Auditory perception can improve when accompanied by somatosensory information, with beneficial effects for hard-of-hearing individuals. Further enhancement could occur by mapping discrete musical pitch information onto tactile spatial patterns across four fingertips. Unlike previous studies, we used tactile stimuli that marked only the sound onsets via light pressure from air-inflated plastic membranes. Pre- and post-learning pitch discrimination tests used vocoded-audio only, vocoded-audio with tactile, and tactile-only conditions. The learning phase was a 10-minute nursery song melody listening task with the audio-tactile condition. In Exp. 1, normal-hearing listeners heard melodies in the original audio; in Exp. 2, normal-hearing listeners heard melodies with vocoded-audio; and cochlear implant (CI) users listened to the original audio. All groups performed best in the audio-tactile condition before the learning phase, and these immediate benefits were maximal at intermediate pitch intervals. Furthermore, CI users showed greater improvement in the audio-only condition after exposure, indicating the rapid transfer effect.

IntroductionTraditional approaches to improving speech perception in noise (SPIN) for hearing-aid users have centered on directional microphones and remote wireless technologies. Recent advances in artificial intelligence and machine learning offer new opportunities for enhancing the signal-to-noise ratio (SNR) through adaptive signal processing. In this study, we evaluated the efficacy of a novel deep neural network (DNN)-based algorithm, commercially implemented as Edge Mode™, in improving SPIN outcomes for individuals with sensorineural hearing loss beyond that of conventional environmental classification approaches.MethodsThe algorithm was evaluated using (1) objective KEMAR-based performance in seven real-world scenarios, (2) aided and unaided speech-in-noise performance in 20 individuals with SNHL, and (3) real-world subjective ratings via ecological momentary assessment (EMA) in 20 individuals with SNHL.ResultsSignificant improvements in SPIN performance were observed on CNC+5, QuickSIN, and WIN, but not NST+5, likely due to the use of speech-shaped noise in the latter, suggesting the algorithm is optimized for multi-talker babble environments. SPIN gains were not predicted by unaided performance or degree of hearing loss, indicating individual variability in benefit, potentially due to differences in peripheral encoding or cognitive function. Furthermore, subjective EMA responses mirrored these improvements, supporting real-world utility.DiscussionThese findings demonstrate that DNN-based signal processing can meaningfully enhance speech understanding in complex listening environments, underscoring the potential of AI-powered features in modern hearing aids and highlighting the need for more personalized fitting strategies.

A test is proposed to characterize the performance of speech recognition systems. The QuickSIN test is used by audiologists to measure the ability of humans to recognize continuous speech in noise. This test yields the signal-to-noise ratio at which individuals can correctly recognize 50% of the keywords in low-context sentences. It is argued that a metric for automatic speech recognizers will ground the performance of automatic speech-in-noise recognizers to human abilities. Here, it is demonstrated that the performance of modern recognizers, built using millions of hours of unsupervised training data, is anywhere from normal to mildly impaired in noise compared to human participants.

OBJECTIVES:Self-assessment of perceived communication difficulty has been used in clinical and research practices for decades. Such questionnaires routinely assess the perceived ability of an individual to understand speech, particularly in background noise. Despite the emphasis on perceived performance in noise, speech recognition in routine audiologic practice is measured by word recognition in quiet (WRQ). Moreover, surprisingly little data exist that compare speech understanding in noise (SIN) abilities to perceived communication difficulty. Here, we address these issues by examining audiometric thresholds, WRQ scores, QuickSIN signal to noise ratio (SNR) loss, and perceived auditory disability as measured by the five questions on the Speech Spatial Questionnaire-12 (SSQ12) devoted to speech understanding (SSQ12-Speech5).DESIGN:We examined data from 1633 patients who underwent audiometric assessment at the Stanford Ear Institute. All individuals completed the SSQ12 questionnaire, pure-tone audiometry, and speech assessment consisting of ear-specific WRQ, and ear-specific QuickSIN. Only individuals with hearing threshold asymmetries ≤10 dB HL in their high-frequency pure-tone average (HFPTA) were included. Our primary objectives were to (1) examine the relationship between audiometric variables and the SSQ12-Speech5 scores, (2) determine the amount of variance in the SSQ12-Speech5 scores which could be predicted from audiometric variables, and (3) predict which patients were likely to report greater perceived auditory disability according to the SSQ12-Speech5.RESULTS:Performance on the SSQ12-Speech5 indicated greater perceived auditory disability with more severe degrees of hearing loss and greater QuickSIN SNR loss. Degree of hearing loss and QuickSIN SNR loss were found to account for modest but significant variance in SSQ12-Speech5 scores after accounting for age. In contrast, WRQ scores did not significantly contribute to the predictive power of the model. Degree of hearing loss and QuickSIN SNR loss were also found to have moderate diagnostic accuracy for determining which patients were likely to report SSQ12-Speech5 scores indicating greater perceived auditory disability.CONCLUSIONS:Taken together, these data indicate that audiometric factors including degree of hearing loss (i.e., HFPTA) and QuickSIN SNR loss are predictive of SSQ12-Speech5 scores, though notable variance remains unaccounted for after considering these factors. HFPTA and QuickSIN SNR loss-but not WRQ scores-accounted for a significant amount of variance in SSQ12-Speech5 scores and were largely effective at predicting which patients are likely to report greater perceived auditory disability on the SSQ12-Speech5. This provides further evidence for the notion that speech-in-noise measures have greater clinical utility than WRQ in most instances as they relate more closely to measures of perceived auditory disability.

Cochlear implant (CI) users often complain about music appreciation and speech recognition in background noise, which depend on segregating sound sources into perceptual streams. The present study examined relationships between frequency and fundamental frequency (F0) discrimination with stream segregation of tonal and speech streams for CI users and peers with no known hearing loss. Frequency and F0 discrimination were measured for 1,000 Hz pure tones and 110 Hz complex tones, respectively. Stream segregation was measured for pure and complex tones using a lead/lag delay detection task. Spondee word identification was measured in competing speech with high levels of informational masking that required listeners to use F0 to segregate speech. The hypotheses were that frequency and F0 discrimination would explain a significant portion of the variance in outcomes for tonal segregation and speech reception. On average, CI users received a large benefit for stream segregation of tonal streams when either the frequency or F0 of the competing stream was shifted relative to the target stream. A linear relationship accounted for 42% of the covariance between measures of stream segregation and complex tone discrimination for CI users. In contrast, such benefits were absent when the F0 of the competing speech was shifted relative to the target speech. The large benefit observed for tonal streams is promising for music listening if it transfers to separating instruments within a song; however, the lack of benefit for speech suggests separate mechanisms, or special requirements, for speech processing.

OBJECTIVES:Understanding speech in noise (SIN) is the dominant complaint of individuals with hearing loss. For decades, the default test of speech perception in routine audiologic assessment has been monosyllabic word recognition in quiet (WRQ), which does not directly address patient concerns, leading some to advocate that measures of SIN should be integrated into routine practice. However, very little is known with regard to how SIN abilities are affected by different types of hearing loss. Here, we examine performance on clinical measures of WRQ and SIN in a large patient base consisting of a variety of hearing loss types, including conductive (CHL), mixed (MHL), and sensorineural (SNHL) losses.DESIGN:In a retrospective study, we examined data from 5593 patients (51% female) who underwent audiometric assessment at the Stanford Ear Institute. All individuals completed pure-tone audiometry, and speech perception testing of monaural WRQ, and monaural QuickSIN. Patient ages ranged from 18 to 104 years (average = 57). The average age in years for the different classifications of hearing loss was 51.1 (NH), 48.5 (CHL), 64.2 (MHL), and 68.5 (SNHL), respectively. Generalized linear mixed-effect models and quartile regression were used to determine the relationship between hearing loss type and severity for the different speech-recognition outcome measures.RESULTS:Patients with CHL had similar performance to patients with normal hearing on both WRQ and QuickSIN, regardless of the hearing loss severity. In patients with MHL or SNHL, WRQ scores remained largely excellent with increasing hearing loss until the loss was moderately severe or worse. In contrast, QuickSIN signal to noise ratio (SNR) losses showed an orderly systematic decrease as the degree of hearing loss became more severe. This effect scaled with the data, with threshold-QuickSIN relationships absent for CHL, and becoming increasingly stronger for MHL and strongest in patients with SNHL. However, the variability in these data suggests that only 57% of the variance in WRQ scores, and 50% of the variance in QuickSIN SNR losses, could be accounted for by the audiometric thresholds. Patients who would not be differentiated by WRQ scores are shown to be potentially differentiable by SIN scores.CONCLUSIONS:In this data set, conductive hearing loss had little effect on WRQ scores or QuickSIN SNR losses. However, for patients with MHL or SNHL, speech perception abilities decreased as the severity of the hearing loss increased. In these data, QuickSIN SNR losses showed deficits in performance with degrees of hearing loss that yielded largely excellent WRQ scores. However, the considerable variability in the data suggests that even after classifying patients according to their type of hearing loss, hearing thresholds only account for a portion of the variance in speech perception abilities, particularly in noise. These results are consistent with the idea that variables such as cochlear health and aging add explanatory power over audibility alone.

OBJECTIVE:To determine whether immigrant status is associated with likelihood of audiogram and hearing aid use among US adults with hearing loss. STUDY DESIGN:Cross-sectional study. SETTING:Nationally representative data from 2009 to 2010, 2011 to 2012, 2015 to 2016, and 2017 to 2020 National Health and Nutrition Examination Survey (NHANES) cycles. METHODS:This cross-sectional study of 4 merged cycles of NHANES included 12,455 adults with subjective (self-reported) or objective (audiometric) hearing loss. Sequentially adjusted logistic regressions were used to assess the association of immigration status with likelihood of having undergone audiogram among those with objective and self-reported hearing loss, and with likelihood of hearing aid use among candidates with objective hearing loss. RESULTS:Immigrants were less likely to have received an audiogram among subjects with subjective (odds ratio [OR]: 0.81, 95% confidence interval [CI]: 0.75-0.87), and objective (OR: 0.76, 95% CI: 0.72-0.81) hearing loss, compared to nonimmigrants. The association persisted for those with subjective (OR: 0.88, 95% CI: 0.81-0.96), and objective (OR: 0.87, 95% CI: 0.80-0.96) hearing loss after adjusting for sociodemographic factors, comorbidities, insurance, and hearing quality, but disappeared in both groups after adjusting for English proficiency. Immigrants were less likely to use hearing aids (OR: 0.90, 95% CI: 0.87-0.93). However, this association disappeared (OR: 0.98, 95% CI: 0.93-1.04) in the adjusted model. CONCLUSION:Immigrant status is a significant barrier to hearing health care and is associated with lower rates of audiometric testing and hearing aid use among individuals with hearing loss.

This multi-center study examined the safety and effectiveness of cochlear implantation of children between 9 and 11 months of age. The intended impact was to support practice regarding candidacy assessment and prognostic counseling of pediatric cochlear implant candidates. Data in the clinical chart of children implanted at 9–11 months of age with Cochlear Ltd devices at five cochlear implant centers in the United States and Canada were included in analyses. The study included data from two cohorts implanted with one or two Nucleus devices during the periods of January 1, 2012–December 31, 2017 (Cohort 1, n = 83) or between January 1, 2018 and May 15, 2020 (Cohort 2, n = 50). Major adverse events (requiring another procedure/hospitalization) and minor adverse events (managed with medication alone or underwent an expected course of treatment that did not require surgery or hospitalization) out to 2 years post-implant were monitored and outcomes measured by audiometric thresholds and parent-reports on the IT-MAIS and LittlEARS questionnaires were collected. Results revealed 60 adverse events in 41 children and 227 ears implanted (26%) of which 14 major events occurred in 11 children; all were transitory and resolved. Improved hearing with cochlear implant use was shown in all outcome measures. Findings reveal that the procedure is safe for infants and that they show clear benefits of cochlear implantation including increased audibility and hearing development.

ObjectiveTo compare fall risk scores of hearing aids embedded with inertial measurement units (IMU-HAs) and powered by artificial intelligence (AI) algorithms with scores by trained observers.Study DesignProspective, double-blinded, observational study of fall risk scores between trained observers and those of IMU-HAs.SettingTertiary referral center.PatientsTwo hundred fifty participants aged 55-100 years who were at risk for falls.InterventionsFall risk was categorized using the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) test battery consisting of the 4-Stage Balance, Timed Up and Go (TUG), and 30-Second Chair Stand tests. Performance was scored using bilateral IMU-HAs and compared to scores by clinicians blinded to the hearing aid measures.Main Outcome MeasuresFall risk categorizations based on 4-Stage Balance, Timed Up and Go (TUG), and 30-Second Chair Stand tests obtained from IMU-HAs and clinicians.ResultsInterrater reliability was excellent across all clinicians. The 4-Stage Balance and TUG showed no statistically significant differences between clinician and HAs. However, the IMU-HAs failed to record a response in 12% of TUG trials. For the 30-Second Chair Stand test, there was a significant difference of nearly one stand count, which would have altered fall risk classification in 21% of participants.ConclusionsThese results suggest that fall risk as determined by the STEADI tests was in most instances similar for IMU-HAs and trained observers; however, differences were observed in certain situations, suggesting improvements are needed in the algorithm to maximize accurate fall risk categorization.

OBJECTIVE:This study aimed to assess the prevalence of cochlear nerve deficiency (CND) in a cohort of pediatric patients with single-sided deafness (SSD). A secondary objective was to investigate trends in intervention and hearing device use in these children.STUDY DESIGN:Case series with chart review.SETTING:Pediatric tertiary care center.METHODS:Children ages 0 to 21 years with SSD (N = 190) who underwent computerized tomography (CT) and/or magnetic resonance imaging (MRI) were included. Diagnostic criteria for SSD included unilateral severe-to-profound sensorineural hearing loss with normal hearing sensitivity in the contralateral ear. Diagnostic criteria for CND included neuroradiologist report of an "aplastic or hypoplastic nerve" on MRI or a "stenotic cochlear aperture" on CT.RESULTS:The prevalence of CND was 42% for children with CT only, 76% for children with MRI only, and 63% for children with both MRI and CT. Of the children with MRI and CT, there was a 90% concordance across imaging modalities. About 36% of children with SSD had hearing devices that routed sound to the normal hearing ear (ie, bone conduction hearing device/contralateral routing of signal), while only 3% received a cochlear implant. Approximately 40% did not have a hearing device. Hearing device wear time averaged 2.9 hours per day and did not differ based on cochlear nerve status.CONCLUSION:There is a high prevalence of CND in children with SSD. Cochlear nerve status should be confirmed via MRI in children with SSD. The limited implementation and use of hearing devices observed for children with SSD reinforce the need for increased support for early and continuous intervention.

OBJECTIVES:Measures of speech-in-noise, such as the QuickSIN, are increasingly common tests of speech perception in audiologic practice. However, the effect of vestibular schwannoma (VS) on speech-in-noise abilities is unclear. Here, we compare the predictive ability of interaural QuickSIN asymmetry for detecting VS against other measures of audiologic asymmetry. METHODS:A retrospective review of patients in our institution who received QuickSIN testing in addition to a regular audiologic battery between September 2015 and February 2019 was conducted. Records for patients with radiographically confirmed, unilateral, pretreatment VSs were identified. The remaining records excluding conductive pathologies were used as controls. The predictive abilities of various measures of audiologic asymmetry to detect VS were statistically compared. RESULTS:Our search yielded 73 unique VS patients and 2423 controls. Receiver operating characteristic curve analysis showed that QuickSIN asymmetry was more sensitive and specific than pure-tone average asymmetry and word-recognition-in-quiet asymmetry for detecting VS. Multiple logistic regression analysis revealed that QuickSIN asymmetry was more predictive of VS (odds ratio [OR] = 1.23, 95% confidence interval [CI] [1.10, 1.38], p < 0.001) than pure-tone average asymmetry (OR = 1.04, 95% CI [1.00, 1.07], p = 0.025) and word-recognition-in-quiet asymmetry (OR = 1.03, 95% CI [0.99, 1.06], p = 0.064). CONCLUSION:Between-ear asymmetries in the QuickSIN appear to be more efficient than traditional measures of audiologic asymmetry for identifying patients with VS. These results suggest that speech-in noise testing could be integrated into clinical practice without hindering the ability to identify retrocochlear pathology.

Objectives: For decades, monosyllabic word-recognition in quiet (WRQ) has been the default test of speech recognition in routine audiologic assessment. The continued use of WRQ scores is noteworthy in part because difficulties understanding speech in noise (SIN) is perhaps the most common complaint of individuals with hearing loss. The easiest way to integrate SIN measures into routine clinical practice would be for SIN to replace WRQ assessment as the primary test of speech perception. To facilitate this goal, we predicted classifications of WRQ scores from the QuickSIN signal to noise ratio (SNR) loss and hearing thresholds.Design: We examined data from 5808 patients who underwent audiometric assessment at the Stanford Ear Institute. All individuals completed pure-tone audiometry, and speech assessment consisting of monaural WRQ, and monaural QuickSIN. We then performed multiple-logistic regression to determine whether classification of WRQ scores could be predicted from pure-tone thresholds and QuickSIN SNR losses.Results: Many patients displayed significant challenges on the QuickSIN despite having excellent WRQ scores. Performance on both measures decreased with hearing loss. However, decrements in performance were observed with less hearing loss for the QuickSIN than for WRQ. Most important, we demonstrate that classification of good or excellent word-recognition scores in quiet can be predicted with high accuracy by the high-frequency pure-tone average and the QuickSIN SNR loss.Conclusions: Taken together, these data suggest that SIN measures provide more information than WRQ. More important, the predictive power of our model suggests that SIN can replace WRQ in most instances, by providing guidelines as to when performance in quiet is likely to be excellent and does not need to be measured. Making this subtle, but profound shift to clinical practice would enable routine audiometric testing to be more sensitive to patient concerns, and may benefit both clinicians and researchers.

Supplemental Digital Content is available in the text Objective: Evaluate outcomes in cochlear implant (CI) recipients qualifying in AzBio noise but not quiet, and identify factors associated with postimplantation improvement. Study Design: Retrospective cohort study. Setting: Tertiary otology/neurotology clinic. Patients: This study included 212 implanted ears. The noise group comprised 23 ears with preoperative AzBio more than or equal to 40% in quiet and less than or equal to 40% in +10 signal-to-noise ratio (SNR). The quiet group included 189 ears with preoperative AzBio less than 40% in quiet. The two groups displayed similar demographics and device characteristics. Interventions: Cochlear implantation. Main Outcome Measures: AzBio in quiet and noise. Results: Mean AzBio quiet scores improved in both the quiet group (pre-implant: 12.7%, postimplant: 67.2%, p < 0.001) and noise group (pre-implant: 61.6%, postimplant: 73.8%, p = 0.04). Mean AzBio +10 SNR also improved in the quiet group (pre-implant: 15.8%, postimplant: 59.3%, p = 0.001) and noise group (pre-implant: 30.5%, postimplant: 49.1%, p = 0.01). However, compared with the quiet group, fewer ears in the noise group achieved within-subject improvement in AzBio quiet (≥15% improvement; quiet group: 90.3%, noise group: 43.8%, p < 0.001) and AzBio +10 SNR (quiet group: 100.0%, noise group: 45.5%, p < 0.001). Baseline AzBio quiet (p < 0.001) and Consonant-Nucleus-Consonant (CNC) scores (p = 0.004) were associated with within-subject improvement in AzBio quiet and displayed a higher area under the curve than either aided or unaided pure-tone average (PTA) (both p = 0.01). Conclusions: CI patients qualifying in noise display significant mean benefit in speech recognition scores but are less likely to benefit compared with those qualifying in quiet. Patients with lower baseline AzBio quiet scores are more likely to display postimplant improvement.

Many studies have found benefits of using somatosensory modality to augment sound information for individuals with hearing loss. However, few studies have explored the use of multiple regions of the body sensitive to vibrotactile stimulation to convey discrete F0 information, important for music perception. This study explored whether mapping of multiple finger patterns associated with musical notes can be learned quickly and transferred to discriminate vocoded auditory stimuli. Each of eight musical diatonic scale notes were associated with one of unique finger digits 2-5 patterns in the dominant hand, where pneumatic tactile stimulation apparatus were attached. The study consisted of a pre and post-test with a learning phase in-between. During the learning phase, normal-hearing participants had to identify common nursery song melodies presented with simultaneous auditory-tactile stimulus for about 10 min, using non-vocoded (original) audio. Pre- and post-tests examined stimulus discrimination for 4 conditions: original audio + tactile, tactile only, vocoded audio only, and vocoded audio + tactile. The audio vocoder used cochlear implant 4 channel simulation. Our results demonstrated audio-tactile learning improved participant’s performance on the vocoded audio + tactile tasks. The tactile only condition also significantly improved, indicating the rapid learning of the audio-tactile mapping and its effective transfer.

The most common device used to manage pediatric sensorineural hearing loss (SNHL) is the behind-the-ear (BTE) hearing aid (HA), which typically requires the use of a custom earmold in pediatric patients to maximize their access to sound. 1 As children grow, these earmolds must be replaced to deliver sound optimally. Otherwise, the amount of feedback is likely to increase and the hearing aid will become less comfortable and useful. 1 Maintaining access to sound is crucial given that duration of HA use is associated with better outcomes. 2,3 These difficulties are likely to be further exacerbated in children in developing countries, who lack consistent access to audiologic care. 4Pediatric audiology, earmolds, hearing aids.Figure 1: (A) Current protocol for provision of pediatric earmolds. (B) Earmolds lose contact with key points of the canal with growth. (C) Novel adjustable earmold can be inflated to maintain contact with anatomic landmarks. Pediatric audiology, earmolds, hearing aids.Figure 2: (A) The fabrication process of creating the proposed adjustable earmold, which utilizes (B) a temperature-dependent, (C) viscosity-changing pluronic fluid that can be drained after the earmold has been molded and cast. Pediatric audiology, earmolds, hearing aids.Figure 3: (A) Adjustable earmold prototype with inflation mechanism (syringe and Luer-activated valve). (B) Adjustable earmold prototype. Pink shading and white silicone represents earmold canal portion before and after inflation, respectively. (C) Proposed derivation of inflation schedule. Pediatric audiology, earmolds, hearing aids.In conventional audiologic settings, at least two visits are required per set of earmolds: one to generate the impression and one to fit the mold (Figure 1A). The manufacturing turnaround for molds is typically 8 to 12 days, with additional time required for the fitting process. 5 This inefficient cycle is repeated many times during childhood due to rapid growth. Furthermore, current earmolds are static in that they lose contact with key points of the canal after growth, leading to poor acoustic seal, loss of retention, and discomfort (Figure 1B). One solution to reduce the amount of time with suboptimal or no sound input would be to have an earmold that could be adjusted, rather than replaced, by either the caregiver or audiologist. Then, children could maintain access to sound as they grow despite changes in the size and shape of the ear. Here, we describe a novel, low-cost manufacturing technique that allows for adjustment of the size and fit of the earmold using standard materials. The earmold, inspired by novel soft robotic engineering techniques, allows for selective inflation of the canalicular portion of the earmold, thus maintaining optimal contact with the anatomic points most important for comfort, retention, and acoustic fidelity (Figure 1C). 6,7 The objective of such a device would be to reduce time and sound input lost due to poorly fitting earmolds. METHODS & MATERIALS Materials All molds consist of two materials: silicone for the body of the mold and temperature-responsive Pluronic F127 for the sacrificial ink. 6,8,9 Methods 1.0 Formulation of Pluronic F127 Pluronic F127 (Sigma-Aldrich) was dissolved in milliQ water (Millipore Sigma) at 20 wt% and dissolved over 2 days at 4°C. The solution was kept in 10 mL aliquots and stored at room temperature. Two drops of aqueous-based red food dye were added to each aliquot. 1.1 Creation of core casting mold Figure 2A displays the overall fabrication process to create the adjustable earmold using silicone and Pluronic F127 with figure numbers aligning with steps detailed subsequently. First, a set of casting molds were designed and 3D printed for an ear impression that was scaled 1.5x original size for prototyping. The casting mold was altered to have the same conchal eminence dimensions as the scaled impression, a canal with the same length, and a diameter no more than 50% of the scaled impression diameter to allow for ease of subsequent manufacturing steps. 10 Figure 2A 1.1 displays the core casting mold creation. 1.2 Creation of earmold core 20 g of SORTAClear 40 silicone (Smooth-On) was mixed according to manufacturer’s instructions, degassed, and loaded into the first small casting mold by filling one half of the mold, covering with the other half and injecting silicone through the injection port until the mold was full. This became the earmold core once cured overnight and removed from the casting mold (Figure 2A 1.2). 2.0 Creation of outer casting mold The same 1.5x scaled digital ear impression was used to create a second casting mold that would result in creation of an earmold with the initial target size. 2.1 Application of Pluronic F127 A spatula was used to paint the entire ear canal portion of the earmold core with a 1 mm-thick layer of 20 wt% Pluronic F127 (Figure 2A 2.1). 2.2 Outer silicone casting to create outer mold 20 g of Ecoflex 20 (Smooth-On) was mixed according to manufacturer’s instructions and degassed. 0.1 g of colored silicone dye, SilcPig (Smooth-On) was added to the Ecoflex 20 to improve visualization. 7 g of Ecoflex 20 was poured into one half of the outer casting mold and the earmold core coated with Pluronic F127 was submerged into this half. Then, the second half of the casting mold was placed on top to envelop the earmold core within and more Ecoflex 20 was injected via the injection port into the mold until completely filled (Figure 2A 2.2) and allowed to cure overnight. 3.1 Draining of Pluronic F127 The complete mold—composed of the outer mold, Pluronic F127 coating within, and earmold core within—was placed at 4°C to liquify the Pluronic F127 using the temperature-dependent behavior of Pluronic F127 seen in Figure 2B. The temperature-dependent viscosity of Pluronic F127 measured with shear rheology is also shown in Figure 2C, where 20 wt% Pluronic F127 in water has a lower critical solution temperature of 23°C. Therefore, when the solution is at low temperatures, it behaves as a liquid and when above room temperature, it behaves as a solid-like gel. The mold was punctured through the conchal eminence with a 21 G needle and 10 mL syringe to access the Pluronic F127 pocket. A syringe, aided with the use of cold water, was used to remove the liquid Pluronic F127, leaving an empty void (Figure 2A 3.1). 3.2 Hardware Preparation for Inflation Both a 21 G needle and a male 1/16” Luer lock barb were inserted into the same puncture site used for draining Pluronic. The barb was coated in a silicone-bonding epoxy to seal the opening to the earmold. This fitting was secured to a syringe, as shown in Figure 3A, using a 1/16” inner diameter silicone tubing and a Luer-activated valve (Qosina Corp.). These components create a simple inflation action via the syringe, while the Luer-activated valve seals the pressure inside the earmold when the syringe is disconnected (Figure 2A 3.2). RESULTS This prototype consisted of a 1.5x scaled earmold with a 1 mm-thick void around the external auditory canal region. The canal region was selected for the inflation to optimize acoustic seal, retention, and comfort. 7 When pressure was applied through the syringe during inflation, we achieved a continuous range of anisotropic inflation of the earmold’s canal portion. Figure 3B displays the final adjustable earmold prototype with labeled designations; pink shading represents the earmold canal portion before inflation, while the white silicone represents the inflated earmold canal. Measurements of canal diameter before and after inflation were taken at three locations along the canal portion of the earmold. The apex of the first bend of the ear canal experienced an expansion of 24.9%. A point in the canal 5 mm medial to the apex of the first bend expanded by 13.3%, and a point 5 mm lateral to the apex of the first bend expanded by 7.0%. DISCUSSION This prototype demonstrates the capabilities of an adjustable, yet still personalized, earmold. This earmold could allow children with BTE hearing aids to maintain optimal access to sound during critical periods of development. Moreover, this approach has the potential to minimize the number of patient visits and reduce the need for “remakes” of earmolds due to poor impressions or manufacturing of the device. The adjustable earmold concept could minimize barriers to access in the pediatric audiology workflow and may be particularly useful for children in developing countries or rural areas who have limited access to specialized audiologic care. Finally, the adjustable earmold approach may also be useful for adults who need compressible molds to accommodate dynamic canal changes with jaw movement. 11 Future optimization could take many forms, including validation across a range of anatomical shapes and sizes, as well as testing adjustment in the conchal eminence. Additionally, acoustic integration and testing using real-ear measurements is needed to assess transmission capabilities across a wide range of hearing losses. Finally, an algorithm must be developed to help determine when the earmold needs to be adjusted. Algorithm inputs may include information from the feedback manager, the output from the HA measured as gain, and also predicted growth patterns of external ear anatomy over time. This final input, the expected pediatric growth pattern, might involve an adjustment schedule. Figure 3C illustrates a proposed method to arrive at a possible inflation schedule using a calibration study in which mold diameter is correlated with input pressure, and canal diameter is correlated with age. This would potentially enable the prediction of input pressure required for a given age and subsequently allow for the creation of a typical inflation schedule. Once these steps to validate the prototype have been achieved, the manufacturing process would need to be streamlined, perhaps by utilizing another casting mold for consistent Pluronic F127 layering, replacing the manual coating method seen in Figure 2A 2.1. Various areas of Pluronic F127 placement may also be tested, including the key anatomical points depicted in Figure 1B and 1C. CONCLUSION To our knowledge, this is the first report of a prototype for an earmold that can be adjusted outside of the clinic. This prototype uses biocompatible materials and allows for selective inflation of different portions of the mold. This approach has the potential to ensure that the earmold can maintain comfort and acoustic retention as the child grows. Thus, an adjustable earmold could reduce the amount of time a child has suboptimal access to sound and may be particularly beneficial for patients who do not have consistent access to audiologic services. Further work is required to validate this approach, but we are optimistic that an adjustable earmold could provide audiologists with additional tools to maximize a child’s access to sound.

Purpose: An extra moment after a sentence is spoken may be important for listeners with hearing loss to mentally repair misperceptions during listening. The current audiologic test battery cannot distinguish between a listener who repaired a misperception versus a listener who heard the speech accurately with no need for repair. This study aims to develop a behavioral method to identify individuals who are at risk for relying on a quiet moment after a sentence. Method: Forty-three individuals with hearing loss (32 cochlear implant users, 11 hearing aid users) heard sentences that were followed by either 2 s of silence or 2 s of babble noise. Both high- and low-context sentences were used in the task. Results: Some individuals showed notable benefit in accuracy scores (particularly for high-context sentences) when given an extra moment of silent time following the sentence. This benefit was highly variable across individuals and sometimes absent altogether. However, the group-level patterns of results were mainly explained by the use of context and successful perception of the words preceding sentence-final words. Conclusions: These results suggest that some but not all individuals improve their speech recognition score by relying on a quiet moment after a sentence, and that this fragility of speech recognition cannot be assessed using one isolated utterance at a time. Reliance on a quiet moment to repair perceptions would potentially impede the perception of an upcoming utterance, making continuous communication in real-world scenarios difficult especially for individuals with hearing loss. The methods used in this study—along with some simple modifications if necessary—could potentially identify patients with hearing loss who retroactively repair mistakes by using clinically feasible methods that can ultimately lead to better patient-centered hearing health care. Supplemental Material: https://doi.org/10.23641/asha.21644801

Objective Present results with remote intraoperative neural response telemetry (NRT) during cochlear implantation (CI) and its usefulness in overcoming the inefficiency of in person NRT. Study Design Case series. Setting Tertiary academic otology practice. Patients All patients undergoing primary or revision CI, both adult and pediatric, were enrolled. Interventions Remote intraoperative NRT performed by audiologists using a desktop computer to control a laptop in the operating room. Testing was performed over the hospital network using commercially available software. A single system was used to test all three FDA-approved manufacturers’ devices. Main Outcome Measures Success rate and time savings of remote NRT. Results Out of 254 procedures, 252 (99.2%) underwent successful remote NRT. In two procedures (0.7%), remote testing was unsuccessful, and required in-person testing to address technical issues. Both failed attempts were due to hardware failure (OR laptop or headpiece problems). There was no relation between success of the procedure and patient/surgical factors such as difficult anatomy, or the approach used for inner ear access. The audiologist time saved using this approach was considerable when compared with in-person testing. Conclusions Remote intraoperative NRT testing during cochlear implantation can be performed effectively using standard hardware and remote-control software. Especially important during the Covid-19 pandemic, such a procedure can reduce in-person contacts, and limit the number of individuals in the operating room. Remote testing can provide additional flexibility and efficiency in audiologist schedules.

OBJECTIVE:To assess whether the pre-operative electrode to cochlear duct length ratio (ECDLR), is associated with post-operative speech recognition outcomes.STUDY DESIGN:A retrospective chart review study.SETTING:Tertiary referral center.PATIENTS:The study included sixty-one adult CI recipients with a pre-operative computed tomography scan and a speech recognition test 12 months after implantation.INTERVENTIONS:The average of two raters' cochlear duct length (CDL) measurements and the length of the recipient's cochlear implant electrode array formed the basis for the electrode-to-cochlear duct length ratio (ECLDR). Speech recognition tests were compared as a function of ECDLR and electrode array length itself.MAIN OUTCOME MEASURES:The relationship between ECDLR and percent correct on speech recognition tests.RESULTS:A second order polynomial regression relating ECDLR to percent correct on the CNC words speech recognition test was statistically significant, as was a fourth order polynomial regression for the AzBio Quiet test. In contrast, there was no statistically significant relationship between speech recognition scores and electrode array length.CONCLUSIONS:ECDLR values can be statistically associated to speech-recognition outcomes. However, these ECDLR values cannot be predicted by the electrode length alone, and must include a measure of CDL.

Acoustic coordinated reset (aCR) therapy for tinnitus aims to desynchronize neuronal populations in the auditory cortex that exhibit pathologically increased coincident firing. The original therapeutic paradigm involves fixed spacing of four low-intensity tones centered around the frequency of a tone matching the tinnitus pitch, f T , but it is unknown whether these tones are optimally spaced for induction of desynchronization. Computational and animal studies suggest that stimulus amplitude, and relatedly, spatial stimulation profiles, of coordinated reset pulses can have a major impact on the degree of desynchronization achievable. In this study, we transform the tone spacing of aCR into a scale that takes into account the frequency selectivity of the auditory system at each therapeutic tone’s center frequency via a measure called the gap index. Higher gap indices are indicative of more loosely spaced aCR tones. The gap index was found to be a significant predictor of symptomatic improvement, with larger gap indices, i.e., more loosely spaced aCR tones, resulting in reduction of tinnitus loudness and annoyance scores in the acute stimulation setting. A notable limitation of this study is the intimate relationship of hearing impairment with the gap index. Particularly, the shape of the audiogram in the vicinity of the tinnitus frequency can have a major impact on tone spacing. However, based on our findings we suggest hypotheses-based experimental protocols that may help to disentangle the impact of hearing loss and tone spacing on clinical outcome, to assess the electrophysiologic correlates of clinical improvement, and to elucidate the effects following chronic rather than acute stimulation.

Hypothesis: This study tests the hypothesis that it is possible to find tone or noise vocoders that sound similar and result in similar speech perception scores to a cochlear implant (CI). This would validate the use of such vocoders as acoustic models of CIs. We further hypothesize that those valid acoustic models will require a personalized amount of frequency mismatch between input filters and output tones or noise bands. Background: Noise or tone vocoders have been used as acoustic models of CIs in hundreds of publications but have never been convincingly validated. Methods: Acoustic models were evaluated by single-sided deaf CI users who compared what they heard with the CI in one ear to what they heard with the acoustic model in the other ear. We evaluated frequency-matched models (both all-channel and 6-channel models, both tone and noise vocoders) as well as self-selected models that included an individualized level of frequency mismatch. Results: Self-selected acoustic models resulted in similar levels of speech perception and similar perceptual quality as the CI. These models also matched the CI in terms of perceived intelligibility, harshness, and pleasantness. Conclusion: Valid acoustic models of CIs exist, but they are different from the models most widely used in the literature. Individual amounts of frequency mismatch may be required to optimize the validity of the model. This may be related to the basalward frequency mismatch experienced by postlingually deaf patients after cochlear implantation.