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The Sanuthera's Serenity device is indicated to provide a mean of sound enrichment therapy that is programmed by a hearing health care professional familiar with diagnosis and management of tinnitus as part of a personalized tinnitus management program to provide temporary relief from the tinnitus symptoms.

The target population is primarily the adult population over 18 years of age.

Sanuthera's Serenity is a device utilizing sound therapy as a means to mitigate the symptoms associated with tinnitus. The Serenity device works as a plug-in device to the uDirect2 bridge device, manufactured by a hearing- aid company Unitron and can be customized to a patient's tinnitus profile and then adjusted to his/her preference to play a number of sounds aimed at obscuring the ringing in the patient's ear and/or re-train patients to avoid focusing on the ringing, essentially “habituating” them away from the disease.

The process of providing tinnitus therapy occur a number of ways although the most popular are Tinnitus Retraining Therapy (TRT) and Tinnitus Masking (TM). In either case, the patient is provided with the Serenity device which is custom programmed. The patient is then taken through a process of multiple protocols to set filter and volume parameters via an onboard processing unit and an onboard digital band pass filter to slowly assist in the habituation to the tinnitus.

Associated Accessories:
• The Software that is utilized by an audiologist to customize, per patient's preference during the device fitting process, the sounds aimed at obscuring the ringing in the patient's ear and/or re-train patients to avoid focusing on the ringing.
• The Unitron's commercially available neck-worn uDirect2 bridge device with Unitron's Moxi Kiss Behind-the-Ear family hearing aids (K130494).
• The battery charger to simultaneously charge in parallel the batteries of the Serenity and the uDirect2 bridge device.

The provided text is a 510(k) premarket notification for a Tinnitus Masker device (Serenity). This type of document is submitted to the FDA to demonstrate that a medical device is substantially equivalent to a legally marketed predicate device.

Crucially, a 510(k) submission for a Class II device like a Tinnitus Masker, especially one cleared through substantial equivalence to a previously marketed device, often relies on demonstrating technological equivalence and safety and effectiveness through non-clinical performance data and comparison to the predicate, rather than new, extensive clinical studies with specific statistical acceptance criteria for a novel AI algorithm.

The document states:

• "The Serenity Tinnitus Masking Device did not conduct any performance testing on animals."
• "The Serenity Tinnitus Masking Device did not conduct any clinical testing."

It mentions "Software Verification and Validation Testing" but does not provide specific performance metrics, acceptance criteria, or a study design for a clinical performance study as would be typical for an AI-powered diagnostic device. The "performance data" section primarily discusses biocompatibility and software validation in general terms.

Therefore, many of the typical questions for AI acceptance criteria and studies (like sample size, number of experts, adjudication, MRMC studies, effect size, training set details) are not applicable to this specific 510(k) submission, as it does not rely on a clinical study demonstrating AI performance against a ground truth.

Based on the provided text, I cannot fill out the requested table and details because the device is a Tinnitus Masker, not an AI diagnostic device, and its 510(k) clearance is based on substantial equivalence to a predicate device, without new clinical performance studies.

However, I can extract the relevant information regarding the type of data presented and the basis for its clearance:

Summary of Acceptance Criteria and Study Information as Pertains to this 510(k) Submission (which is not an AI-driven device requiring clinical performance metrics):

Given that the device is a Tinnitus Masker – a sound therapy device – and not an AI diagnostic tool, the typical "acceptance criteria" for AI performance metrics (e.g., sensitivity, specificity, AUC) and associated studies (clinical trials comparing AI-assisted vs. unassisted performance) are not present in this document. The "proof" of the device meeting criteria relies on demonstrating substantial equivalence to an existing predicate device based on technological characteristics and safety considerations.

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Not Applicable. No clinical test set data is presented in this 510(k) submission for performance evaluation. The device clearance relies on demonstrating substantial equivalence to a predicate based on existing technological and safety profiles, and non-clinical testing (biocompatibility, software validation).

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

• Not Applicable. No test set with ground truth established by experts is mentioned, as there were no clinical studies for performance.

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

• Not Applicable. No test set requiring expert adjudication is mentioned.

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 is not an AI diagnostic device, and no MRMC study was conducted or required for this type of 510(k) clearance.

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

• Not Applicable. This is not an AI diagnostic algorithm. The device's "standalone" function is to generate sound, which is then customized and used by a healthcare professional as part of a patient's management program.

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

• Not Applicable. As no clinical performance study was conducted, there was no ground truth established for performance evaluation. The "ground truth" for the device's function is its ability to produce sounds according to specifications, which is verified through software and hardware testing, not clinical outcomes data in this submission.

8. The sample size for the training set:

• Not Applicable. This device is not an AI/machine learning model that requires a "training set" in the conventional sense. The "training" that occurs is the programming of the device by a healthcare professional according to a patient's individual needs.

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

• Not Applicable. See point 8.

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