Starkey Research & Clinical Blog

Patients with higher cognitive function may benefit more from hearing aid features

Ng, E.H.N., Rudner, M., Lunner, T., Pedersen, M.S., & Ronnberg, J. (2013). Effects of noise and working memory capacity on memory processing of speech for hearing-aid users. International Journal of Audiology, Early Online, 1-9.

This editorial discusses the clinical implications of an independent research study and does not represent the opinions of the original authors.

Research reports as well as clinical observations indicate that competing noise increases the cognitive demands of listening, an effect that is especially impactful for individuals with hearing loss (McCoy et al., 2005; Picou et al., 2013; Rudner et al., 2011).  Listening effort is a cognitive dimension of listening that is thought to represent the allocation of cognitive resources needed for speech recognition (Hick & Tharpe, 2002). Working memory, is a further dimension of cognition that involves the simultaneous processing and storage of information; its effect on speech processing may vary depending on the listening conditions (Rudner et al., 2011).

The concept of effortful listening can be characterized with the Ease of Language Understanding (ELU) model (Ronnberg, 2003; Ronnberg et al., 2008). In quiet conditions when the speech is audible and clear, the speech input is intact and is automatically and easily matched to stored representations in the lexicon. When speech inputs are weak, distorted or obscured by noise, mismatches may occur and speech inputs may need to be compared to multiple stored representations to arrive at the most likely match. In these conditions, allocation of additional cognitive resources, is required. Efficient cognitive functioning and large working memory capacity allows more rapid and successful matches between speech inputs and stored representations. Several studies have indicated a relationship between cognitive ability and speech perception: Humes (2007) found that cognitive function was the best predictor of speech understanding in noise and Lunner (2003) reported that participants with better working memory capacity and verbal processing speed had better speech perception performance.

Following the ELU model, hearing aids may allow listeners to match inputs and stored representations more successfully, with less explicit processing. Noise reduction, as implemented in hearing aids, has been proposed as a technology that may ease effortful listening. In contrast, however, it has been suggested that hearing aid signal processing may introduce unwanted artifacts or alter the speech inputs so that more explicit processing is required to match them to stored images (Lunner et al., 2009). If this is the case, hearing aid users with good working memory may function better with amplification because their expanded working memory capacity allows more resources to be applied to the task of matching speech inputs to long-term memory stores.

Elaine Ng and her colleagues investigated the effect of noise and noise reduction on word recall and identification and examined whether individuals were affected by these variables differently based on their working memory capacity. The authors had several hypotheses:

1. Noise would adversely affect memory, with poorer memory performance for speech in noise than in quiet.

2. Memory performance in noise would be at least partially restored by the use of noise reduction.

3. The effect of noise reduction on memory would be greater for items in late list positions because participants were older and therefore likely to have slower memory encoding speeds.

4. Memory in competing speech would be worse than in stationary noise because of the stronger masking effect of competing speech.

5. Overall memory performance would be better for participants with higher working memory capacity in the presence of noise reduction. This effect should be more apparent for late list items presented with competing speech babble.

Twenty-six native Swedish-speaking individuals with moderate to moderately-severe, high-frequency sensorineural hearing loss participated in the authors’ study. Prior to commencement of the study, participants were tested to ensure that they had age-appropriate cognitive performance. A battery of tests was administered and results were comparable to previously reported performance for their age group (Ronnberg, 1990).

Two tests were administered to study participants. First, a reading span test evaluated working memory capacity.  Participants were presented with a total of 24 three-word sentences and sub-lists of 3, 4 and 5 sentences were presented in ascending order. Participants were asked to judge whether the sentences were sensible or nonsense. At the end of each sub-list of sentences, listeners were prompted to recall either the first or final words of each sentence, in the order in which they were presented. Tests were scored as the total number of items correctly recalled.

The second test was a sentence-final word identification and recall (SWIR) test, consisting of 140 everyday sentences from the Swedish Hearing In Noise Test (HINT; Hallgren et al, 2006). This test involved two different tasks. The first was an identification task in which participants were asked to report the final word of each sentence immediately after listening to it.  The second task was a free recall task; after reporting the final word of the eighth sentence of the list, they were asked to recall all the words that they had previously reported. Three of seven tested conditions included variations of noise reduction algorithms, ranging from one similar to those implemented in modern hearing aids to an ‘ideal’ noise reduction algorithm.

Prior to the main analyses of working memory and recall performance, two sets of groups were created based on reading span scores, using two different grouping methods. In the first set, two groups were created by splitting the group at the median score so that 13 individuals were in a high reading span group and the remaining 13 were in a low reading span group. In the second set, participants who scored in the mid-range on the reading span test were excluded from the analysis, creating High reading span and Low reading span groups of 10 participants each. There was no significant difference between groups based on age, pure tone average or word identification performance, in any of the noise conditions. Overall reading span scores for participants in this study were comparable to previously reported results (Lunner, 2003; Foo, 2007).

Also prior to the main analysis, the SWIR results were analyzed to compare noise reduction and ideal noise reduction conditions. There was no significant difference between noise reduction and ideal noise reduction conditions in the identification or free recall tasks, nor was there an interaction of noise reduction condition with reading span score. Therefore, only the noise reduction condition was considered in the subsequent analyses.

The relationship between reading span score (representing working memory capacity) and SWIR recall was examined for all the test conditions. Reading span score correlated with overall recall performance in all conditions but one. When recall was analyzed as a function of list position (beginning or final), reading span scores correlated significantly with beginning (primacy) positions in quiet and most noise conditions. There was no significant correlation between overall reading span scores and items in final (recency) position in any of the noise conditions.

There were significant main effects for noise, list position and reading span group. In other words, when noise reduction was implemented, the negative effects of noise were lessened. There was a recency effect, in that performance was better for late list positions than for early list positions. Overall, the high reading span groups scored better than the low reading span groups, for both median-split and mid-range exclusion groups. The high reading span groups showed improved recall with noise reduction, whereas the low reading span groups exhibited no change in performance with noise reduction versus quiet.  The use of four-talker babble had a negative effect on late list positions, but did not affect items in other positions, suggesting that four-talker babble disrupted working memory more than steady-state noise. These analyses supported hypotheses 1, 2, 3 and 5, indicating that noise adversely affects memory performance (1), that noise reduction and list position interact with this effect (2,3) especially for individuals with high working memory capacity (5).

The results also supported hypothesis 4, which suggested that competing speech babble would affect memory performance more than steady state noise. Recall performance was significantly better in the presence of steady-state noise than it was in 4-talker babble. Though there was no significant effect of noise reduction overall, high reading span participants once again outperformed low reading span participants with noise reduction.

In summary, the results of this study determined that noise had an adverse effect on recall, but that this effect was mildly mitigated by the use of noise reduction. Four-talker babble was more disruptive to recall performance than was steady-state noise. Recall performance was better for individuals with higher working memory capacity. These individuals also demonstrated more of a benefit from noise reduction than did those with lower working memory capacity.

Recall performance is better in quiet conditions than in noise because presumably fewer cognitive resources are required to encode the speech input (Murphy, et al., 2000). Ng and her colleagues suggest that noise reduction helps to perceptually segregate speech from noise, allowing the speech input to be matched to stored lexical representations with less cognitive demand. So, noise reduction may at least partially reverse the negative effect of noise on working memory.

Competing speech babble is more likely to be cognitively demanding than steady-state noise (such as an air conditioner) because it contains meaningful information that is more distracting and harder to separate from the speech of interest (Sorqvist & Ronnberg, 2012). Not only is the speech signal of interest degraded by the presence of competing sound and therefore harder to encode, but additional cognitive resources are required to inhibit the unwanted or irrelevant linguistic information (Macken, 2009).  Because competing speech puts more demands on cognitive resources, it is more potentially disruptive than steady-state noise to perception of the speech signal of interest.

Unfortunately, much of the background noise encountered by hearing aid wearers is competing speech. The classic example of the cocktail party illustrates one of the most challenging situations for hearing-impaired individuals, in which they must try to attend to a proximal conversation while ignoring multiple conversations surrounding them. The results of this study suggest that noise reduction may be more useful in these situations for listeners with better working memory capacity; however, noise reduction should still be considered for all hearing aid users, with comprehensive follow-up care to make adjustments for individuals who are not functioning well in noisy conditions. Noise reduction may generally alleviate perceived effort or annoyance, allowing a listener to be more attentive to the speech signal of interest or to remain in a noisy situation that would otherwise be uncomfortable or aggravating.

More research is needed on the effects of noise, noise reduction and advanced signal processing on listening effort and memory in everyday situations. It is likely that performance is affected by numerous variables of the hearing aid, including compression characteristics, directionality, noise reduction, as well as the automatic implementation or adjustment of these features. These variables in turn combine with user-related characteristics such as age, degree of hearing loss, word recognition ability, cognitive capacity and more.

References

Foo, C., Rudner, M., & Ronnberg, J. (2007). Recognition of speech in noise with new hearing instrument compression release settings requires explicit cognitive storage and processing capacity. Journal of the American Academy of Audiology 18, 618-631.

Hallgren, M., Larsby, B. & Arlinger, S. (2006). A Swedish version of the hearing in noise test (HINT) for measurement of speech recognition. International Journal of Audiology 45, 227-237.

Hick, C. B., & Tharpe, A. M. (2002). Listening effort and fatigue in school-age children with and without hearing loss. Journal of Speech Language and Hearing Research 45, 573–584.

Humes, L. (2007). The contributions of audibility and cognitive factors to the benefit provided by amplified speech to older adults. Journal of the American Academy of Audiology 18, 590-603.

Lunner, T. (2003). Cognitive function in relation to hearing aid use. International Journal of Audiology 42, (Suppl. 1), S49-S58.

Lunner, T., Rudner, M. & Ronnberg, J. (2009). Cognition and hearing aids. Scandinavian Journal of Psychology 50, 395-403.

Macken, W.J., Phelps, F.G. & Jones, D.M. (2009). What causes auditory distraction? Psychonomic Bulletin and Review 16, 139-144.

McCoy, S.L., Tun, P.A. & Cox, L.C. (2005). Hearing loss and perceptual effort: downstream effects on older adults’ memory for speech. Quarterly Journal of Experimental Psychology A, 58, 22-33.

Picou, E.M., Ricketts, T.A. & Hornsby, B.W.Y. (2013). How hearing aids, background noise and visual cues influence objective listening effort. Ear and Hearing 34 (5).

Ronnberg, J. (2003). Cognition in the hearing impaired and deaf as a bridge between signal and dialogue: a framework and a model. International Journal of Audiology 42 (Suppl. 1), S68-S76.

Ronnberg, J., Rudner, M. & Foo, C. (2008). Cognition counts: A working memory system for ease of language understanding (ELU). International Journal of Audiology 47 (Suppl. 2), S99-S105.

Rudner, M., Ronnberg, J. & Lunner, T. (2011). Working memory supports listening in noise for persons with hearing impairment. Journal of the American Academy of Audiology 22, 156-167.

Sorqvist, P. & Ronnberg, J. (2012). Episodic long-term memory of spoken discourse masked by speech: What role for working memory capacity? Journal of Speech Language and Hearing Research 55, 210-218.

Are you prescribing an appropriate MPO?

Effect of MPO and Noise Reduction on Speech Recognition in Noise

Kuk, F., Peeters, H., Korhonen, P. & Lau, C. (2010). Effect of MPO and noise reduction on speech recognition in noise. Journal of the American Academy of Audiology, submitted November 2010.

This editorial discusses the clinical implications of an independent research study. The original work was not associated with Starkey Laboratories and does not reflect the opinions of the original authors.

A component of clinical best practice would suggest that clinicians determine a patient’s uncomfortable listening levels in order to prescribe the output limiting characteristics of a hearing aid (Hawkins et al., 1987). The optimal maximum power output (MPO) should be based on two goals: preventing loudness discomfort and avoiding distorted sound quality at high input levels. The upper limit of a prescribed MPO must allow comfortable listening; less consideration is given to the consequences that under prescribing MPO might have on hearing aid and patient performance.

There are two primary concerns related to the acceptable lower MPO limit: saturation and insufficient loudness. Saturation occurs when the input level of a stimulus plus gains applied by the hearing aid exceed the MPO, causing distortion and temporal smearing (Dillon & Storey, 1998). This results in a degradation of speech cues and a perceived lack of clarity, particularly in the presence of competing noise. Similarly, insufficient loudness reduces the availability of speech cues. There are numerous reports of subjective degradation of sound when MPO is set lower than prescribed levels, particularly in linear hearing instruments (Kuk et al., 2008; Storey et al., 1998; Preminger, et al., 2001). There is not yet consensus on whether low MPO levels also cause objective degradation in performance.

The purpose of the study described here was to determine if sub-optimal MPO could affect speech intelligibility in the presence of noise, even in a multi-channel, nonlinear hearing aid. Furthermore, the authors examined if gain reductions from a noise reduction algorithm could mitigate the detrimental effects of the lower MPO. The authors reasoned that a reduction in output at higher input levels, via compression and noise reduction, could reduce saturation and temporal distortion.

Eleven adults with flat, severe hearing losses participated in the reviewed study. Subjects were fitted bilaterally with 15-channel, wide dynamic range compression, behind-the-ear hearing aids. Microphones were set to omnidirectional and other than noise reduction, no special features were activated during the study. Subjects responded to stimuli from the Hearing in Noise Test (HINT, Nilsson et al., 1994) presented at a 0-degree azimuth angle in the presence of continuous speech-shaped noise. The HINT stimuli yielded reception thresholds for speech (RTS) scores for each test condition.

Test conditions included two MPO prescriptions: the default MPO level (Pascoe, 1989) and 10dB below that level. The lower setting was chosen based on previous work that reported an approximately 18dB acceptable MPO range for listeners with severe hearing loss  (Storey et al., 1998). MPOs set at 10dB below default would therefore be likely to approach the low end of the acceptable range, resulting in perceptual consequences. Speech-shaped noise was presented at two levels: 68dB and 75dB. Testing was done with and without digital noise reduction (DNR).

Analysis of the HINT RTS scores yielded significant main effects of MPO and DNR, as well as significant interactions between MPO and DNR, and DNR and noise level. There was no significant difference between the two noise level conditions. Subjects performed better with the default MPO setting versus the reduced MPO setting. The interaction between the MPO and DNR showed that subjects’ performance in the low-MPO condition was less degraded when DNR was activated. These findings support the authors’ hypotheses that reduced MPO can adversely affect speech discrimination and that noise reduction processing can at least partially mitigate these adverse effects.

Prescriptive formulae have proven to be reasonably good predictors of acceptable MPO levels (Storey et al., 1988; Preminger et al., 2001). In contrast, there is some question as to the value of clinical UCL testing prior to fitting, especially when validation with loudness measures is performed after the fitting (Mackersie, 2006). Improper instruction for the UCL task may yield inappropriately low UCL estimates, resulting in compromised performance and sound quality. The authors of the current paper recommend following prescriptive targets for MPO and conducting verification measures after the fitting, such as real-ear saturation response (RESR) and subjective loudness judgments.

Another scenario, and an ultimately avoidable one, involves individuals who have been fitted with inappropriate instruments for their loss, usually because of cosmetic concerns. It is unfortunately not so unusual for some individuals with severe hearing losses to be fitted with RIC or CIC instruments because of their desirable cosmetic characteristics. Smaller receivers will likely have MPOs that are too low for hearing aid users with severe hearing loss. Many hearing-aid users may not realize they are giving anything up when they select a CIC or RIC and may view these styles as equally appropriate options for their loss. The hearing aid selection process must therefore be guided by the clinician; clients should be educated about the benefits and limitations of various hearing aid options and counseled about the adverse effects of under-fitting their loss with a more cosmetically appealing option.

The results of the current study are important because they illuminate an issue related to hearing aid output that might not always be taken into clinical consideration. MPO settings are usually thought of as a way to prevent loudness discomfort, so the concern is to avoid setting the MPO too high. Kuk and his colleagues have shown that an MPO that is too low could also have adverse effects and have provided valuable information to help clinicians select appropriate MPO settings. Additionally, their findings show objective benefits and support the use of noise reduction strategies, particularly for individuals with reduced dynamic range due to severe hearing loss or tolerance issues. Of course their findings may not be generalizable to all multi-channel compression instruments, with the wide variety of compression characteristics that are available, but they present important considerations that should be examined in further detail with other instruments.

References

ANSI (1997). ANSI S3.5-1997. American National Standards methods for the calculation of the speech intelligibility index. American National Standards Institute, New York.

Dillon, H. & Storey, L. (1998). The National Acoustic Laboratories’ procedure for selecting the saturation sound pressure level of hearing aids: theoretical derivation. Ear and Hearing 19(4), 255-266.

Hawkins, D., Walden, B., Montgomery, A. & Prosek, R. (1987). Description and validation of an LDL procedure designed to select SSPL90. Ear and Hearing 8, 162-169.

Kuk , F., Korhonen, P., Baekgaard, L. & Jessen, A. (2008). MPO: A forgotten parameter in hearing aid fitting. Hearing Review 15(6), 34-40.

Kuk et al., (2010). Effect of MPO and noise reduction on speech recognition in noise. Journal of the American Academy of Audiology, submitted November 2010, fast track article.

Kuk, F. & Paludan-Muller, C. (2006). Noise management algorithm may improve speech intelligibility in noise. Hearing Journal 59(4), 62-65.

Mackersie, C. (2006). Hearing aid maximum output and loudness discomfort: are unaided loudness measures needed? Journal of the American Academy of Audiology 18 (6), 504-514.

Nilsson, M., Soli, S. & Sullivan, J. (1994). Development of the Hearing in Noise Test for the measurement of speech reception thresholds in quiet and in noise. Journal of the Acoustical Society of America 95(2), 1085-1099.

Pascoe, D. (1989). Clinical measurements of the auditory dynamic range and their relation to formulae for hearing aid gain. In J. Jensen (Ed.), Hearing Aid Fitting: Theoretical and Practical Views. Proceedings of the 13th Danavox Symposium. Copenhagen: Danavox, pp. 129-152.

Preminger, J., Neuman, A. & Cunningham, D. (2001). The selection and validation of output sound pressure level in multichannel hearing aids. Ear and Hearing 22(6), 487-500.

Storey, L., Dillon, H., Yeend, I. & Wigney, D. (1998). The National Acoustic Laboratories, procedure for selecting the saturation sound pressure level of hearing aids: experimental validation. Ear and Hearing 19(4), 267-279.

Reviewing the benefits of open-fit hearing aids

Article of interest:

Unaided and Aided Performance with a Directional Open-Fit Hearing Aid

Valente, M., and Mispagel, K.M. (2008)

This editorial discusses the clinical implications of an independent research study. The original work was not associated with Starkey Laboratories and does not reflect the opinions of the authors. 

With the continued popularity of directional microphone use in open-fit and receiver-in-canal (RIC) hearing aids, there has been increasing interest in evaluating their performance in noisy environments. A number of studies have investigated the performance of directional, open-fit BTEs in laboratory conditions. (Valente et al., 1995; Ricketts, 2000a; Ricketts, 2000b). Some have evaluated directional microphone performance in real-life or simulated real-life noise environments (Ching et al, 2009). In the current study, the authors compared performance in omnidirectional, directional and unaided conditions using RIC instruments in R-SpaceTM (Revitt et al, 2000) recorded restaurant noise. Their goal was to obtain more externally valid results by using real-life noise in a controlled, laboratory setting.

The R-SpaceTM method involved recordings of real restaurant noise from an 8-microphone, circular array. For the test conditions, these recordings were presented through an 8-speaker, circular array to simulate the conditions in the busy restaurant. One important factor that distinguishes this study from most others is that the subjects listened to speech stimuli in the presence of noise from all directions, including the front. At the time of this study only a few other studies had tested directional microphone performance in the presence of multiple noise sources, including frontal (Ricketts, 2000a; Ricketts, 2001; Bentler et al., 2004).

The authors recruited 26 adults with no prior hearing aid experience for the study. They were fitted with binaural receiver-in-canal (RIC) instruments. The instruments were programmed without noise reduction processing and with independent omnidirectional and directional settings. Subjects were counseled on use and care of the instruments, including proper use of omnidirectional and directional programs. They returned for follow-up adjustments one week after their fitting then used their instruments for four weeks before returning for testing. Subjects were given the opportunity to either purchase the hearing aids after the study at a 50% discount or receive a $200 payment for participation.

Hearing in Noise Test (HINT) (Nilsson et al., 1994) sentence reception thresholds were obtained to evaluate sentence perception in the uncorrelated R-Space noise. The Abbreviated Profile of Hearing Aid Benefit (APHAB) (Cox & Alexander, 1995) was also administered to evaluate perceived benefit from the instruments in the study. Four APHAB subscales were evaluated independently:

- Ease of communication (EC)
- Reverberation (RV)
- Background noise (BN)
- Aversiveness to loud sounds (AV)

The authors found that subjects’ performance in the directional condition was significantly better than both omnidirectional and unaided conditions. The omnidirectional condition was not significantly better than unaided; in fact results were slightly worse than those obtained in the unaided condition.

For the APHAB results, the authors found that on the EC, RV and BV subscales, aided scores were significantly better than unaided scores. Perhaps not surprisingly, the AV score, which evaluates “aversiveness to noise” was worse in the aided conditions. The aided results combined omnidirectional and directional conditions, so it is possible that aversion to noise in omnidirectional conditions was greater than the directional conditions. However, this was not specifically evaluated in the current study.

The authors pointed out that their directional benefit, which on average was 1.7dB, was lower than those found in other studies of open-fit or RIC hearing instruments (Ricketts, 2000b; Ricketts, 2001; Bentler, 2004; Pumford et al., 2000). However, they mention that most of those studies did not use frontal noise sources in their arrays. Frontal noise sources should have obvious detrimental effects on directional microphone performance, so it is likely that the speaker arrangement in the current study affected the measured directional improvement. At the time of this publication one other study had been conducted using the R-SpaceTM restaurant noise (Compton-Conley et al 2004). They found mean directional benefits of 3.6 to 5.8 dB, but their subjects had normal hearing and the hearing aids they used were not an open-fit design and were very different from the ones in the current study..

Clinicians can gain a number of important insights from Valente and Mispagel’s study. First and foremost, directional microphones are likely to provide significant benefits for users of RIC hearing aids. At the time of publication, the authors noted that directional improvement should be studied in order to warrant the extra expense of adding directional microphones to an open-fit hearing aid order. However, most of today’s open-fit and RIC instruments already come standard with directional microphones, many of which are automatically adjustable. So there is no need to justify the use of directional microphones on a cost basis, as they usually add nothing to the hearing aid purchase price.

This study provided more evidence for directional benefit in noise, but further work is needed to determine performance differences between directional and omnidirectional microphones in quiet conditions. Dispensing clinicians should always order instruments that have omnidirectional and directional modes, whether manually or automatically adjustable. This helps ensure that the instruments will perform optimally in most situations. Even instruments with automatically adjustable directional microphones often have push-buttons that allow us to give patients additional programs. For example, a manually accessible, directional program, perhaps with more aggressive noise reduction, offers the user another option for excessively noisy situations.

The current study obtained slightly reduced directional effects compared to other studies that tested subjects in speaker arrays without frontal noise sources. This underscores the importance of counseling patients about proper positioning when using directional settings. In general, patients should understand that they will be better off when they can put as much noise behind them as possible. But, it is also important to ensure that patients have reasonable expectations about directional microphones. They must understand that the directional microphone will help them focus on conversation in front of them, but will not completely remove competing noise behind them. Patients must also understand that omnidirectional settings are likely to offer no improvement in noise and might even be a detriment to speech perception in some noisy environments.

Subjects in Valente and Mispagel’s study were offered the opportunity to purchase their hearing instruments at a 50% discount after the study’s completion. Only 8 of the 26 subjects opted to do so. Of the remaining subjects, 3 reported that the perceived benefit was not enough to justify the purchase, whereas 15 subjects did not report any significant perceived benefit. This leads to another important point about patient counseling.

The subjects in this study, like most candidates for open-fit or RIC instruments, had normal low-frequency hearing. Therefore, they may have had less of a perceived need for hearing aids in the first place. It is important for audiologists to discuss realistic expectations and likely hearing aid benefits with patients in detail at the hearing aid selection appointment, before hearing aids are ordered. Patients who are unmotivated or do not perceive enough need for hearing assistance will ultimately be less likely to perceive significant benefit from their hearing aids. This is particularly true in everyday clinical situations, in which patients are not typically offered a 50% discount and will have to factor financial constraints into their decisions. For most open-fit or RIC candidates, their motivation and perceived handicap will be related to their lifestyle: their social activities, employment situation, hobbies, etc. Because a patient who has a less than satisfying experience with hearing aids may be reluctant to pursue them again in the future, it is critical for the clinician to help them establish realistic goals early on, before hearing aid options are discussed.

References
Bentler, R., Egge, J., Tubbs, J., Dittberner, A., and Flamme, G. (2004). Quantification of directional benefit across different polar response patterns. Journal of the American Academy of Audiology 15(9), 649-659.

Ching, T.C., O’Brien, A., Dillon, H., Chalupper, J., Hartley, L., Hartley, D., Raicevich, G., and Hain, J. (2009). Journal of Speech, Language and Hearing Research 52, 1241-1254.

Compton-Conley, C., Neuman, A., Killion, M., and Levitt, H. (2004). Performance of directional microphones for hearing aids: real world versus simulation. Journal of the American Academy of Audiology 15, 440-455.

Cox, R.M. and Alexander, G.C. (1995). The abbreviated profile of hearing-aid benefit. Ear and Hearing 16, 176-183.

Nilsson, M., Soli, S. and Sullivan, J. (1994). Development of the hearing in noise test for the measurement of speech reception thresholds in quiet and in noise. Journal of the Acoustical Society of America 95, 1085-1099.

Pumford, J., Seewald, R,. Scollie, S. and Jenstad, L. (2000). Speech recognition with in-the-ear and behind-the-ear dual microphone hearing instruments. Journal of the American Academy of Audiology 11, 23-35.

Revit, L., Schulein, R., and Julstrom, S. (2002). Toward accurate assessment of real-world hearing aid benefit. Hearing Review 9, 34-38, 51.

Ricketts, T. (2000a). The impact of head angle on monaural and bilateral performance with directional and omnidirectional hearing aids. Ear and Hearing 21, 318-329.

Ricketts, T. (2000b). Impact of noise source configuration on directional hearing aid benefit and performance. Ear and Hearing 21, 194-205.

Ricketts, T., Lindley, G., and Henry, P. (2001). Impact of compression and hearing aid style on directional hearing aid benefit and performance. Ear and Hearing 22, 348-360.

Valente, M., Fabry, D., and Potts, L. (1995). Recognition of speech in noise with hearing aids using a dual microphone. Journal of the American Academy of Audiology 6, 440-449.

Valente, M., & Mispagel, K.M. (2008). Unaided and aided performance with a directional open-fit hearing aid. International Journal of Audiology, 47, 329-336.

The effect of digital noise reduction on listening effort: an article review

This article marks the first in a monthly series for StarkeyEvidence.com.

Each month scholarly journals publish articles on a wide array of topics. Some of these valuable articles and their useful conclusions never reach professionals in the clinical arena. The aim of these entries is to discuss research findings and their implications for hearing professionals living a daily clinical routine. Some of these topics may have general clinical relevance, while other may target specific aspects of hearing aids and their application.

This first discussion revolves around an article by authors Sarampalis, Kalluri, Edwards, and Hafter entitled “Objective measures of listening effort: Effects of background noise and noise reduction”. In this 2009 study, the authors pursue the sometimes elusive benefits of digital noise reduction. A review of past literature suggests that digital noise reduction, as implemented in hearing aids, benefits patients through improved sound quality, ease of listening and a possible perceived improvement in speech understanding. Significant improvements in speech understanding are, however, not a routinely observed benefit of digital noise reduction and some studies have shown significant decreases in speech understanding with active digital noise reduction.

In a 1992 article, authors Hafter and Schlauch suggest that noise reduction may lighten a patient’s cognitive load, essentially freeing resources for other tasks. To better understand the proposed effect, imagine driving a car in an unfamiliar area. It’s common for drivers to turn their stereo down, or off, when driving in a demanding situation. This is beneficial, not because music affects driving ability, but because the additional auditory input is distracting, effectively increasing the driver’s cognitive load. By removing the distraction of the stereo, more cognitive resources are freed and the ability to focus, or pay attention to the complex task of driving is improved.

In order to better understand how digital noise reduction may affect attention and cognitive load, two experiments were completed. In the first experiment, research participants were asked to repeat the last word of sentences presented in a background of noise. After eight sentences the listener attempted to repeat as many of the target words as they could. The sentence material contained both high-context and no-context conditions, for example:

High context: A chimpanzee is an ape

No context: She might have discussed the ape

In the second experiment listeners were asked to judge if a random number between one and eight was even or odd, while at the same time listening to and repeating sentences presented in a background of noise. Both experiments incorporated a dual-task paradigm: the first asked participants to repeat select words presented in noise, while also remembering these words for later recall. The second required participants to repeat an entire sentence, presented in noise, while also completing a complex visual task.

Highlights from experiment one show:

  • performance in all conditions decreased as the signal-to-noise ratio became more difficult;
  • overall performance in the no-context conditions was lower than in the high-context conditions;
  • a comparison between performance with and without digital noise reduction showed a significant improvement in recall ability with digital noise reduction

Highlights from experiment two show:

  • performance in all conditions decreased as the signal-to-noise ratio became more difficult;
  • reaction times increased with decreased signal-to-noise ratio;
  • at -6 dB SNR, reaction times were significantly improved with digital noise reduction

The findings of this study show that the cognitive demands of non-auditory tasks, such as visual and memory tasks, inhibit the ability of a person to understand speech-in-noise. In other words, secondary tasks make speech understanding more difficult. Additionally, digital noise reduction algorithms can reduce cognitive effort under adverse listening conditions. The authors discuss the value of using cognitive measures in hearing aid research and speculate that directional microphones may provide a cognitive benefit as well.

The clinical implications of this study suggest that patients may find benefits of wearing hearing aids that go beyond improved speech audibility. Modern signal processing may provide benefits that are only now being understood. For instance, a patient may report that hearing aids have made listening easier, that their new hearing instruments seem to suppress noise more than the old ones, but routine evaluation of speech understanding may not show significant differences between the two hearing aids.

Hearing aid success and benefit has traditionally been defined with the results of speech testing, or questionnaires. If advanced technology can ease the task of listening, patients may be receiving benefits from their hearing aids that we are not currently prepared to evaluate in the clinic. Hopefully, work in this area will continue, increasing our understanding of the role that cognition plays in the success of the hearing aid wearer.

References:
Bentler, R., Wu, Y., Kettle, J., & Hurtig, R. (2008). Digital Noise Reduction: Outcomes from laboratory and field studies. International Journal of Audiology, 47:8, 447-460.

Hafter, E. R., & Schlauch, R. S. (1992). Cognitive factors and selection of auditory listening bands. In A. Dancer, D. Henderson, R. J. Salvi, & R. P. Hammernik ( Eds.), Noise-induced hearing loss (pp. 303–310). Philadelphia: B.C. Decker.

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