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The IQbuds 2 PRO Hearing Aids are intended to amplify sound for individuals 18 years of age or older with perceived mild to moderate hearing impairment. They are adjusted by the user to meet the user's hearing needs. No pre-programming or hearing test is necessary. The device is intended for over the counter sale and use without the assistance of a hearing care professional.

The Nuheara IQbuds 2 PRO Hearing Aid (Model NU320) is a self-fitting wireless air conduction hearing aid (§ 874.3325) consisting of the hearing aids with Ear Tips. Charge Case, Nuheara software, the Nuheara app, and accessories supplied in the carton. The device is indicated for over-the-counter sale. The hearing aids are designed to be worn in both ears simultaneously with the appropriate size Ear Tips fitted to the sound port of the aid. The device has Ear ID, an innovative hearing assessment system that uses the NAL-NL2 unique programming formula designed for and used globally by hearing aid manufacturers. This hearing profile/personalization system in the IQbuds 2 PRO Hearing Aid assesses the individual's hearing levels across a frequency spectrum to customize the device's amplification specific to their hearing needs. In addition to hearing aid functionality for environmental and directive listening (using the microphones on the aids); the hearing aids can be used for making and receiving phone calls and for streaming audio from a Bluetooth®-compliant mobile device that has been paired with the Nuheara Hearing Aids.

Here's a breakdown of the acceptance criteria and the study that proves the Nuheara IQbuds 2 PRO Hearing Aid meets them, based on the provided document:

The document describes the performance of the Nuheara IQbuds 2 PRO Hearing Aid as part of its 510(k) premarket notification to the FDA, demonstrating its substantial equivalence to predicate devices. The studies primarily focus on usability and clinical performance to show effectiveness and safety.

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly list "acceptance criteria" in a clean table format with specific numerical targets for usability or clinical performance in the same way it does for electro-acoustic characteristics. Instead, the acceptance criteria for Usability and Clinical Performance appear to be demonstrated by showing that the device is safe and effective for its intended use by the target population and that its performance is comparable to established benchmarks or predicate devices.

For Electro-Acoustic Characteristics, the acceptance criteria are implicit: the device must meet or be within the established standards (ANSI S3.22 and CTA 2051:2017) and be comparable to the predicate device.

Implicit Acceptance Criteria and Reported Performance (derived from the text):

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

• Usability Testing:
  • Sample Size: Eighteen (18) adults.
  • Data Provenance: The study was conducted in a "quiet, comfortable room" for one-on-one sessions, implying a controlled, prospective study. The location is not explicitly stated (e.g., country of origin), but the context of an FDA submission for a US market suggests it was likely conducted in the US or in compliance with US regulatory standards.
• Clinical Performance Study:
  • Sample Size: Forty-three (43) adults.
  • Data Provenance: This was a "prospective investigation." Similar to usability, the exact country is not stated, but it's part of a US FDA submission.

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

The document does not explicitly state the number or specific qualifications of experts used to establish ground truth for the test set in the same way one might expect for imaging studies.

• Usability Testing: "An independent, trained moderator conducted each session." It doesn't specify if experts established a 'ground truth' for whether a task was performed correctly beyond the scoring of completion by the moderator and review by a "cross-functional team."
• Clinical Performance Study:
  • NAL-NL2 Reference: The "audiologist determined REM using standard audiologic practice (NAL-NL2)" serves as a direct ground truth. This implies audiologists were involved.
  • Subjective Questionnaires (APHAB, SSQ): These are self-reported measures, so the "ground truth" is the participant's own perception, not expert-established.
  • Speech in Noise: This involves objective performance (percent recall of sentences) vs. a known noise background.
  • The "Ear ID feature... was developed and validated by National Acoustics Laboratories (NAL)." This indicates expert development of the core self-fitting algorithm.

No explicit mention of a "number of experts" for adjudication or ground truth per test case.

4. Adjudication Method for the Test Set

The document does not describe a formal "adjudication method" like 2+1 or 3+1, which is common in radiologic image interpretation studies.

• Usability Testing: Participants were "scored on status of completion of all steps in each of the tasks." A "cross-functional team reviewed outcomes at frequent intervals and addressed changes." This implies consensus or review, but not a specific adjudication protocol.
• Clinical Performance Study: The methods used (comparison to NAL-NL2, self-reported questionnaires, objective speech-in-noise tests) are direct measurements or comparisons against established audiological standards, not subject to typical human reader adjudication.

5. Multi Reader Multi Case (MRMC) Comparative Effectiveness Study

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not conducted in the traditional sense of human readers interpreting medical images with and without AI assistance. This device is a self-fitting hearing aid, not an AI for image interpretation.

The clinical performance study does compare the performance of the device's self-fitting method (Ear ID) to established audiological practices (NAL-NL2) and to the unaided condition, demonstrating clinical effectiveness. This serves a similar purpose of demonstrating effectiveness, but via audiological metrics rather than MRMC.

• Effect Size (Unaided vs. Aided performance from APHAB):
  • Unaided to Aided difference in mean scores (lower is better):
    • Ease of Communication (EC) in quiet: 7.4 points
    • Reverberation (RV): 8.2 points
    • Background Noise (BN): 17.8 points
    • Global Score: 11 points
  • These improvements were "well within the published 5-30 (%) percentile norms for the APHAB (Cox and Alexander, 1995)." The study also references Valente et al., 2018, which showed a significant median advantage of 4.2% for NAL-NL2 fitted subjects vs. manufacturer default fit for the background noise subscale problem score.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance)

Yes, the "Clinical Performance" study effectively assesses the standalone performance of the device's self-fitting algorithm (Ear ID) by:

• Quantitatively comparing target gain from the self-fit (Ear ID) to audiologist-determined NAL-NL2 REM targets. This is a direct measure of the algorithm's output against a gold standard.
• The entire premise of a "self-fitting" hearing aid is that the algorithm (Ear ID) performs the fitting function without professional human intervention in the loop.

7. The Type of Ground Truth Used

• Clinical Performance:

  • Expert Consensus/Standard Practice: For the quantitative comparison, the ground truth was "audiologist determined REM using standard audiologic practice (NAL-NL2)." This represents a professional, expert-established standard.
  • User Performance/Subjective Outcomes: For the APHAB and SSQ, the ground truth is the individual participant's self-reported perception of their listening experience and sound quality. For Speech in Noise, it's the objective percentage of recalled sentences.

• Usability Testing: The ground truth for task completion was based on the success/failure observed by a trained moderator against predefined task steps.

8. The Sample Size for the Training Set

The document does not specify a separate "training set" for the device's main self-fitting algorithm. The Ear ID system is described as using a "validated NAL-NL2 fitting algorithm" developed by National Acoustics Laboratories (NAL). NAL-NL2 is a widely recognized and established prescriptive formula for hearing aid fitting, not typically something a new device "trains" on in the machine learning sense. Instead, the device implements this algorithm.

If there were any machine learning components (e.g., for noise reduction or sound processing features), the training data for those are not disclosed in this document. The focus here is on the validation of the implementation of the NAL-NL2 principle and the device's overall performance.

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

As noted above, there's no explicitly mentioned "training set" for the core self-fitting algorithm (Ear ID) in the machine learning sense that would require a separate ground truth establishment. The Nuheara IQbuds 2 PRO Hearing Aid utilizes the "validated NAL-NL2 fitting algorithm." The ground truth for NAL-NL2 itself (as a prescriptive target based on audiometric data) is an established audiological standard developed through extensive research and clinical validation by the National Acoustics Laboratories.

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