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This air-conduction behind-the-ear hearing instrument, intended to amplify sound pressure waves and transmit the signal to the external ear through the medium of air, is designed to compensate for hearing losses from mild to severe.

This air-conduction behind-the-ear hearing instrument, intended to amplify sound pressure waves and transmit the signal to the external ear through the medium of air, is designed to compensate for hearing losses from mild to severe.
The device is powered by a standard hearing aid battery (type 13).
The device is manufactured and delivered completely assembled to the hearing aid dispenser using materials and techniques widely used by other manufacturers of hearing devices.
The intended use, performance specifications, functions and operations of the ReSound® BT4 . Personal Hearing System™ are essentially identical to that described in the 510(k) Premarket Notification for the ReSound® Personal Hearing System BT.
The ability to program digitally the fitting parameters of the hearing device is the same as in the ReSound® Personal Hearing System BT, as is the ability to change the characteristics of the sound processing and adjust the volume via an ultrasound remote control. The ReSound® BT4 Personal Hearing System™ and the predicate device have the ability to retain two programs in memory.
The operation and functioning of the DAI option is identical to that offered by other hearing aid manufacturers.

This document is a 510(k) summary for the ReSound® BT4 Personal Hearing System™. It is a premarket notification for a medical device and provides very limited information about performance or a clinical study in the way a modern clinical trial summary would.

Based on the provided text, the device is a hearing aid, and the submission is focused on demonstrating substantial equivalence to a predicate device (ReSound® Personal Hearing System BT, marketed as BT2, K912665/A).

Therefore, it is highly unlikely that the typical "acceptance criteria" and "study proving device meets criteria" as defined for a diagnostic AI/ML device (which is what these questions usually relate to) would be present in this type of document from 1996 for a hearing aid.

Here's an attempt to answer the questions based only on the provided text, acknowledging that most questions cannot be answered directly from this document:

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

The document does not provide a table of acceptance criteria for specific performance metrics (e.g., sensitivity, specificity, accuracy) or quantitative performance data from a study. Instead, it asserts substantial equivalence based on the following general points:

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

This information is not provided in the document. As this is a 510(k) for a hearing aid from 1996, it's highly improbable that a "test set" in the context of an AI/ML algorithm's performance evaluation was used or would be reported in this manner. The "study" here is demonstrating equivalence, not necessarily a performance trial on human subjects with a defined test set.

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

This information is not provided and is not applicable to the type of regulatory submission presented.

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

This information is not provided and is not applicable.

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

A MRMC study as described (comparing human readers with/without AI assistance) was not done and is not applicable to this 1996 hearing aid submission.

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

A standalone algorithm performance study as described is not applicable to this device. The device itself is a hearing aid, not an AI algorithm.

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

The concept of "ground truth" as typically used for AI/ML device evaluation is not applicable here. The "truth" being established is that the new device is substantially equivalent to an existing, legally marketed device.

8. The sample size for the training set

This information is not provided and is not applicable. There is no indication of an AI/ML training set in the document.

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

This information is not provided and is not applicable. There is no indication of an AI/ML training set in the document.

Summary based on the provided text:

The document is a 510(k) summary for a hearing aid, demonstrating substantial equivalence to a predicate device. It focuses on functional and operational similarities rather than detailed performance metrics from a clinical study with acceptance criteria often seen for imaging or AI/ML-based diagnostic devices. Therefore, most of the requested information, which pertains to AI/ML or extensive clinical trial performance, is not present or applicable.

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