. The document describes a medical device, not a machine learning or AI model that typically requires a "training set" of data.

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

This is not applicable, as there is no mention of a training set for a machine learning or AI algorithm.

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The Tinnitus Sound Generator Module 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. This product may also be used with children 5 years of age or older.

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

The Tinnitus Sound Generator provides a means for healthcare professionals to create a hearing instrument solution that provides relief for Tinnitus patients. This software solution is embedded into a digital hearing instrument platform, so that the end-user can wear this device in all environments. The fitting of the digital device, which contains the Tinnitus Sound Generator module, is performed by a healthcare professional, in order to meet the exact needs of the Tinnitus patient.

A mobile medical application (app) is available as an optional device to use with the Tinnitus Sound Generator. The mobile medical app allows the user to adjust the hearing aid within the limits set by the healthcare professional during fitting of the hearing aid. The app is known as the TSG Tinnitus Manager app.

This document describes a 510(k) premarket notification for a Tinnitus Sound Generator Module (K181586). However, the document does not describe acceptance criteria for algorithmic performance or a study proving the device meets such criteria.

Instead, it focuses on demonstrating substantial equivalence to a predicate device (K150171) based on:

1. Technological characteristics comparison: Highlighting minor software advancements that improve functionality with minimal risk.
2. Performance Data: Stating that risk analysis, verification, and validation activities were conducted to show the modified device meets design input requirements and is substantially equivalent. These activities appear to be internal and relate to the device's design and functionality rather than clinical efficacy.

Therefore, I cannot provide the requested information regarding acceptance criteria for algorithmic performance, sample sizes for test/training sets, expert qualifications, adjudication methods, MRMC studies, or standalone algorithm performance. The document does not contain details of such a study or information for establishing those criteria.

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audifon Tinnitus-Module is a tool intended to generate sound as part of a Tinnitus Retraining Therapy (TRT) protocol designed to provide temporary relief for people experiencing tinnitus symptoms. The module in a hearing aid.

audifon Tinnitus-Module is intended for adults over 18 years of age.

audifon Tinnitus-Module is targeted for licensed hearing care professionals who are familiar with the evaluation and treatment of tinnitus and hearing losses. The fitting of audifon Timitus-Module must be done by a hearing care professional participating in a tinnitus management program.

The above mentioned audifon Tinnitus module is a digital noise generator which was developed to be used in a tinnitus retraining therapy. This product has up to four different programs, which can be programmed in shape and level to fit the individual user's needs. The programming can be done with a standard HI-PRO and the audifon audifit software. Within the software the amplification of the device can be fitted to the individual needs. The noise can be adjusted in shape with low- and high-cut filters and in the output level. It can be housed in a standard In-the-ear instrument housing, in a standard behind-the-ear instrument housing as well as in standard receiver-in-the ear housing.

The audifon Tinnitus-Module is a digital noise generator intended to provide temporary relief for tinnitus symptoms as part of a Tinnitus Retraining Therapy (TRT) protocol. The device is designed to be embedded in a hearing aid and is targeted for adults over 18 years of age, with fitting to be done by licensed hearing care professionals.

The study presented to establish substantial equivalence for the audifon Tinnitus-Module primarily relies on non-clinical performance data and a comparison to a legally marketed predicate device, the audifon vico TRT devices (K130514).

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly defined by demonstrating equivalence to the predicate device's performance based on official standards (ANSI S3.22-2014) and functional comparisons.

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

The document does not explicitly state a specific sample size for a test set for clinical performance evaluations. The supporting data is described as "non-clinical performance data" measured according to official standards (ANSI S3.22-2014). This implies laboratory testing rather than human subject testing.

The data provenance is Germany, where audifon GmbH & Co. KG, the manufacturer, is located. The study is retrospective in the sense that it relies on existing standards and predicate device data, rather than a new prospective clinical trial.

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

Not applicable, as the evaluation is based on non-clinical performance data and comparison to a predicate device, not on ground truth established by experts for a test set of clinical cases.

4. Adjudication Method for the Test Set

Not applicable, as no clinical test set requiring adjudication is described.

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

No. The document describes a comparison between devices, but not a multi-reader multi-case (MRMC) study involving human readers with and without AI assistance.

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

Yes, in the sense that the "non-clinical performance data" assessed the device's technical specifications (like sound output and frequency range) in isolation, demonstrating its inherent functional capabilities according to industry standards (ANSI S3.22-2014). This is considered a standalone technical performance assessment.

7. The Type of Ground Truth Used

The "ground truth" used is defined by adherence to established industry standards (ANSI S3.22-2014) for hearing aid performance and the functional characteristics of the legally marketed predicate device (audifon vico TRT devices, K130514). This is a technical and regulatory ground truth.

8. The Sample Size for the Training Set

Not applicable. The device is a digital noise generator, not an AI/ML algorithm that requires a training set in the conventional sense. Its functionality is based on programmed parameters and physical acoustic properties.

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

Not applicable, as there is no training set for an AI/ML algorithm. The device's "ground truth" (i.e., its intended and verified performance) is established through its design specifications and compliance with non-clinical performance standards.

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The TinniLogic Mobile Tinnitus Management Device is indicated for use in the temporary relief of tinnitus symptoms. The device is a player to play customized sounds and display professional counseling or education to relieve patients suffering from tinnitus and can be used in a tinnitus management program. The target population is adults (18 years or older). This is a medical device and should only be used with the advice of a physician, audiologist or other hearing healthcare professional.

The TinniLogic Mobile Tinnitus Management Device is a sound player which is designed to assist the qualified healthcare professional in delivering customized sound therapies and professional counseling or education to the patient for treatment. The TinniLogic Mobile Tinnitus Management Device provides idiopathic tinnitus sound treatment based upon sound stimulation during sleeping or waking hours. The TinniLogic Mobile Tinnitus Management Device uses amplitude modulated (SAM) tinnitus pitch matched sounds, narrow-band noise centered at the tinnitus frequency. broad-band noise, pure tone, white noise, natural sounds, and combination of these sounds. The subject device consists of a tablet, a specialized headset, a charger and a charger cable.

The provided text is a 510(k) Summary for the "TinniLogic Mobile Tinnitus Management Device." This document focuses on demonstrating substantial equivalence to predicate devices, rather than establishing acceptance criteria based on a clinical study for a novel device.

The document explicitly states: "No clinical study is included in this submission."

Therefore, it is not possible to describe acceptance criteria or a study that proves the device meets those criteria from the provided text in the way you've requested. The "device performance" reported here is strictly in the context of non-clinical safety/electrical tests and comparison of technical specifications to predicate devices.

However, I can extract information related to the device's technical specifications and how its performance was assessed in a non-clinical context, which serves a similar purpose in a 510(k) submission (demonstrating equivalence rather than novel efficacy).

Here's the information that can be extracted, framed within the limitations of the provided document:

Acceptance Criteria and Device Performance (Based on 510(k) Equivalence)

The TinniLogic Mobile Tinnitus Management Device (K163094) did not undergo a clinical study to establish novel acceptance criteria. Instead, its acceptance for market clearance is based on demonstrating substantial equivalence to legally marketed predicate devices, primarily through non-clinical testing and comparison of technical characteristics. The "performance" in this context refers to its technical specifications matching or being similar to those of the predicate devices, and its compliance with relevant electrical safety and electromagnetic compatibility (EMC) standards.

1. Table of Acceptance Criteria (from predicate comparison) and Reported Device Performance

Note: The "acceptance criteria" in this table are inferred from the demonstrated substantial equivalence to the predicate devices. The device's technical specifications fall within the range or align with the standards met by the predicate devices.

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

• Test Set: Not applicable. No clinical test set or patient data was used for evaluating performance as no clinical study was conducted.
• Data Provenance: Not applicable for clinical data. Non-clinical test data would be from laboratory testing conducted presumably at the manufacturer's facilities in China (Jiangsu BetterLife Medical Co., Ltd.).

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

Not applicable. No clinical ground truth was established, as no clinical study was conducted.

4. Adjudication Method for the Test Set

Not applicable. No clinical test set or adjudication was performed.

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

No, an MRMC comparative effectiveness study was not done. The document explicitly states: "No clinical study is included in this submission."

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

Not applicable. This device is a sound player for tinnitus management; it does not involve an algorithm requiring standalone performance evaluation in the context of diagnostic AI. Its performance is related to its sound output characteristics and electrical safety.

7. The Type of Ground Truth Used

Not applicable for clinical ground truth. For non-clinical testing (electrical safety, EMC, output performance), the "ground truth" would be the applicable international standards (IEC 60601-1, IEC 60601-1-2) and the technical specifications of the predicate devices.

8. The Sample Size for the Training Set

Not applicable. This device is a sound player and does not use machine learning in a way that would require a "training set" in the context of AI/algorithms generating medical insights.

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

Not applicable. As no training set was used.

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