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The Concha Sol 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 use without the assistance of a hearing care professional.

The Concha Sol OTC Hearing Aids (Model CL-1001) are receiver-in-the ear, self-fitting, wireless air conduction hearing aids (§ 874.3325) intended to amplify sounds in the environment for adult users who have a perceived mild-to-moderate hearing loss. The hearing aids include Ear Tips, Carry Case and the Concha Labs mobile application. The device is indicated for over-the-counter sale (product code QUH) and integrates user input with a self fitting strategy, enabling users to independently derive and customize their hearing aid fitting and settings. Self-fitting wireless air-conduction hearing aids are Class II medical devices. The Self-Fitting hearing aids incorporate microphones for audio input, and sound is delivered to the ear via a receiver that can be coupled with domes. The mobile application contains a self-fitting software known as Soundscope, an innovative software that uses the NAL-NL2 programming formula used globally by hearing aid manufacturers. The hearing profile/personalization system in the Concha Sol Hearing Aid assesses the individual's hearing levels across a frequency spectrum in order to generate and customize the device's amplification specific to their hearing needs. The self-fitting software also assesses the individual's hearing preferences to help fine-tune the device's amplification. In addition to hearing aid functionality for environmental and directive listening; the hearing aids can also be used for telephony and streaming audio from a Bluetooth® compliant mobile device. The hearing aids are powered using Zinc Air size 312 cell batteries.

The Concha Sol Hearing Aids (CL-1001) were evaluated for their effectiveness and safety through a clinical study. The study objective was to assess the performance and clinical effectiveness of the self-fitting hearing aid using two distinct fitting methods: SELF-FIT (user-fitted with the Concha Labs App) and CLIN-FIT (clinically fitted by a hearing care professional).

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: 21 participants (13 men, 8 women).
• Data Provenance: The document does not explicitly state the country of origin. The study design ("within-subject, randomized, crossover study design of the clinical investigation") suggests it was a prospective clinical study.

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

• Number of Experts: The document details the "CLIN-FIT" method, which involved fitting by a "hearing care professional." It does not specify the number of individual hearing care professionals involved or their specific qualifications (e.g., years of experience).

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable in the traditional sense for these endpoints. The study compared two fitting methods (self-fit vs. clinician-fit) within the same subjects, using standardized objective (QuickSIN) and subjective (APHAB) outcome measures. The "ground truth" for the CLIN-FIT condition was established by the hearing care professional's fitting, which was then used as a reference for comparison.

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

• No, a MRMC comparative effectiveness study was not explicitly described. The study design was a "within-subject, randomized, crossover study" to compare the performance of the Concha Sol device under two different fitting methods (SELF-FIT vs. CLIN-FIT). While human readers (users and a clinician) were involved in the fitting process and perception, it was not framed as an MRMC study comparing interpretations of diagnostic cases.
• Effect Size of Human Readers Improvement with AI vs. Without AI Assistance: Not applicable, as this was not a diagnostic AI study. The "AI" component would be the self-fitting software (Soundscope), which the users interact with directly. The comparison was between user-driven fitting and clinician-driven fitting of the same device.

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

• No, a standalone (algorithm only) performance study was not explicitly described for clinical effectiveness. The clinical study inherently involved human feedback and interaction (either by the user for SELF-FIT or by the clinician for CLIN-FIT). The Soundscope software's performance was evaluated as part of the overall device system in conjunction with human use. Electroacoustic testing provided standalone performance metrics for the hardware and general sound processing, but not specifically for the self-fitting algorithm's clinical outcomes without human interaction.

7. Type of Ground Truth Used

• Ground Truth: The study used the performance of the device when fitted by a hearing care professional (CLIN-FIT) as a reference "ground truth" for comparison against the user's self-fitting (SELF-FIT) results. This is an expert-derived benchmark using established clinical practices.
  • QuickSIN: Objective measure of speech communication in noise.
  • APHAB: Subjective measure of hearing impairment and benefit in daily life.
  • Safety: Directly observed adverse events and health-related issues.

8. Sample Size for the Training Set

• Not Applicable / Not Provided: The document describes a clinical validation study for the Concha Sol device. It does not mention a separate "training set" for the self-fitting algorithm. The Soundscope software uses the NAL-NL2 programming formula, which is an established, globally used, prescriptive target rule for hearing aid fitting, implying its development and "training" occurred much earlier and separately from this device-specific validation.

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

• Not Applicable / Not Provided: As noted above, the document does not describe a training set for the self-fitting algorithm within the context of this submission. The NAL-NL2 (National Acoustic Laboratories - Nonlinear 2) formula, which the Soundscope technology utilizes, is a well-established prescriptive method in audiology. Its "ground truth" (i.e., its derivation and validation) would stem from extensive research, clinical trials, and epidemiological data in hearing science involving human perception, speech intelligibility, and comfort over many years, conducted by the National Acoustic Laboratories (Australia) and other research institutions. This is a foundational audiological principle rather than a training set specifically for this device's algorithm.

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The WSA Self-Fitting Hearing Aid Gen 2 is intended to amplify sound for individuals 18 years of age or older with perceived mild to moderate hearing impairment. It is adjusted by the user to meet the user's hearing needs through software tools. The device is intended for direct-to-consumer sale and use without the assistance of a hearing care professional.

The SF-App is intended to support self-fitting and fine-tuning of the hearing aid.

The WSA Self-Fitting Hearing Aid Gen 2 ("SF Gen 2") is a self-fitting air conduction hearing aid that is intended to compensate for impaired hearing and incorporates technology, including software, that allows users to program their hearing aids. This technology integrates user input with a self-fitting strategy and enables users to independently derive and customize their hearing aid fitting and settings.

The SF Gen 2 hardware includes: Earpieces (sleeves), housing, circuit board including a chip set running embedded software, antenna for near-field magnetic inductive wireless connection for data exchange between the left and right hearing aids, rechargeable battery, and electroacoustic components. The instant fit in-the ear (ITE) style of the hearing aids uses sleeves in 4 different sizes to couple with the ear canal. The sleeves are available in vented and closed styles. The hearing aids are powered by built-in rechargeable Lithium-lon batteries. The device includes embedded software that communicates with the self-fitting software app.

The SF Gen 2 self-fitting system consists of: (a) a wireless hearing aid with a self-fitting feature, and (b) a software application to support hearing aid self-fitting and fine tuning. The subject device is fitted for bilateral use. Left and right hearing aids can communicate with each other over a magnetic inductive wireless link, and the hearing aids communicate with the self-fitting web application (the "self-fitting app") using acoustic technology.

The SF Gen 2 self-fitting app is run on an Internet browser that is integrated into a software app that is downloaded onto and accessed through the user's mobile device. The self-fitting strategy begins with an acoustic profiling test that the user performs while wearing the hearing aids. Based on the user's hearing profile, a "cluster" of initial settings is applied to each hearing aid, and users are then guided through fine-tuning of these settings to self-fit the hearing aids for their particular needs and comfort. The mobile app also allows the user to adjust audiological gain parameters and preferred settings on the hearing aid, and functions as a remote control for adjusting hearing aid volume during daily use.

The provided text describes a 510(k) premarket notification for the "WSA Self-Fitting Hearing Aid Gen 2" and claims substantial equivalence to a predicate device, the "Vibe SF Self-Fitting Hearing Aid (K220403)".

While it mentions performance testing for various engineering properties, it explicitly states that "no new clinical performance testing was required." This means there is no detailed study described that establishes a specific acceptance criterion (e.g., in terms of hearing improvement or speech understanding) and then proves the device meets it through a clinical trial. Instead, the argument for safety and effectiveness is based on the device's substantial equivalence to a previously cleared predicate and non-clinical performance testing of its components.

Therefore, the requested information elements related to clinical study design (sample size, ground truth, expert opinions, MRMC, standalone performance) cannot be fully answered as these types of studies were not conducted or described for this specific submission as per the provided text.

Here's the information that can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not describe a clinical test set or patient data used for evaluation of the device's hearing performance. The "Performance Testing" section refers to non-clinical (engineering) tests.

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 with human-established ground truth for hearing performance is described.

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

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

Not applicable. The device is a self-fitting hearing aid, not an AI diagnostic tool primarily evaluated with human readers. The submission explicitly states "no new clinical performance testing was required."

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

The document describes non-clinical technical testing (e.g., electroacoustic performance, software validation) of the device's components and overall system. While these tests evaluate the "algorithm" or device's standalone performance in specific technical domains, it does not refer to "standalone performance" in the context of a clinical outcome that would typically be compared to human performance (e.g., a standalone AI diagnostic algorithm).

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

For the non-clinical performance tests, the "ground truth" or reference is typically the specified international standards and regulations (e.g., IEC, ANSI, CFR requirements). For example, electroacoustic performance is compared against the limits defined in ANSI/ASA S3.22:2014.

8. The sample size for the training set

Not applicable. The document does not describe the development or training of a machine learning model beyond the general mention of a "self-fitting strategy" which "integrates user input with a self-fitting strategy." It does not specify a separate training set for a machine learning algorithm.

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

Not applicable, as no training set for a machine learning algorithm is described.

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The Soundwave Hearing Sontro® Self-Fitting OTC Hearing Aids are intended to amplify sounds for use by individuals 18 years and older with perceived mild to moderate hearing impairment. The device is intended for over-the-counter sale and use without the assistance of a hearing care professional.

Per 21 CFR 874.3325, a self-fitting wireless air-conduction hearing aid is a wearable soundamplifying device intended to compensate for impaired hearing. It incorporates technology, including software, that allows users to program their hearing aids. This technology integrates user input with a self-fitting strategy, enabling users to independently derive and customize their hearing aid fitting and settings. This is an over-the-counter hearing aid.

The Soundwave Hearing, Sontro® OTC (over-the-counter) Hearing Aids are self-fitting wireless air conduction hearing aids consisting of the hardware and software: the device uses the otoTune® app and accessories supplied in the carton. Each hearing aid in the pair functions and interacts with the otoTune® app independently and as a system.

A disposable size 312 zinc-air battery powers the hearing aids. The hearing aids incorporate microphones for audio input, and sound is delivered to the ear via a receiver in the canal that can be coupled with ear domes. The hearing aids are controlled via onboard button controls and wirelessly via the otoTune® app (iOS and Android). The controls allow the user to configure parameters, settings, and listening modes.

Here's a breakdown of the acceptance criteria and the study details for the Sontro® OTC Hearing Aids (AI), based on the provided document:

Acceptance Criteria and Device Performance

Study Details

1. Sample Size used for the test set and the data provenance:

   • Sample Size: 29 participants were enrolled in the study (13 men, 16 women). 17 subjects withdrew due to poor compliance or personal reasons, meaning the final analysis was likely based on 12 participants.
   • Data Provenance: The document does not explicitly state the country of origin but implies a single clinical study setting. It was a prospective study involving participants with perceived mild to moderate hearing impairment.

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

   • The "ground truth" for the test set in this context refers to the CLINIC-FIT measurements. These were established by an "audiology-best-practices hearing aid fitting," which implies fitting by a qualified audiologist. The document does not specify the exact number of audiologists or their years of experience but indicates adherence to "audiology-best-practices."

3. Adjudication method for the test set:

   • The clinical study compared the device's self-fitting method (SELF-FIT) against a clinician-fitted method (CLINIC-FIT). There isn't an explicit "adjudication method" described in the sense of multiple experts reviewing cases. Instead, the "ground truth" (CLINIC-FIT) was established by standard audiological best practices. The comparison was statistical, assessing non-inferiority between the SELF-FIT and CLINIC-FIT results.

4. 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, a traditional MRMC study comparing human readers with and without AI assistance was not explicitly stated or conducted as described. This study focuses on the effectiveness of a self-fitting hearing aid compared to a clinician-fitted hearing aid, not on AI assistance for human "readers" of medical images or data.

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

   • Yes, the "SELF-FIT" arm of the study represents the performance of the device's self-fitting algorithm without direct human (audiologist) intervention in the fitting process. The user themselves interacts with the app to perform the fitting. However, it's important to note that the user is "in the loop" for the self-fitting process, but an audiologist is not. So while not a fully "algorithm-only" standalone per se, it is standalone clinician-free fitting.

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

   • The ground truth for comparison ("reference standard") was expert-established audiological measurements and patient-reported outcomes, specifically:
     • Real-Ear Aided Response (REAR) based on audiology-best-practices NAL/NL2 prescription, representing an objective acoustic measure.
     • Abbreviated Profile of Hearing Aid Benefit (APHAB) global scores, representing subjective patient outcomes.
     • QuickSIN test results, representing an objective measure of speech recognition in noise.

7. The sample size for the training set:

   • The document does not provide information regarding a specific training set size for the self-fitting algorithm. The focus of this submission is the clinical validation of the device itself, which incorporates the self-fitting technology. The development and training data for the underlying algorithm are not detailed here.

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

   • As there is no information on a specific training set in the provided text, there is also no information on how the ground truth for such a set was established. It can be inferred that the NAL-NL2 fitting algorithm, which the device utilizes, is a widely validated and established prescriptive method in audiology, derived from extensive research and clinical data over time, rather than a specific "training set" for this particular device submission.

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The Self-Fitting hearing aids are intended to amplify sound for individuals 18 years of age or older with to moderate hearing impairment. They are adjusted by the user's hearing needs. The device is intended for use without the assistance of a hearing care professional.

Per 21 CFR 874.3325, a self-fitting wireless air conduction hearing aid is a wearable sound amplifying device that is intended to compensate for impaired hearing and incorporates technology, including software, that allows users to program their hearing aids. This technology integrates user input with a self-fitting strategy and enables users to independently derive and customize their hearing aid fitting and settings. Self-fitting wireless air conduction hearing aids are Class II medical devices. The Self-Fitting hearing aids incorporate microphones for audio input and sound is delivered to the ear via a receiver that can be coupled with domes. Self-Fitting hearing aids are controlled via button controls and wirelessly via the smart hearing app (iOS and Android). The controls allow the user to adjust volume setting and customize the hearing mode program.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Acceptance Criteria and Device Performance for Self-Fitting Hearing Aids (K221052)

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample Sizes and Data Provenance:

• Clinical Test Set Sample Size: 36 subjects were initially enrolled, but 6 withdrew, resulting in 30 subjects for analysis. The document states the planned minimum was 32 subjects.
• Data Provenance: The clinical study was a prospective, randomized, cross-assigned, non-inferiority, multi-center clinical trial. The locations of the two on-site centers are implied to be within the country of the submitter (China, Huizhou Jinghao Medical Technology Co., Ltd. and Shenzhen Reanny Medical Devices Management Consulting Co., Ltd.), though not explicitly stated for the subjects' origin.

3. Number and Qualifications of Experts for Ground Truth:

• For the Pro-fit condition, which serves as a comparison to the self-fit device, the text refers to "audiological best practice hearing aid fittings." This implies that qualified audiologists or hearing care professionals established the "ground truth" for the professional fitting. The number and specific qualifications of these experts are not explicitly stated in the provided text.

4. Adjudication Method for the Test Set:

• The study design was a randomized, cross-assigned, non-inferiority, multi-center clinical trial. Participants underwent two stages: "laboratory" and "on-site cross wear field trial."
• Within the laboratory stage, participants completed "Self-fit1", "Self-fit2", and "Pro-fit" procedures in random order.
• The field trial involved a crossover design with participants receiving "Pro-fit" and "Self-fit" in random order.
• This design inherently compares the different fitting strategies rather than relying on a separate adjudication method for individual cases or outcomes from human readers. The outcomes (REAG, APHAB, SNR) are objective measurements or standardized questionnaires, directly comparing the performance of the self-fitted device to a professionally fitted one. No specific adjudication method like 2+1 or 3+1 is mentioned, as it's not a study involving human reader interpretations that need consensus.

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 for image interpretation. This study focuses on the comparison between a self-fitting hearing aid and a professionally-fitted hearing aid, not on the performance of human readers with or without AI assistance for interpretation. Therefore, there is no effect size of how much human readers improve with AI vs. without AI assistance.

6. Standalone (Algorithm Only) Performance Study:

• Yes, a standalone performance study was conducted in the sense that the "Self-fit" condition represents the algorithm's performance without direct intervention from a hearing care professional during the fitting process by the user. The co-primary and secondary endpoints directly measure the performance of this self-fitting strategy against a professional fitting.

7. Type of Ground Truth Used:

• For the clinical study, the "ground truth" or reference for comparison was established by:
  • Audiological Best Practice Hearing Aid Fittings (Pro-fit): This involved a professionally conducted fitting, likely by qualified audiologists, measuring Real Ear Aided Gain (REAG) and collecting data on Abbreviated Profile of Hearing Aid Benefit (APHAB) and Speech Recognition Threshold in Noise (SNR). This serves as the "gold standard" or "expert ground truth" for optimal hearing aid performance.
  • Repeated Self-fitting Measurements (Self-fit1 vs. Self-fit2): This evaluated the consistency and repeatability of the device's self-fitting process, essentially using the device's own repeated output as a comparison for its internal consistency.

8. Sample Size for the Training Set:

• The document describes a clinical validation study for effectiveness and safety. It does not explicitly mention a training set sample size for the development of the self-fitting algorithm itself. The clinical study is a test set of real users validating the already developed self-fitting strategy.

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

• Since there's no explicit mention of a training set or its sample size, there's no information provided on how ground truth for a training set was established. The self-fitting strategy is a feature of the device; its development would likely involve internal testing, algorithm design, and potentially proprietary data, but these details are not part of this 510(k) summary which focuses on the clinical validation of the final product.

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Intrisound™ Tuned Lumen® 155 are self-fitting, wireless air conduction hearing aids, intended to amplify sound for individuals 18 years of age or older with perceived mild to moderate hearing impairment. They are to meet the user's hearing needs. The device is intended for use without the assistance of a hearing care professional.

The Intrisound™ Tuned Lumen® 155 Hearing Aid is a wireless, self-fitting air conduction hearing aid. It features digital signal processing (16 channel wide dynamic input compression, 3 layer fastacting output compression, 16 channel noise reduction, feedback cancellation), bi-directional microphone with windscreen, volume and program control, 12 band equalizer, self-selectable tube and ear tips, and customization through the Tuned Mobile Application. The Tuned Mobile Application aims to detect accurate auditory thresholds, partnering with a smart phone application to deliver user-customized sound through the Intrisound™ Tuned Lumen® 155 Hearing Aid. These thresholds are used to program the device using a proprietary algorithm.

The provided text describes the acceptance criteria and the studies conducted for the Intrisound™ Tuned Lumen® 155 Hearing Aids.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not present a single, consolidated table specifically labeled "Acceptance Criteria and Reported Device Performance" in the typical format of a summary table for a medical device. However, the STUDY 1 section clearly outlines acceptance criteria for various endpoints and then immediately follows with the reported results for those criteria. Similarly, Table 2 and Table 3 detail performance characteristics against standards.

Let's synthesize the information specifically from STUDY 1 and relevant tables:

Acceptance Criteria and Reported Device Performance for Intrisound™ Tuned Lumen® 155 Hearing Aids

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

STUDY 1 (Clinical Performance Validation):

• Sample Size: 30 participants (adults).
• Data Provenance: Retrospective or Prospective is not explicitly stated as a separate point; however, the study design section states it was a "prospective, crossover, comparative study." The recruitment from "private hearing clinics" suggests the data is likely sourced from the country where these clinics are located, but the country of origin is not explicitly stated.

STUDY 2 (Subjective Outcome Comparison - COSI/IOI-HA):

• Sample Size: 41 participants (N=41 completed the study: 20 in Group 1, 21 in Group 2).
• Data Provenance: "Prospective, two-arm, two-site, crossover randomized controlled and comparative study." Similar to Study 1, the country of origin is not explicitly stated. Given the context of FDA submission, it's typically assumed to be North America or Europe unless otherwise specified.

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

STUDY 1:

• Number of Experts: Not explicitly specified as a distinct number, but the study compared the Tuned self-test to "traditional audiometry performed by a professional" and "licensed audiologist." This implies at least one, if not multiple, qualified professionals.
• Qualifications of Experts: "Licensed audiologist" and "professional." No specific experience (e.g., "10 years of experience") is mentioned.

STUDY 2:

• Number of Experts: Not explicitly stated as a distinct number. The study compared self-fitting to "licensed professional fitting." This implies the involvement of one or more licensed professionals to perform the "professional fitting."
• Qualifications of Experts: "Licensed professional." No specific experience mentioned.

4. Adjudication method for the test set

The provided text does not mention any adjudication method for the test sets in either Study 1 or Study 2. The comparisons are direct between the device's output/self-fitting outcome and the professional's assessment/fitting outcome.

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

An MRMC comparative effectiveness study was not explicitly described in the provided text. The studies focus on comparing the self-fitting hearing aid's performance/user outcomes against traditional audiology methods, rather than assessing how human readers (e.g., radiologists, ophthalmologists) improve with AI assistance. The device is a self-fitting hearing aid, not an AI-powered diagnostic imaging tool that assists human readers.

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

Yes, in essence, standalone performance was assessed for the self-fitting capability.

• Study 1 directly compared the "Tuned self-test" (algorithm-driven self-assessment) against "traditional audiometry performed by a professional" for auditory thresholds. This can be considered a form of standalone evaluation for the audiometric threshold detection aspect of the device's algorithm.
• The "Intrisound™ Tuned Lumen® 155 Hearing Aid is a wireless, self-fitting air conduction hearing aid... customization through the Tuned Mobile Application. The Tuned Mobile Application aims to detect accurate auditory thresholds, partnering with a smart phone application to deliver user-customized sound through the Intrisound™ Tuned Lumen® 155 Hearing Aid. These thresholds are used to program the device using a proprietary algorithm." This describes the core standalone functionality of the device's self-fitting algorithm.

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

• Study 1: The ground truth for audiometric thresholds was established by traditional audiometry performed by a licensed professional (audiologist). For fitting parameters (NAL-NL2 targets, REAR), the ground truth was based on established audiology standards and professional fitting methods.
• Study 2: The ground truth for subjective outcomes was established using validated patient-reported outcome measures (PROMs) - COSI and IOI-HA questionnaires completed by the participants themselves, after using both self-fitting and professional fitting methods. This is a form of user-reported outcomes data. The "professional fitting" condition serves as a comparative reference for the self-fitting's effectiveness.

8. The sample size for the training set

The document does not specify the sample size for the training set used to develop the proprietary algorithm or the Tuned self-test. The studies described are performance validation/testing studies, not algorithm development studies.

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

Since the training set size or methodology is not detailed, the document does not provide information on how the ground truth for the training set was established.

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The All-Day Clear Slim hearing aids are intended for individuals 18 years or older with perceived mild to moderate hearing loss. The intended use of the All-Day Clear Slim hearing aids is to amplify and transmit sound to the ears and hereby compensate for hearing loss. The hearing aids must only be used by the intended person. They should not be used by any other person as they could damage hearing. The charging case is intended to charge the battery of the rechargeable hearing aids. The All-Day Clear App is intended for individuals 18 years or older, to set-up and/or adjust All-Day Clear Slim hearing aids through Android and Apple iOS smartphones.

The All-Day Clear hearing aids are intended for individuals 18 years or older with perceived mild to moderate hearing loss. The intended use of the All-Day Clear hearing aids is to amplify and transmit sound to the ears and hereby compensate for hearing loss. The hearing aids must only be used by the intended person. They should not be used by any other person as they could damage hearing. The charging case is intended to charge the battery of the rechargeable hearing aids. The All-Day Clear App is intended for individuals 18 years or older, to set-up and/or adjust All-Day Clear hearing aids through Android and Apple iOS smartphones.

The All-Day Clear Slim ADCS1 hearing aid and All-Day Clear ADC1 hearing aid are self-fitting air-conduction hearing aids. The ADCS1 and ADC1 hearing aids are nearly identical except for minor design differences. The hearing aid system consists of hearing aids for left and right ears, charging case, charging cable with USB-A and USB-C connector, wall plug, a set of eartips (small, medium, and large sizes), cleaning brush, carrying case (for ADCS1 hearing aids alone), and wax guards. The ADCS1 and ADC1 hearing aids are indicated for over-the-counter use.

The end user can self-fit the hearing aid by downloading the All-Day Clear App to their Android or Apple iOS device, pairing the hearing aids to the App, and following a series of guided onboarding steps:

• Instructions on how to wear the hearing aids
• Creation of a sound profile by listening to sample audio in which the user selects parameters for volume and sound clarity
• Selection of sound balance

Once the hearing aids have been set up with a sound profile, the App can continue to be used as a remote control of the hearing aids. For example, the end users can use the App to change the volume or mute the hearing aid microphones (together or independently), switch between different hearing aid sound modes, adjust the volume of a streamed signal, adjust equalizer and wind noise control, and read out the status of the hearing aid charge level.

The ADCS1 and ADC1 hearing aid system provides an alternative optional method of fitting the device by letting the end users purchase "In-Clinic Care Package", where they can have a licensed hearing care professional fit their hearing aids using professional fitting software called "All-Day Clear Fitting Software." All-Day Clear Fitting Software is a component of Sonova's TrueFit 5.3 or higher fitting software which can only be used by a licensed hearing care professional. In both scenarios, the end users can use the App as a remote control of the hearing aid.

Here's a breakdown of the acceptance criteria and study details based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set:
  • Clinical Study: 44 participants (enrolled). Due to early discontinuations and outlier exclusion, analysis for effectiveness endpoints was based on varying numbers:
    • APHAB: 40 participants (after excluding 2 outliers from the original 42 for Period 1 analysis).
    • QuickSiN: 40 participants (Period 1 data analysis).
  • Human Factors/Usability Study: 30 participants (15 patients, 15 caregivers).
• Data Provenance: Retrospective from clinical study performed with "HelloGO" hearing aid, which is stated to have identical hardware and almost identical firmware to the subject devices (ADCS1, ADC1). The human factors study was prospective, conducted specifically for the ADCS1/ADC1. The country of origin for the clinical study is not explicitly stated in the provided text.

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

• The clinical study did not involve AI assistance, therefore "ground truth" was established through direct measurement of human hearing abilities and perceptions using standardized audiological tests (APHAB and QuickSiN) with both self-fitted and professionally fitted devices.
• Professionally Fit Devices: Implies fitting by audiologists or hearing care professionals, but the specific number or qualifications of these professionals for establishing the "ground truth" (the professional fit as a comparator) are not detailed beyond "professional fitting method."

4. Adjudication Method for the Test Set

• Clinical Study (Effectiveness Endpoints): Not applicable in the sense of expert adjudication of a device's output. The study design involved direct comparison of patient-reported outcomes (APHAB) and objective speech-in-noise testing (QuickSiN) under two different fitting conditions (self-fit vs. professional fit). The "ground truth" for the benefit scores was derived directly from participant responses and test results.
• Human Factors/Usability Study: "Study staff systematically assessed device usage to identify problems that were encountered by participants, including use errors and close calls during participant performance." This suggests observation and recording of events, rather than a formal expert adjudication of discrete findings.

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 comparative effectiveness study was not done. This study focuses on the effectiveness of a self-fitting hearing aid compared to a professionally fitted one, not on AI assistance for human readers/clinicians.

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

• Yes, in a sense, the "self-fitting" method can be considered a standalone performance of the algorithm (as implemented in the app) plus the user's interaction, without a hearing care professional in the loop for the fitting process itself. The study compared this "self-fitted" performance to a "professionally fitted" performance.

7. The Type of Ground Truth Used

• Clinical Study (Effectiveness):
  • Patient-Reported Outcomes: Abbreviated Profile of Hearing Aid Benefit (APHAB) global benefit score.
  • Objective Audiological Measure: Quick Speech-in-Noise (QuickSiN) test benefit score.
  • The "ground truth" for comparison was the outcome achieved with a professionally derived fitting.
• Safety: Tabulation of adverse events and serious adverse events.
• Human Factors/Usability: Observed use errors and close calls in a simulated environment, and participant feedback.

8. The Sample Size for the Training Set

• The document does not explicitly mention a "training set" for the clinical study parameters. The study design is a comparative effectiveness study between two fitting methods (self-fit and professional fit) for the hearing aid itself. The "self-fitting algorithm" embedded in the app would have had its own development and possible internal training process, but details of this are not provided in the context of this FDA summary.
• The human factors study did not involve a training set; it was a usability validation.

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

• As a training set for the specific self-fitting algorithm is not detailed, the method for establishing its "ground truth" (e.g., what data it was trained on to achieve optimal fitting) is not provided in this document. The clinical study established ground truth for effectiveness comparison by using a professionally fitted condition as a benchmark.

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The Lexie Lumen Self-Fitting OTC Hearing Aid(s) with Lexie Application is a self-fitting air-conduction hearing aid, intended to amplify sound for individuals 18 years of age or older with perceived mild to moderate hearing impairment. The device is adjusted by the user to meet the user's hearing needs. The device is intended for use without the assistance of a hearing care professional.

The Lexie Lumen Self-Fitting OTC Hearing Aid(s) with Lexie Application is a self-fitting, air conduction hearing aid consisting of the IntriCon hardware, Lexie Software, Lexie Application and accessories supplied in the carton. The Lexie App is available on Android and iOS. The Lumen self-fitting OTC hearing aid is the only model applicable to this 510(k). The Lexie Lumen Self-Fitting OTC Hearing Aid(s) with Lexie Application is a behind the ear device that includes self-adjustable coupling by means of a slim tube and ear tip/dome. The hearing aids can be fine-tuned remotely by trained hearing experts, at the request of the user, in the Lexie contact center. The Lexie app receives custom remote settings as performed through the Lexie adjustment wizard and fitting portal (internet service).

Here's a breakdown of the acceptance criteria and the study details for the Lexie Lumen Self-Fitting OTC Hearing Aid(s) with Lexie Application, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Clinical Study:
  • Sample Size: 64 participants (32 in the Audiologist Fit (AF) group, 32 in the Self-Fit (SF) group).
  • Data Provenance: Prospective, Randomized Controlled Trial conducted at the University of Pretoria, Gauteng, South Africa.
• In-situ Hearing Test Accuracy Validation (separate study):
  • Sample Size: 45 participants (90 ears).
• Human Factors Testing:
  • Sample Size: 29 adult participants.
  • Data Provenance: Simulated-use session, likely within a controlled environment (e.g., laboratory).

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

• Clinical Study:
  • The "ground truth" for the Audiologist Fit (AF) group was established by audiologists who performed standard audiometric evaluations and fitted the hearing aids to match NAL-NL2 prescriptive targets. The text doesn't specify the exact number of audiologists, but refers to "the audiologist" (singular) in descriptions of procedures, implying at least one qualified audiologist was involved in the fitting and orientation for the AF group. The context of a university setting (University of Pretoria) suggests these would be qualified professionals.
  • For the in-situ hearing test validation, "the audiologist-performed audiometry" was used as a reference, again implying qualified audiologist(s).
• Human Factors Testing:
  • No specific experts are mentioned as establishing "ground truth" in the same way as the clinical study. Instead, the "effectiveness and accuracy of the tasks" were assessed by observing participants' performance during simulated use, implying assessment by human factors specialists or researchers.

4. Adjudication Method for the Test Set

• The clinical study was a randomized controlled trial (RCT) comparing two groups (SF vs. AF).
• No explicit "adjudication method" (like 2+1 or 3+1 for expert review) is mentioned for the outcomes of the clinical study, as the primary and secondary endpoints (APHAB, IOI-HA, QuickSIN, DIN) are quantitative measures.
• For the in-situ hearing test accuracy, performance (Mean Absolute Difference) was compared against "audiologist-performed audiometry," where the audiologist's results served as the reference.
• For Human Factors Testing, an "observer" evaluated task success, and a "semi-structured interview" was used for user perceptions.

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

• Yes, a comparative effectiveness study was done, comparing the Lexie Lumen in a self-fit (SF) condition against an audiologist-fit (AF) condition. This is a direct comparison of the device's performance with and without expert assistance in fitting.
• Effect Size of Human Readers Improve with AI vs. without AI assistance:
  • The study compares self-fitting (device with its AI/software-driven fitting strategy) to audiologist-fitting (human expert). It doesn't present an effect size of "human readers improve with AI vs. without AI assistance" in the context of interpretation of medical images.
  • Instead, it evaluates if the self-fitting strategy (which is AI/software-driven) is non-inferior to an audiologist's fitting. The results show that the SF group was equivalent or even slightly better in some aspects (background noise difficulty at 2 weeks, duration of use at 2 weeks) compared to the AF group, and overall achieved equivalence within the defined acceptance criteria for the primary and secondary endpoints. This implies that the device's self-fitting capability largely negates the need for a human professional's direct fitting intervention for achieving comparable outcomes for mild to moderate hearing loss.

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

• Yes, the "Self-Fit (SF) group" in the clinical study represents the standalone performance of the device's self-fitting algorithm without human-in-the-loop fitting assistance. Participants in this group were explicitly stated to "set up and manage the devices using the Lexie app, entirely without professional support." Any assistance sought in Phase II was through the Lexie online hearing experts, but the initial fitting and core performance were self-directed via the app's algorithm.

7. The Type of Ground Truth Used

• Clinical Study (Effectiveness):
  • The ground truth was established by comparison with best-practice audiological fitting (NAL-NL2 targets) performed by audiologists. The aim was to demonstrate non-inferiority or equivalence against this established clinical standard.
  • For the in-situ hearing test, the "Reference" was audiologist-performed audiometry.
• Safety:
  • "Ground truth" for safety was the occurrence and nature of Adverse Events (AE) and Serious Adverse Events (SAE), which are reportable objective events.
• Human Factors Testing:
  • "Ground truth" was the observational assessment of task completion and accuracy by study personnel, corroborated by user self-reports and satisfaction.
• Non-clinical Performance Testing:
  • "Ground truth" was defined by the acceptance criteria within the cited national and international consensus standards (e.g., IEC, ISO, ANSI, CTA), against which the device's physical and electrical properties were measured.

8. The Sample Size for the Training Set

• The document does not provide information on the sample size for the training set used to develop the Lexie self-fitting algorithm or its core software. This information is typically proprietary and not usually disclosed in a 510(k) summary, which focuses on validation rather than development.

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

• The document does not provide information on how the ground truth for the training set was established. The text only states that the fitting algorithm (Lexie Comfort) is "based on National Acoustics Laboratories' Non-Linear Version 2 (NAL-NL2), with additional adjustments aimed for a greater listening comfort." This implies that the NAL-NL2 prescriptive targets likely form a significant part of the foundational "ground truth" or reference for the algorithm's development, but details of specific training data and its ground truth are absent.

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The Eargo Self-Fitting Hearing Aids are intended to amplify and transmit sound to the ear and thereby compensate for perceived mild to moderate hearing impairment in individuals 18 years of age or older. They are adjusted by the user to meet the user's hearing needs. No pre-programming or hearing test is necessary. The product is intended to be used without the assistance of a hearing care professional.

The Eargo Self-Fitting Hearing Aid is a self-fitting air-conduction hearing aid system that incorporates wireless technology in its programming and use. The hearing aid system consists of a pair of earbud-style hearing aids (left and right), a charging case, and a companion mobile application (app) available for iOS (version 12 or later) and Android (version 7 or later) mobile devices. The hearing aids are designed to be virtually invisible, inserted completely and discreetly within the ear canal. Each hearing aid contains a microphone to allow for audio input, which is amplified by the hearing aid. The mobile app facilitates Eargo's proprietary self-fitting process using a combination of proprietary ultrasonic (for fitting) and Bluetooth Low Energy (BLE; for programming fitting settings) wireless communication. The mobile app also allows the user to control the hearing aids using proprietary ultrasonic wireless communication and enables firmware updates to the hearing aid system via BLE. App-based user controls include program and settings changes. In addition, each hearing aid contains an accelerometer sensor that allows for ondevice user control of the hearing aids. On-device user controls allow the user to make program changes without the mobile app. Each hearing aid contains a rechargeable Li-ion battery and is charged by the charging case that also functions as a carrying case. The charging case contains a single-cell Li-ion rechargeable battery, which charges the hearing aids via wireless (near-field inductive) charging when the hearing aids are correctly placed into the charging case.

Here's a breakdown of the acceptance criteria and the study details for the Eargo Self-Fitting Hearing Aids, based on the provided text:

Acceptance Criteria and Device Performance

The document doesn't explicitly present a single "Table of Acceptance Criteria" with numerical targets and direct "Reported Device Performance" for each criterion in the same way one might find for a pass/fail mechanical test. Instead, the acceptance criteria are embedded within descriptions of various tests, and the "reported device performance" is the successful conclusion (e.g., "Pass," "Comparable to predicate," "Acceptable usability and satisfaction").

However, I can extract the implicit acceptance criteria and the demonstrated performance where quantitative or qualitative measures are reported:

Study Details:

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

• Clinical Validation of Eargo's Sound Match Hearing Thresholds:

  • Test Set Sample Size: 100 subjects (76 with hearing loss, 24 normal hearing).
  • Data Provenance: Three geographically disparate U.S. sites (University of the Pacific - San Francisco and Stockton campuses). Data appears to be prospective, collected specifically for this validation.

• Clinical Verification of Eargo's Self-Fitting Approach:

  • Test Set Sample Size: 33 subjects.
  • Data Provenance: Center for Applied and Translational Sensory Science at the University of Minnesota, U.S. Data appears to be prospective, collected specifically for this clinical trial.

• Real-World Fit and Comfort / Real-World Safety:

  • Test Set Sample Size: 33 participants for Fit/Comfort; 31 participants for Safety.
  • Data Provenance: Real-world usage in the U.S. This appears to be prospective data collection.

• Real-World Evaluation of Satisfaction and Usability:

  • Test Set Sample Size: 255 subjects.
  • Data Provenance: Web-based survey of adults in the U.S. who have used Eargo devices for at least two months. This appears to be retrospective (surveying existing users).

• Human Factors Validation of Self-Fit Strategy:

  • Test Set Sample Size: 16 participants.
  • Data Provenance: U.S. setting for a summative usability test. This is prospective.

• Human Factors Validation of Device Labeling and Device Handling/Maintenance:

  • Test Set Sample Size: 24 participants.
  • Data Provenance: U.S. setting for human factors validation testing. This is prospective.

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

• Clinical Validation of Sound Match:

  • Ground Truth: "Audiometric thresholds obtained by an Audiologist in a sound-treated booth, following Audiology best practice methods (ABP)."
  • Experts: While the exact number of audiologists is not specified, it was conducted by "an Audiologist" (implying one per test administration) at the "University of the Pacific" which implies qualified personnel. The setup suggests multiple audiologists involved across the two campuses. Qualifications are implied by "Audiology best practice methods."

• Clinical Verification of Self-Fitting Approach:

  • Ground Truth: "Real Ear Aided Response (REAR) to NAL-NL2 targets... and other measures (APHAB, speech in noise, sound quality ratings) were compared against results from the same hearing aid fit by an audiologist following clinical best practice methods for fitting hearing aids."
  • Experts: "a research audiologist" at the "University of Minnesota" for the AUD-fit condition. This implies a single, qualified audiologist for all AUD-fit programming in this trial. Further expertise is implicitly built into the NAL-NL2 prescription targets and clinical best practices.

• Other studies (Usability, Safety, Satisfaction, Human Factors): Ground truth was established through participant feedback, observation of task completion, and adherence to established human factors methodologies rather than expert clinical interpretation of results. No external "experts" were explicitly mentioned for ground truth establishment beyond the study design and evaluation team.

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

• The document does not describe a formal adjudication method (like 2+1 or 3+1) for the clinical or human factors studies.
• Clinical Validation of Sound Match: Comparison was directly between two measurement methods (Eargo Sound Match vs. Audiologist Best Practice), with statistical analysis determining equivalence.
• Clinical Verification of Self-Fitting: Within-subject crossover design, comparing self-fit outcomes directly against audiologist-fit outcomes, with statistical analysis for non-inferiority/equivalence.
• Human Factors/Usability: Task success was observed and rated as successful, with difficulty, assistance, or failed/unable to complete. "No use errors" or "completed successfully by at least 80% of participants" were reported. The experimenter assisted only if asked, implying that "assistance" counted against independence.

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 Multi-Reader Multi-Case (MRMC) study was done for AI assistance. This device is a self-fitting hearing aid, not an AI-assisted diagnostic tool for human readers. The studies compare a self-fitting method to a professionally-fitted method, both involving a human user (the patient) directly.

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

• Yes, in the context of the device's self-fitting algorithm. The "Sound Match" feature is described as Eargo's "proprietary, app-based method for self-determining audiometric thresholds," where the "hearing aids act as the transducer, emitting tonal stimuli... The measured hearing thresholds are then used as the basis for fitting the appropriate gain profile(s)." This is the algorithm's direct measurement output.
  • The "Clinical Validation of Eargo's Sound Match Hearing Thresholds" directly assesses the accuracy of this algorithm's output (EargoA/EargoB thresholds) against audiologist-derived thresholds (ABP). This is essentially a standalone evaluation of the algorithm's ability to measure hearing thresholds.

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

• Clinical Validation of Sound Match: Expert Consensus / Standard of Care (audiometric thresholds measured by an audiologist following audiology best practice methods).
• Clinical Verification of Self-Fitting: Mixed ground truth:
  • Objective: NAL-NL2 prescriptive targets for REAR (an established audiological fitting formula).
  • Comparative Clinical Outcome: Audiologist-fit condition using clinical best practices for APHAB, speech in noise, and subjective sound quality.
• Usability/Human Factors: Observation of task completion based on pre-defined criteria, and user self-reported satisfaction/experience, aligned with established human factors validation methodologies.

8. The sample size for the training set

• The document does not provide specific information on the sample size for the training set used to develop the Eargo self-fitting algorithm or the Sound Match feature. It only describes the validation studies. The algorithm is described as "proprietary," indicating its development was internal to Eargo.

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

• The document does not explicitly describe how the ground truth for the training set was established. Given the proprietary nature of the self-fitting algorithm and Sound Match, this information would likely be confidential commercial information not typically disclosed in a 510(k) summary. However, it can be inferred that its development would have been based on established audiology principles and data, similar to the validation methods, but applied to a development dataset.

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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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