The Hearing Aid Feature is a software-only mobile medical application that is intended to be used with compatible wearable electronic products. The feature is intended to amplify sound for individuals 18 years of age or older with perceived mild to moderate hearing impairment. The Hearing Aid Feature utilizes a self-fitting strategy and is adjusted by the user to meet their hearing needs without the assistance of a hearing healthcare professional. The device is intended for Over-the-Counter use.

The Hearing Aid Feature (HAF) is a software-only device that is comprised of a pair of software modules which operate on two separate required products: (1) HAF iOS Application on a compatible iOS product, and (2) HAF software (i.e., firmware) on the Apple AirPods Pro 2. Refer to Figure I, middle and right, respectively, The AirPods Pro 2, formerly named AirPods Pro (2nd generation), supported this granting and are hereafter simply referred to as "AirPods Pro" in this document.

The HAF iOS Application guides users through the onboarding and setup process for the HAF. The process is self-guided by the user and includes step-by-step instructions and informational content (e.g. warnings, instructions for use). To initiate HAF setup, the user must select a saved audiogram from the iOS HealthKit.

Once the audiogram has been imported by the HAF, the feature will configure the amplification for the user's audiogram based upon Apple's proprietary fitting formula. Once the initial set-up is complete, users can listen with the HAF using the AirPods Pro and refine their settings. Fine tuning is facilitated by user controls on the iOS device that can adjust amplification, tone, and balance. A user can access the fine tuning settings at any time after setting up the HAF.

The HAF settings are transferred to the HAF Firmware Module on the AirPods Pro. The HAF Firmware Module utilizes the general purpose computing platform features of the AirPods Pro, including the microphone, speakers, amplifiers, and audio processing software, to process incoming sound and provide amplification at a specific frequency and gain based on the user's custom settings. The user's custom settings are stored on the HAF Firmware Module and will be available even when the AirPods Pro are not connected to the iOS device.

Acceptance Criteria and Device Performance for Apple's Hearing Aid Feature (HAF)

1. Table of Acceptance Criteria and Reported Device Performance

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

Bench/Non-Clinical Tests:

• Performance Testing (21 CFR 800.30(d) & (e)): No specific sample size (n) is provided, but the tests refer to "all test frequencies" and compliance with ANSI/ASA S3.22 or ANSI/CTA 2051:2017 clauses. This implies comprehensive testing across the specified parameters, rather than a limited sample.
• Human Factors Formative Testing: 39 subjects.
• Audiogram Input Risk and Mitigation Study: No specific sample size (n) for the study itself, but refers to the Hearing Test Feature (HTF) validation study dataset.

Clinical Study:

• Overall Clinical Study (HAF Self-Fit vs. Professionally-Fit): 118 total participants (59 in Self-Fit group, 59 in Professionally-Fit group for FAS/CCAS; 59 in Self-Fit, 58 in Professionally-Fit for PP analysis).
• Data Provenance: Prospective, non-significant risk study from three sites across the United States.

Supplemental Clinical Data (Apple Hearing Test Feature Validation):

• Comparison of HTF outputs to professionally derived audiograms: n = 202.
• Gain analysis for HAF with HTF vs. professionally-derived audiograms: n = 173 (subset with mild to moderate hearing loss from the n=202 dataset).

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

Bench/Non-Clinical Tests:

• Performance Testing: Ground truth is established by well-defined regulatory standards (21 CFR 800.30) and industry standards (ANSI/ASA S3.22, ANSI/CTA 2051:2017). Expertise is inherent in the test methodologies themselves.
• Human Factors Formative Testing: No explicitly stated "experts" establishing ground truth in the context of diagnostic accuracy. The testing assessed use-related risks, and findings led to software design modifications.
• Audiogram Input Risk and Mitigation Study: No explicitly stated "experts" for ground truth on this specific study, but the study for the Hearing Test Feature Validation (see below) involved professional audiograms which would have been established by qualified audiologists.

Clinical Study (HAF Self-Fit vs. Professionally-Fit):

• Ground Truth for Professional-Fit (PF) Group: The "Professionally-Fit" group had their hearing aids fitted by an audiologist and underwent an optional audiologist fine-tuning session. This implies a number of audiologists (not specified but plural) provided this professional fit, thus establishing a "ground truth" reference for professional care. The study design intrinsically compares the self-fit approach to professional audiologist care, using the latter as the benchmark for a successful fit in terms of patient-perceived benefit.

Supplemental Clinical Data (Apple Hearing Test Feature Validation):

• Comparison to Professionally Derived Audiograms: These would have been established by qualified hearing healthcare professionals, such as audiologists. The exact number of such professionals establishing these audiograms for the 202 subjects is not specified but the term "professionally derived" implies expertise.

4. Adjudication Method for the Test Set

Bench/Non-Clinical Tests:

• Performance Testing: Not applicable; compliance is determined by direct measurement against pre-defined numerical thresholds in regulatory and industry standards.
• Human Factors Formative Testing: Not applicable; the output is identification of use-related risks and subsequent design modifications.
• Audiogram Input Risk and Mitigation Study: Not applicable.

Clinical Study (HAF Self-Fit vs. Professionally-Fit):

• Primary Endpoint (IOI-HA score): Not applicable in the sense of expert adjudication of a diagnostic finding. The primary outcome was a patient-reported outcome measure (IOI-HA score), a subjective assessment collected directly from participants. The comparison was statistical (non-inferiority margin) between the two groups.
• Objective Measures (QuickSIN, REM): These are objective measurements and do not require adjudication.

Supplemental Clinical Data (Apple Hearing Test Feature Validation):

• Audiogram Comparison & Gain Analysis: Not applicable. The comparison was quantitative (pure-tone average, gain differences) between HTF-derived and professionally-derived audiograms.

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

• No, a traditional MRMC comparative effectiveness study, as typically seen in diagnostic imaging where multiple readers interpret cases with and without AI assistance, was not performed for the core Hearing Aid Feature.
• Instead, a clinical study compared two groups:
  • Self-Fit (SF): Users applying the HAF's self-fitting algorithm.
  • Professionally-Fit (PF): Users whose devices were fitted by an audiologist using the NAL-NL2 formula.
• This study evaluated the effectiveness of the HAF's self-fitting approach directly against professional care by assessing patient-reported outcomes (IOI-HA) and objective measures (QuickSIN, REM).
• Effect Size of Human Readers Improve with AI vs without AI assistance: This metric is not applicable as the study design was a comparison of a self-fitting AI system against professional human fitting, not a study of human readers improving with AI assistance. The study concluded that the HAF Self-Fit group achieved non-inferior perceived benefit (IOI-HA scores) compared to the Professionally-Fit group, indicating equivalent patient outcomes without the direct involvement of a hearing healthcare professional in the fitting process.

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

• Yes, a standalone study was inherently performed to assess the performance of the HAF's self-fitting algorithm.
• The "Self-Fit (SF)" group in the clinical study directly represents the standalone performance of the algorithm. These users utilized the HAF's automatic fitting algorithm and then could adjust amplification, tone, and balance themselves. The device's performance, as measured by IOI-HA scores, QuickSIN, and REM, was attributed to this self-fitting strategy.
• The comparison to the "Professionally-Fit (PF)" group served as a benchmark for what a human expert (audiologist) would achieve.
• Therefore, the clinical study's SF arm is a direct measure of the algorithm's standalone performance in a real-world setting.

7. Type of Ground Truth Used

Bench/Non-Clinical Tests:

• Regulatory and Industry Standards: Ground truth is defined by explicit numerical thresholds and methodologies prescribed by 21 CFR 800.30 and ANSI/ASA/CTA standards.
• Human Factors: "Ground truth" is the identification of potential use errors and associated risks, which is derived from observing user interactions and conducting risk analysis.

Clinical Study (HAF Self-Fit vs. Professionally-Fit):

• Expert Consensus / Professional Practice: The "Professionally-Fit" group, whose devices were fitted by audiologists using a standard clinical fitting formula (NAL-NL2), served as the gold standard or ground truth for best clinical practice in hearing aid fitting. The HAF's performance was evaluated against this professional benchmark.
• Patient-Reported Outcomes (IOI-HA): The primary ground truth for effectiveness was the subjective perception of benefit, satisfaction, and quality of life as reported by the patients themselves via the IOI-HA questionnaire.
• Objective Outcomes Data (QuickSIN, REM): These objective functional measures also served as ground truth regarding speech intelligibility and actual gain.

Supplemental Clinical Data (Apple Hearing Test Feature Validation):

• Expert Consensus / Professional Practice: The comparison was made against "professionally derived audiograms," implying that these audiograms, established by trained hearing healthcare professionals, served as the ground truth.

8. Sample Size for the Training Set

The document does not explicitly state the sample size for the training set used to develop Apple's proprietary fitting formula within the HAF. The description only refers to the clinical study as establishing safety and effectiveness, and the HAF's fitting formula is described as "Apple's proprietary fitting formula." This formula would have been developed using a separate dataset prior to the validation study.

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

Since the training set size and characteristics are not provided, the method for establishing its ground truth is also not explicitly stated in this document.

However, based on the nature of hearing aid fitting algorithms and the validation study design, it is highly probable that the proprietary fitting formula was developed and refined using:

• Large datasets of audiogram data: Likely anonymized audiograms from various sources, potentially including those collected by Apple's own Hearing Test Feature over time or from research collaborations.
• Patient-reported outcomes data: To correlate objective audiometric data with subjective patient benefit and preference.
• Expert knowledge/models: Incorporating established audiological principles, validated fitting targets (e.g., NAL-NL2, DSL v5), and clinical experience synthesized into an algorithmic form.
• Iterative development and testing: The "proprietary fitting formula" would have undergone extensive internal testing, likely including simulations and pilot studies with real users, where the "ground truth" would be established by comparing algorithm outputs to professional recommendations or patient preferences.

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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 Lumen® 155-SF self-fitting, wireless air conduction 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. The device is intended for over-the-counter sales without the assistance of a hearing health 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 Lumen 155-SF self-fitting hearing aid(s) with Sentibo application is a self-fitting wireless air conduction Behind-The-Ear (BTE) hearing aid consisting of the Intricon hardware and Sentibo software to be used on an Apple mobile device (mobile device not included) including wired lightning connector Apple EarPods for the assessment (not included) designed for a single user. The Sentibo app is available only on iOS. The Lumen 155-SF self-fitting OTC hearing aid(s) with Sentibo application is a behind the ear device that includes self-adjustable coupling by means of a slim tube and ear tip/open dome. The hearing aids can be fine-tuned by the user or remotely at the request of the user via the use of QR codes. Once the hearing aids are switched on, the software (Sentibo app) is required for the initial set-up, which is done via the smart phone and requires Apple EarPods with lightning connector to complete (not included). The Sentibo self-fitting software allows the consumer to self-select a hearing profile from a list of options by listening to digitized speech embedded in the software while scrolling through the hearing profiles in real-time through the Apple EarPods. After the setting is selected, the settings can be transferred from the smart phone to the hearing aid directly, though direct audio streaming from the smart phone to the hearing aid is unsupported with the Lumen 155-SF firmware. All Sentibo settings are stored in the application itself, and no internet service is required to perform the self-fitting. The Sentibo application provides 24 predefined options. At the conclusion of the assessment, the software will program hearing aids wirelessly and the user will wear the hearing aids per normal use. The smartphone app will function as a software accessory, allowing the user to make minor adjustments to the hearing aids. The hearing aid is intended to be used with the Sentibo App and to be worn and removed daily by the end user.

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

Acceptance Criteria and Reported Device Performance

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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:

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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

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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

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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:

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