Smartphone-based audiometric test for screening hearing loss in the elderly

Reference equivalent threshold sound pressure levels for Apple EarPods

Reference equivalent threshold sound pressure levels (RETSPLs) are used when calibrating audiometric equipment to a hearing threshold level of zero at various frequencies. To the best of the authors' knowledge, the RETSPLs for Apple EarPods (MB770G) have not been reported, and so this study aimed to measure them. The hearing thresholds of 36 normal-hearing subjects (72 ears) were measured at 250, 500, 1000, 2000, 4000, and 8000 Hz, with the measurements being performed twice in 33 subjects (66 ears) for evaluating the test-retest reliability. This study provides Apple EarPod RETSPLs and shows significant Pearson's correlations (p < 0.001) with no significant Wilcoxon signed-rank test differences (p > 0.01), which confirm the test reliability.

Accuracy of Mobile-Based Audiometry in the Evaluation of Hearing Loss in Quiet and Noisy Environments

Objectives

(1) To compare the accuracy of 2 previously validated mobile-based hearing tests in determining pure tone thresholds and screening for hearing loss. (2) To determine the accuracy of mobile audiometry in noisy environments through noise reduction strategies.

Study Design

Prospective clinical study.

Setting

Tertiary hospital.

Subjects and Methods

Thirty-three adults with or without hearing loss were tested (mean age, 49.7 years; women, 42.4%). Air conduction thresholds measured as pure tone average and at individual frequencies were assessed by conventional audiogram and by 2 audiometric applications (consumer and professional) on a tablet device. Mobile audiometry was performed in a quiet sound booth and in a noisy sound booth (50 dB of background noise) through active and passive noise reduction strategies.

Results

On average, 91.1% (95% confidence interval [95% CI], 89.1%-93.2%) and 95.8% (95% CI, 93.5%-97.1%) of the threshold values obtained in a quiet sound booth with the consumer and professional applications, respectively, were within 10 dB of the corresponding audiogram thresholds, as compared with 86.5% (95% CI, 82.6%-88.5%) and 91.3% (95% CI, 88.5%-92.8%) in a noisy sound booth through noise cancellation. When screening for at least moderate hearing loss (pure tone average >40 dB HL), the consumer application showed a sensitivity and specificity of 87.5% and 95.9%, respectively, and the professional application, 100% and 95.9%. Overall, patients preferred mobile audiometry over conventional audiograms.

Conclusion

Mobile audiometry can correctly estimate pure tone thresholds and screen for moderate hearing loss. Noise reduction strategies in mobile audiometry provide a portable effective solution for hearing assessments outside clinical settings.

Validated Smartphone-Based Apps for Ear and Hearing Assessments: A Review

BACKGROUND

An estimated 360 million people have a disabling hearing impairment globally, the vast majority of whom live in low- and middle-income countries (LMICs). Early identification through screening is important to negate the negative effects of untreated hearing impairment. Substantial barriers exist in screening for hearing impairment in LMICs, such as the requirement for skilled hearing health care professionals and prohibitively expensive specialist equipment to measure hearing. These challenges may be overcome through utilization of increasingly available smartphone app technologies for ear and hearing assessments that are easy to use by unskilled professionals.

OBJECTIVE

Our objective was to identify and compare available apps for ear and hearing assessments and consider the incorporation of such apps into hearing screening programs.

METHODS

In July 2015, the commercial app stores Google Play and Apple App Store were searched to identify apps for ear and hearing assessments. Thereafter, six databases (EMBASE, MEDLINE, Global Health, Web of Science, CINAHL, and mHealth Evidence) were searched to assess which of the apps identified in the commercial review had been validated against gold standard measures. A comparison was made between validated apps.

RESULTS

App store search queries returned 30 apps that could be used for ear and hearing assessments, the majority of which are for performing audiometry. The literature search identified 11 eligible validity studies that examined 6 different apps. uHear, an app for self-administered audiometry, was validated in the highest number of peer reviewed studies against gold standard pure tone audiometry (n=5). However, the accuracy of uHear varied across these studies.

CONCLUSIONS

Very few of the available apps have been validated in peer-reviewed studies. Of the apps that have been validated, further independent research is required to fully understand their accuracy at detecting ear and hearing conditions.

Application-Based Hearing Screening in the Elderly Population

Objectives:

The effects of age-related hearing loss are severe. Early detection is essential for maximum benefit. However, most hearing-impaired adults delay obtaining treatment. Diagnostic hearing testing at an appropriate facility is impractical, and new methods for screening audiometry aim to provide easy access for patients and reliable outcomes. The purpose of this study was to examine the accuracy of application-based hearing screening in an elderly population.

Methods:

The uHear application was downloaded to an iPad. Application-based hearing screening was performed in a non-soundproofed quiet room, and subsequently all participants underwent full diagnostic audiometry in a soundproof booth.

Results:

Sixty patients were recruited and completed both tests. Significant differences were observed between the hearing results obtained with the application and the standard audiogram at all frequencies and in both ears. Following subtraction of a constant factor of 25 dB from the application-based results in order to compensate for ambient noise, no significant differences in pure tone average were found between the 2 methods.

Conclusions:

The uHear application is inaccurate in assessing hearing thresholds for screening in the elderly. However, when site-specifically corrected, the uHear application may be used as a screening tool for hearing loss in an elderly population.

Hearing Tests on Mobile Devices: Evaluation of the Reference Sound Level by Means of Biological Calibration

Background

Hearing tests carried out in home setting by means of mobile devices require previous calibration of the reference sound level. Mobile devices with bundled headphones create a possibility of applying the predefined level for a particular model as an alternative to calibrating each device separately.

Objective

The objective of this study was to determine the reference sound level for sets composed of a mobile device and bundled headphones.

Methods

Reference sound levels for Android-based mobile devices were determined using an open access mobile phone app by means of biological calibration, that is, in relation to the normal-hearing threshold. The examinations were conducted in 2 groups: an uncontrolled and a controlled one. In the uncontrolled group, the fully automated self-measurements were carried out in home conditions by 18- to 35-year-old subjects, without prior hearing problems, recruited online. Calibration was conducted as a preliminary step in preparation for further examination. In the controlled group, audiologist-assisted examinations were performed in a sound booth, on normal-hearing subjects verified through pure-tone audiometry, recruited offline from among the workers and patients of the clinic. In both the groups, the reference sound levels were determined on a subject’s mobile device using the Bekesy audiometry. The reference sound levels were compared between the groups. Intramodel and intermodel analyses were carried out as well.

Results

In the uncontrolled group, 8988 calibrations were conducted on 8620 different devices representing 2040 models. In the controlled group, 158 calibrations (test and retest) were conducted on 79 devices representing 50 models. Result analysis was performed for 10 most frequently used models in both the groups. The difference in reference sound levels between uncontrolled and controlled groups was 1.50 dB (SD 4.42). The mean SD of the reference sound level determined for devices within the same model was 4.03 dB (95% CI 3.93-4.11). Statistically significant differences were found across models.

Conclusions

Reference sound levels determined in the uncontrolled group are comparable to the values obtained in the controlled group. This validates the use of biological calibration in the uncontrolled group for determining the predefined reference sound level for new devices. Moreover, due to a relatively small deviation of the reference sound level for devices of the same model, it is feasible to conduct hearing screening on devices calibrated with the predefined reference sound level.

Validation of a Self-Administered Audiometry Application: An Equivalence Study

OBJECTIVES/HYPOTHESIS

To compare hearing measurements made at home using self-administered audiometric software against audiological tests performed on the same subjects in a clinical setting

STUDY DESIGN

Prospective, crossover equivalence study

METHODS

In experiment 1, adults with varying degrees of hearing loss (N = 19) performed air-conduction audiometry, frequency discrimination, and speech recognition in noise testing twice at home with an automated tablet application and twice in sound-treated clinical booths with an audiologist. The accuracy and reliability of computer-guided home hearing tests were compared to audiologist administered tests. In experiment 2, the reliability and accuracy of pure-tone audiometric results were examined in a separate cohort across a variety of clinical settings (N = 21).

RESULTS

Remote, automated audiograms were statistically equivalent to manual, clinic-based testing from 500 to 8,000 Hz (P ≤ .02); however, 250 Hz thresholds were elevated when collected at home. Remote and sound-treated booth testing of frequency discrimination and speech recognition thresholds were equivalent (P ≤ 5 × 10(-5) ). In the second experiment, remote testing was equivalent to manual sound-booth testing from 500 to 8,000 Hz (P ≤ .02) for a different cohort who received clinic-based testing in a variety of settings.

CONCLUSION

These data provide a proof of concept that several self-administered, automated hearing measurements are statistically equivalent to manual measurements made by an audiologist in the clinic. The demonstration of statistical equivalency for these basic behavioral hearing tests points toward the eventual feasibility of monitoring progressive or fluctuant hearing disorders outside of the clinic to increase the efficiency of clinical information collection.

LEVEL OF EVIDENCE

2b. Laryngoscope, 126:2382-2388, 2016.