Smartphone Based Audiometric Test for Confirming the Level of Hearing; Is It Useable in Underserved Areas?

The Hearing Test App for Android Devices: Distinctive Features of Pure-Tone Audiometry Performed on Mobile Devices

The popularity of mobile devices, combined with advances in electronic design and internet technology, has enabled home-based hearing tests in recent years. The purpose of this article is to highlight the distinctive aspects of pure-tone audiometry performed on a mobile device by means of the Hearing Test app for Android devices. The first version of this app was released a decade ago, and since then the app has been systematically improved, which required addressing many issues common to the majority of mobile apps for hearing testing. The article discusses techniques for mobile device calibration, outlines the testing procedure and how it differs from traditional pure-tone audiometry, explores the potential for bone conduction testing, and provides considerations for interpreting mobile audiometry including test duration and background noise. The article concludes by detailing clinically relevant aspects requiring special attention during testing and interpretation of results which are of substantial value to the hundreds of thousands of active users of the Hearing Test app worldwide, as well as to users of other hearing test apps.

Mobile audiometry for hearing threshold assessment: A systematic review and meta-analysis

OBJECTIVES

Technological advancements in mobile audiometry (MA) have enabled hearing assessment using tablets and smartphones. This systematic review (PROSPERO ID: CRD42021274761) aimed to identify MA options available to health providers, assess their accuracy in measuring hearing thresholds, and explore factors that might influence their accuracy.

DESIGN AND SETTING

A systematic search of online databases including PubMed, Embase, Cochrane, Evidence Search and Dynamed was conducted on 13th December 2021, and repeated on 30th October 2022, using appropriate Medical Subject Headings (MeSH) terms. Eligible studies reported the use of MA to determine hearing thresholds and compared results to conventional pure-tone audiometry (CA). Studies investigating MA for hearing screening (i.e. reporting just pass/fail) were ineligible for inclusion. Two authors independently reviewed studies, extracted data, and assessed methodological quality and risk of bias using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool.

PARTICIPANTS

Adults and children, with and without diagnosis of hearing impairment.

MAIN OUTCOME MEASURES

A meta-analysis was performed to obtain the mean difference between thresholds measured using MA and CA in dB HL.

RESULTS

Searches returned 858 articles. After systematic review, 17 articles including 1032 participants were analysed. The most used software application was ShoeboxTM (6/17) followed by Hearing TestTM (3/17), then HearTestTM (2/17). Tablet computers were used in ten studies, smartphones in six, and a computer in one. The mean difference between MA and CA thresholds was 1.36 dB (95% CI, 0.07-2.66, p = 0.04). Significant differences between mobile audiometry (MA) and conventional audiometry (CA) thresholds were observed in thresholds measured at 500Hz, in children, when MA was conducted in a sound booth, and when MA was self-administered. However, these differences did not exceed the clinically significant threshold of 10 decibels (dB). Included studies exhibited high levels of heterogeneity, high risk of bias and low concerns about applicability.

CONCLUSIONS

MA compares favourably to CA in measuring hearing thresholds and has role in providing access to hearing assessment in situations where CA is not available or feasible. Future studies should prioritize the integration of pure-tone threshold assessment with additional tests, such as Speech Recognition and Digits-in-Noise, for a more rounded evaluation of hearing ability, assesses acceptability and feasibility, and the cost-effectiveness of MA in non-specialist settings.

Burden, determinants, consequences and care of multimorbidity in rural and urbanising Telangana, India: protocol for a mixed-methods study within the APCAPS cohort

INTRODUCTION

The epidemiological and demographic transitions are leading to a rising burden of multimorbidity (co-occurrence of two or more chronic conditions) worldwide. Evidence on the burden, determinants, consequences and care of multimorbidity in rural and urbanising India is limited, partly due to a lack of longitudinal and objectively measured data on chronic health conditions. We will conduct a mixed-methods study nested in the prospective Andhra Pradesh Children and Parents' Study (APCAPS) cohort to develop a data resource for understanding the epidemiology of multimorbidity in rural and urbanising India and developing interventions to improve the prevention and care of multimorbidity.

METHODS AND ANALYSIS

We aim to recruit 2100 APCAPS cohort members aged 45+ who have clinical and lifestyle data collected during a previous cohort follow-up (2010-2012). We will screen for locally prevalent non-communicable, infectious and mental health conditions, alongside cognitive impairments, disabilities and frailty, using a combination of self-reported clinical diagnosis, symptom-based questionnaires, physical examinations and biochemical assays. We will conduct in-depth interviews with people with varying multimorbidity clusters, their informal carers and local healthcare providers. Deidentified data will be made available to external researchers.

ETHICS AND DISSEMINATION

The study has received approval from the ethics committees of the National Institute of Nutrition and Indian Institute of Public Health Hyderabad, India and the London School of Hygiene and Tropical Medicine, UK. Meta-data and data collection instruments will be published on the APCAPS website alongside details of existing APCAPS data and the data access process (www.lshtm.ac.uk/research/centres-projects-groups/apcaps).

Self-assessment of bone conduction hearing threshold using mobile audiometry: comparison with pure tone audiometry

OBJECTIVE

The aim of the research was to evaluate the feasibility of measuring the bone conduction hearing threshold using self-administered mobile audiometry.

DESIGN

A single-centre, closed, cross-over trial was carried out on patients from the ENT Department. A mobile-based, self-administered, audiologist-assisted assessment of the bone conduction hearing threshold was carried out by means of the open-access, freeware app Hearing Test using two types of bone conduction headphones: professional B71 bone transducer and commercially available AfterShokz Openmove open-ear headphones.

STUDY SAMPLE

Seventy-seven ears.

RESULTS

A test-retest examination revealed the lowest standard deviation for open-ear headphones at 3.33 dB (95% CI 2.92-3.79). When compared with pure tone audiometry, the intraclass correlations of 0.95 (95% CI 0.94-0.96) and 0.90 (95% CI 0.88-0.92) were obtained for the bone transducer and for the open-ear headphones, indicating excellent and good reliability, respectively. However, the regression slope of 0.67 was found for the air-bone gap when using open ear headphones, which was significantly different from 1 (p < 0.001).

CONCLUSIONS

Open-ear headphones provide an alternative for estimating bone conduction once the air-bone gap has been adjusted by a factor of 1/0.6 7 ≅1.5. They demonstrate improved reproducibility over the bone transducer and are much easier to use with a mobile device. Trial Registration: Wroclaw Medical University, Science Support Centre, BW60/2020.

Optimization of the Speech Test Material in a Group of Hearing Impaired Subjects: A Feasibility Study for Multilingual Digit Triplet Test Development

Background: The development of the global digit-in-noise test requires optimization of each language version on a group of normal-hearing native-speakers. An alternative solution may be an adaptive optimization during ongoing tests in a group of subjects with unknown hearing impairments. The objective of the research was to compare the optimization results between these groups. Methods: Digit triplets consisting of three pseudo-randomly selected digits were presented in speech-shaped noise at various signal-to-noise ratios (SNRs), according to the protocol of the final speech test. Digit-specific and position-specific speech reception thresholds (SRTs) were determined and compared between groups. Results: The study sample consisted of 82 subjects, 26 normal-hearing subjects and 56 patients with diverse hearing disorders. Statistically significant differences in digit-specific SRTs between the control and the investigated group were obtained for three digits in continuous noise (digits 0, 4, 6; p-value of 0.04, 0.03, 0.05) and two in modulated noise (digits 1 and 6; p-value of 0.05 and 0.01). An analysis including only ears with SRTs within the range of the normal hearing control group showed no statistically significant differences between digits. Conclusion: Optimization of speech material can be carried out in a group of subjects with unknown hearing impairments, provided the ears with scores outside normal range are rejected.

Smartphone-Based Applications to Detect Hearing Loss: A Review of Current Technology

BACKGROUND/OBJECTIVES

Age-related hearing loss (ARHL) is a widely prevalent yet manageable condition that has been linked to neurocognitive and psychiatric comorbidities. Multiple barriers hinder older individuals from being diagnosed with ARHL through pure-tone audiometry. This is especially true during the COVID-19 pandemic, which has resulted in the closure of many outpatient audiology and otolaryngology offices. Smartphone-based hearing assessment apps may overcome these challenges by enabling patients to remotely self-administer their own hearing examination. The objective of this review is to provide an up-to-date overview of current mobile health applications (apps) that claim to assess hearing.

DESIGN

Narrative review.

MEASUREMENTS

The Apple App Store and Google Play Store were queried for apps that claim to assess hearing. Relevant apps were downloaded and used to conduct a mock hearing assessment. Names of included apps were searched on four literature databases (PubMed/MEDLINE, EMBASE, Cochrane Library, and CINAHL) to determine which apps had been validated against gold standard methods.

RESULTS

App store searches identified 44 unique apps. Apps differed with respect to the type of test offered (e.g., hearing threshold test), cost, strategies to reduce ambient noise, test output (quantitative vs qualitative results), and options to export results. Validation studies were identified for seven apps.

CONCLUSION

Given their low cost and relative accessibility, smartphone-based hearing apps may facilitate screening for ARHL, particularly in the setting of limitations on in-person medical care due to COVID-19. However, app features vary widely, few apps have been validated, and user-centered designs for older adults are largely lacking. Further research and validation efforts are necessary to determine whether smartphone-based hearing assessments are a feasible and accurate screening tool for ARHL. Key Points Age-related hearing loss is a prevalent yet undertreated condition among older adults. Why Does this Paper Matter?     Smartphone-based hearing test apps may facilitate remote screening for hearing loss, but limitations surrounding app validation, usability, equipment calibration, and data security should be addressed.

Worldwide Prevalence of Hearing Loss Among Smartphone Users: Cross-Sectional Study Using a Mobile-Based App

Background

In addition to the aging process, risk factors for hearing loss in adults include, among others, exposure to noise, use of ototoxic drugs, genetics, and limited access to medical care. Differences in exposure to these factors are bound to be reflected in the prevalence of hearing loss. Assessment of hearing loss can easily be carried out on a large scale and at low cost using mobile apps.

Objective

This study aimed to conduct a worldwide assessment of the differences in hearing loss prevalence between countries in a group of mobile device users.

Methods

Hearing tests were conducted using the open-access Android-based mobile app Hearing Test. The app is available free of charge in the Google Play store, provided that consent to the use of the results for scientific purposes is given. This study included hearing tests carried out on device models supported by the app with bundled headphones in the set. Calibration factors for supported models were determined using the biological method. The tests consisted of self-determining the quietest audible tone in the frequency range from 250 Hz to 8 kHz by adjusting its intensity using the buttons. The ambient noise level was optionally monitored using a built-in microphone. Following the test, the user could compare his hearing threshold against age norms by providing his or her age. The user's location was identified based on the phone’s IP address.

Results

From November 23, 2016 to November 22, 2019, 733,716 hearing tests were conducted on 236,716 mobile devices across 212 countries. After rejecting the tests that were incomplete, performed with disconnected headphones, not meeting the time criterion, repeated by the same user, or carried out regularly on one device, 116,733 of 733,716 tests (15.9%) were qualified for further analysis. The prevalence of hearing loss, defined as the average threshold at frequencies 0.5 kHz, 1 kHz, 2 kHz, and 4 kHz above 25 dB HL in the better ear, was calculated at 15.6% (95% CI 15.4-15.8). Statistically significant differences were found between countries (P<.001), with the highest prevalences for Bangladesh, Pakistan, and India (>28%) and the lowest prevalences for Taiwan, Finland, and South Korea (<11%).

Conclusions

Hearing thresholds measured by means of mobile devices were congruent with the literature data on worldwide hearing loss prevalence. Uniform recruitment criteria simplify the comparison of the hearing loss prevalence across countries. Hearing testing on mobile devices may be a valid tool in epidemiological studies carried out on a large scale.

Validity of hearing screening using hearTest smartphone-based audiometry: performance evaluation of different response modes

Objective: To investigate the validity of hearing screening with hearTest smartphone-based audiometry and to specify test duration addressing the two response modes and hearing loss criteria.Design: A diagnostic accuracy study comparing hearing screening with conventional audiometry.Study sample: Three hundred and forty individuals, aged between 5-92 years.Results: Of the 340 participants, 301 undertook all test procedures (273 adults and 28 children). Sensitivity and specificity were >90% for hearTest hearing screening to identify disabling hearing loss for both response modes with adults and children. We found similar sensitivity in identifying any level of hearing loss for both response modes in children, with specificity >80%, and for the self-test mode in adults. Low specificity was observed when identifying any level of hearing loss in adults using the test-operator mode. In adults, there was a significant difference between test duration for the test-operator and self-test modes.Conclusion: Hearing screening using hearTest smartphone-based audiometry is accurate for the identification of both disabling hearing loss and any level of hearing loss in adults and children in the self-test response mode. The test-operator mode is also an option for children; however, it does not provide good accuracy in identifying mild level of hearing loss in adults.

Evaluation of Hearing Thresholds by Using a Mobile Application in Children with Otitis Media with Effusion

Objective: Otitis media with effusion (OME) is the most common cause of hearing loss in children. Early diagnosis is important as hearing loss affects speech and language development in children. The aim of this study was to compare conventional audiometry with the Android mobile operating system application Hearing TestTM in the evaluation of hearing thresholds in children with OME and to determine the accuracy and reliability of the mobile application. Design and Study Sample: Fifty school-age children aged between 5 and 15 years with OME in at least 1 ear were included in the study. First, hearing thresholds were obtained by conventional audiometric methods and the degree of hearing loss was determined. Then, the hearing thresholds of the patients were measured using the smartphone-based Hearing TestTM application. The data were compared using Cohen’s kappa analysis. Results: OME was detected in 88 ears. There was no statistically significant correlation between the hearing threshold results obtained with the mobile phone and conventional audiometry at 500, 1,000, 2,000, and 4,000 Hz. Conclusion: The Android mobile phone application Hearing TestTM (version 1.1.3) is not an appropriate screening test to detect hearing loss in children with OME.

A Mobile Phone-Based Approach for Hearing Screening of School-Age Children: Cross-Sectional Validation Study

Background

Pure-tone screening (PTS) is considered as the gold standard for hearing screening programs in school-age children. Mobile devices, such as mobile phones, have the potential for audiometric testing.

Objective

This study aimed to demonstrate a new approach to rapidly screen hearing status and provide stratified test values, using a smartphone-based hearing screening app, for each screened ear of school-age children.

Method

This was a prospective cohort study design. The proposed smartphone-based screening method and a standard sound-treated booth with PTS were used to assess 85 school-age children (170 ears). Sound-treated PTS involved applying 4 test tones to each tested ear: 500 Hz at 25 dB and 1000 Hz, 2000 Hz, and 4000 Hz at 20 dB. The results were classified as pass (normal hearing in the ear) or fail (possible hearing impairment). The proposed smartphone-based screening employs 20 stratified hearing scales. Thresholds were compared with those of pure-tone average (PTA).

Results

A total of 85 subjects (170 ears), including 38 males and 47 females, aged between 11 and 12 years with a mean (SD) of 11 (0.5) years, participated in the trial. Both screening methods produced comparable pass and fail results (pass in 168 ears and fail in 2 ears). The smartphone-based screening detected moderate or worse hearing loss (average PTA>25 dB) accurately. Both the sensitivity and specificity of the smartphone-based screening method were calculated at 100%.

Conclusions

The results of the proposed smartphone-based self-hearing test demonstrated high concordance with conventional PTS in a sound-treated booth. Our results suggested the potential use of the proposed smartphone-based hearing screening in a school-age population.

Automated Smartphone Audiometry: A Preliminary Validation of a Bone-Conduction Threshold Test App

Objective:

To develop and validate an automated smartphone app that determines bone-conduction pure-tone thresholds.

Methods:

A novel app, called EarBone, was developed as an automated test to determine best-cochlea pure-tone bone-conduction thresholds using a smartphone driving a professional-grade bone oscillator. Adult, English-speaking patients who were undergoing audiometric assessment by audiologists at an academic health system as part of their prescribed care were invited to use the EarBone app. Best-ear bone-conduction thresholds determined by the app and the gold standard audiologist were compared.

Results:

Forty subjects with varied hearing thresholds were tested. Sixty-one percent of app-determined thresholds were within 5 dB of audiologist-determined thresholds, and 79% were within 10 dB. Nearly all subjects required assistance with placing the bone oscillator on their mastoid.

Conclusion:

Best-cochlea bone-conduction thresholds determined by the EarBone automated smartphone audiometry app approximate those determined by an audiologist. This serves as a proof of concept for automated smartphone-based bone-conduction threshold testing. Further improvements, such as the addition of contralateral ear masking, are needed to make the app clinically useful.

Hearing Tests Based on Biologically Calibrated Mobile Devices: Comparison With Pure-Tone Audiometry

BACKGROUND

Hearing screening tests based on pure-tone audiometry may be conducted on mobile devices, provided that the devices are specially calibrated for the purpose. Calibration consists of determining the reference sound level and can be performed in relation to the hearing threshold of normal-hearing persons. In the case of devices provided by the manufacturer, together with bundled headphones, the reference sound level can be calculated once for all devices of the same model.

OBJECTIVE

This study aimed to compare the hearing threshold measured by a mobile device that was calibrated using a model-specific, biologically determined reference sound level with the hearing threshold obtained in pure-tone audiometry.

METHODS

Trial participants were recruited offline using face-to-face prompting from among Otolaryngology Clinic patients, who own Android-based mobile devices with bundled headphones. The hearing threshold was obtained on a mobile device by means of an open access app, Hearing Test, with incorporated model-specific reference sound levels. These reference sound levels were previously determined in uncontrolled conditions in relation to the hearing threshold of normal-hearing persons. An audiologist-assisted self-measurement was conducted by the participants in a sound booth, and it involved determining the lowest audible sound generated by the device within the frequency range of 250 Hz to 8 kHz. The results were compared with pure-tone audiometry.

RESULTS

A total of 70 subjects, 34 men and 36 women, aged 18-71 years (mean 36, standard deviation [SD] 11) participated in the trial. The hearing threshold obtained on mobile devices was significantly different from the one determined by pure-tone audiometry with a mean difference of 2.6 dB (95% CI 2.0-3.1) and SD of 8.3 dB (95% CI 7.9-8.7). The number of differences not greater than 10 dB reached 89% (95% CI 88-91), whereas the mean absolute difference was obtained at 6.5 dB (95% CI 6.2-6.9). Sensitivity and specificity for a mobile-based screening method were calculated at 98% (95% CI 93-100.0) and 79% (95% CI 71-87), respectively.

CONCLUSIONS

The method of hearing self-test carried out on mobile devices with bundled headphones demonstrates high compatibility with pure-tone audiometry, which confirms its potential application in hearing monitoring, screening tests, or epidemiological examinations on a large scale.