Trends in Hearing最新文献

This study measured electroencephalographic activity in the alpha band, often associated with task difficulty, to physiologically validate self-reported effort ratings from older hearing-impaired listeners performing the Repeat-Recall Test (RRT)-an integrative multipart assessment of speech-in-noise performance, context use, and auditory working memory. Following a single-blind within-subjects design, 16 older listeners (mean age = 71 years, SD = 13, 9 female) with a moderate-to-severe degree of bilateral sensorineural hearing loss performed the RRT while wearing hearing aids at four fixed signal-to-noise ratios (SNRs) of -5, 0, 5, and 10 dB. Performance and subjective ratings of listening effort were assessed for complementary versions of the RRT materials with high/low availability of semantic context. Listeners were also tested with a version of the RRT that omitted the memory (i.e., recall) component. As expected, results showed alpha power to decrease significantly with increasing SNR from 0 through 10 dB. When tested with high context sentences, alpha was significantly higher in conditions where listeners had to recall the sentence materials compared to conditions where the recall requirement was omitted. When tested with low context sentences, alpha power was relatively high irrespective of the memory component. Within-subjects, alpha power was related to listening effort ratings collected across the different RRT conditions. Overall, these results suggest that the multipart demands of the RRT modulate both neural and behavioral measures of listening effort in directions consistent with the expected/designed difficulty of the RRT conditions.

This study aimed to assess the validity of a high-frequency audiometry tool based on Bayesian learning to provide a reliable, repeatable, automatic, and fast test to clinics. The study involved 85 people (138 ears) who had their high-frequency thresholds measured with three tests: standard audiometry (SA), alternative forced choice (AFC)-based algorithm, and Bayesian active (BA) learning-based algorithm. The results showed median differences within ±5 dB up to 10 kHz when comparing the BA with the other two tests, and median differences within ±10 dB at higher frequencies. The variability increased from lower to higher frequencies. The BA showed lower thresholds compared to the SA at the majority of the frequencies. The results of the different tests were consistent across groups (age, hearing loss, and tinnitus). The data for the BA showed high test-retest reliability (>90%). The time required for the BA was shorter than for the AFC (4 min vs. 13 min). The data suggest that the BA test for high-frequency audiometry could be a good candidate for clinical screening. It would add reliable and significant information without adding too much time to the visit.

This study aimed to preliminarily investigate the associations between performance on the integrated Digit-in-Noise Test (iDIN) and performance on measures of general cognition and working memory (WM). The study recruited 81 older adult hearing aid users between 60 and 95 years of age with bilateral moderate to severe hearing loss. The Chinese version of the Montreal Cognitive Assessment Basic (MoCA-BC) was used to screen older adults for mild cognitive impairment. Speech reception thresholds (SRTs) were measured using 2- to 5-digit sequences of the Mandarin iDIN. The differences in SRT between five-digit and two-digit sequences (SRT_5-2), and between five-digit and three-digit sequences (SRT_5-3), were used as indicators of memory performance. The results were compared to those from the Digit Span Test and Corsi Blocks Tapping Test, which evaluate WM and attention capacity. SRT_5-2 and SRT_5-3 demonstrated significant correlations with the three cognitive function tests (rs ranging from -.705 to -.528). Furthermore, SRT_5-2 and SRT_5-3 were significantly higher in participants who failed the MoCA-BC screening compared to those who passed. The findings show associations between performance on the iDIN and performance on memory tests. However, further validation and exploration are needed to fully establish its effectiveness and efficacy.

In open-fit digital hearing aids (HAs), the processing delay influences comb-filter effects that arise from the interaction of the processed HA sound with the unprocessed direct sound. The current study investigated potential relations between preferred processing delay, spectral and temporal processing abilities, and self-reported listening habits. Ten listeners with normal hearing and 20 listeners with mild-to-moderate sensorineural hearing impairments participated. Using a HA simulator, delay preference was assessed with a paired-comparison task, three types of stimuli, and five processing delays (0, 0.5, 2, 5, and 10 ms). Spectral processing was assessed with a spectral ripple discrimination (SRD) task. Temporal processing was assessed with a gap detection task. Self-reported listening habits were assessed using a shortened version of the 'sound preference and hearing habits' questionnaire. A linear mixed-effects model showed a strong effect of processing delay on preference scores (p < .001, η²= 0.30). Post-hoc comparisons revealed no differences between either the two shortest delays or the three longer delays (all p > .05) but a clear difference between the two sets of delays (p < .001). A multiple linear regression analysis showed SRD to be a significant predictor of delay preference (p < .01, η²= 0.29), with good spectral processing abilities being associated with a preference for short processing delay. Overall, these results indicate that assessing spectral processing abilities can guide the prescription of open-fit HAs.

This study aimed to investigate the role of hearing aid (HA) usage in language outcomes among preschool children aged 3-5 years with mild bilateral hearing loss (MBHL). The data were retrieved from a total of 52 children with MBHL and 30 children with normal hearing (NH). The association between demographical, audiological factors and language outcomes was examined. Analyses of variance were conducted to compare the language abilities of HA users, non-HA users, and their NH peers. Furthermore, regression analyses were performed to identify significant predictors of language outcomes. Aided better ear pure-tone average (BEPTA) was significantly correlated with language comprehension scores. Among children with MBHL, those who used HA outperformed the ones who did not use HA across all linguistic domains. The language skills of children with MBHL were comparable to those of their peers with NH. The degree of improvement in audibility in terms of aided BEPTA was a significant predictor of language comprehension. It is noteworthy that 50% of the parents expressed reluctance regarding HA use for their children with MBHL. The findings highlight the positive impact of HA usage on language development in this population. Professionals may therefore consider HAs as a viable treatment option for children with MBHL, especially when there is a potential risk of language delay due to hearing loss. It was observed that 25% of the children with MBHL had late-onset hearing loss. Consequently, the implementation of preschool screening or a listening performance checklist is recommended to facilitate early detection.

Almost since the inception of the modern-day electroacoustic audiometer a century ago the results of pure-tone audiometry have been characterized by an audiogram. For almost as many years, clinicians and researchers have sought ways to distill the volume and complexity of information on the audiogram. Commonly used approaches have made use of pure-tone averages (PTAs) for various frequency ranges with the PTA for 500, 1000, 2000 and 4000 Hz (PTA4) being the most widely used for the categorization of hearing loss severity. Here, a three-digit triad is proposed as a single-number summary of not only the severity, but also the configuration and bilateral symmetry of the hearing loss. Each digit in the triad ranges from 0 to 9, increasing as the level of the pure-tone hearing threshold level (HTL) increases from a range of optimal hearing (< 10 dB Hearing Level; HL) to complete hearing loss (≥ 90 dB HL). Each digit also represents a different frequency region of the audiogram proceeding from left to right as: (Low, L) PTA for 500, 1000, and 2000 Hz; (Center, C) PTA for 3000, 4000 and 6000 Hz; and (High, H) HTL at 8000 Hz. This LCH Triad audiogram-classification system is evaluated using a large United States (U.S.) national dataset (N = 8,795) from adults 20 to 80 + years of age and two large clinical datasets totaling 8,254 adults covering a similar age range. Its ability to capture variations in hearing function was found to be superior to that of the widely used PTA4.

When presenting two competing speech stimuli, one to each ear, a right-ear advantage (REA) can often be observed, reflected in better speech recognition compared to the left ear. Considering the left-hemispheric dominance for language, the REA has been explained by superior contralateral pathways (structural models) and language-induced shifts of attention to the right (attentional models). There is some evidence that the REA becomes more pronounced, as cognitive load increases. Hence, it is interesting to investigate the REA in static (constant target talker) and dynamic (target changing pseudo-randomly) cocktail-party situations, as the latter is associated with a higher cognitive load than the former. Furthermore, previous research suggests an increasing REA, when listening becomes more perceptually challenging. The present study examined the REA by using virtual acoustics to simulate static and dynamic cocktail-party situations, with three spatially separated talkers uttering concurrent matrix sentences. Sentences were presented at low sound pressure levels or processed with a noise vocoder to increase perceptual load. Sixteen young normal-hearing adults participated in the study. The REA was assessed by means of word recognition scores and a detailed error analysis. Word recognition revealed a greater REA for the dynamic than for the static situations, compatible with the view that an increase in cognitive load results in a heightened REA. Also, the REA depended on the type of perceptual load, as indicated by a higher REA associated with vocoded compared to low-level stimuli. The results of the error analysis support both structural and attentional models of the REA.

The present study aimed to define use of head and eye movements during sound localization in children and adults to: (1) assess effects of stationary versus moving sound and (2) define effects of binaural cues degraded through acute monaural ear plugging. Thirty-three youth (M_Age= 12.9 years) and seventeen adults (M_Age= 24.6 years) with typical hearing were recruited and asked to localize white noise anywhere within a horizontal arc from -60° (left) to +60° (right) azimuth in two conditions (typical binaural and right ear plugged). In each trial, sound was presented at an initial stationary position (L1) and then while moving at ∼4°/s until reaching a second position (L2). Sound moved in five conditions (±40°, ±20°, or 0°). Participants adjusted a laser pointer to indicate L1 and L2 positions. Unrestricted head and eye movements were collected with gyroscopic sensors on the head and eye-tracking glasses, respectively. Results confirmed that accurate sound localization of both stationary and moving sound is disrupted by acute monaural ear plugging. Eye movements preceded head movements for sound localization in normal binaural listening and head movements were larger than eye movements during monaural plugging. Head movements favored the unplugged left ear when stationary sounds were presented in the right hemifield and during sound motion in both hemifields regardless of the movement direction. Disrupted binaural cues have greater effects on localization of moving than stationary sound. Head movements reveal preferential use of the better-hearing ear and relatively stable eye positions likely reflect normal vestibular-ocular reflexes.

In daily life, both acoustic factors and social context can affect listening effort investment. In laboratory settings, information about listening effort has been deduced from pupil and cardiovascular responses independently. The extent to which these measures can jointly predict listening-related factors is unknown. Here we combined pupil and cardiovascular features to predict acoustic and contextual aspects of speech perception. Data were collected from 29 adults (mean  =  64.6 years, SD  =  9.2) with hearing loss. Participants performed a speech perception task at two individualized signal-to-noise ratios (corresponding to 50% and 80% of sentences correct) and in two social contexts (the presence and absence of two observers). Seven features were extracted per trial: baseline pupil size, peak pupil dilation, mean pupil dilation, interbeat interval, blood volume pulse amplitude, pre-ejection period and pulse arrival time. These features were used to train k-nearest neighbor classifiers to predict task demand, social context and sentence accuracy. The k-fold cross validation on the group-level data revealed above-chance classification accuracies: task demand, 64.4%; social context, 78.3%; and sentence accuracy, 55.1%. However, classification accuracies diminished when the classifiers were trained and tested on data from different participants. Individually trained classifiers (one per participant) performed better than group-level classifiers: 71.7% (SD  =  10.2) for task demand, 88.0% (SD  =  7.5) for social context, and 60.0% (SD  =  13.1) for sentence accuracy. We demonstrated that classifiers trained on group-level physiological data to predict aspects of speech perception generalized poorly to novel participants. Individually calibrated classifiers hold more promise for future applications.