Large scale objective assessment of preferred gain and ... · Large scale objective assessment of...

Large scale objective assessment of preferred gain and frequency response for multiband compression hearing aids

Adrian Lister, M.Sc. & Drew Dundas, Ph.D.

Introduc9on

Background

Methods

Results Results

References

! Hearing aid fitting targets are typically generated based on audiometric threshold testing results. While the underlying rationales of the prescriptive algorithms may differ, (e.g., overall or specific loudness normalization, loudness equalization, maximization of the speech intelligibility index, and/or preservation of high-level input comfort) the overarching goals are similar. Those goals are to provide a set of fitting targets that lead to improved speech understanding, maintain comfort, and result in acceptable sound quality and spontaneous acceptance of the hearing aid.

! Prescriptions such as the National Acoustic Laboratories Non-Linear (NAL-NL1 and -NL2) (Byrne et al, 2001; Keidser et al., 2011) and the Desired Sensation Level (DSLv5) (Scollie et al, 2005) approaches have been well validated in the field, as fittings have been conducted on millions of users. Despite this level of validation, it is commonly accepted that patients will request deviations from fitting targets to address individual perceptions and manage sound quality preferences.

! This study sought to investigate the results of subjective fine-tuning by the hearing healthcare practitioner (HHP) after the initial calculation of the fitting by four prescriptive targets. A review of data stored on devices that were received for repair and/or inspection was conducted. Modeled ear canal responses achieved in the initial target match were compared to fine-tuned settings retained after at least two follow up visits. The purpose of this process was to determine the ways in which gain/frequency responses calculated by the NAL-R, NAL-NL1, DSL-v5 and eSTAT fitting prescriptions converged or differed after subjective fine-tuning.

! Keidser and Dillon (2003) demonstrated that individuals with SNHL exhibit widely varying preferences for overall gain, and that the preferred deviation from the prescriptive target is not entirely predictable based on the severity of the audiogram. This study, however, looked only at overall gain differences, and did not allow variation of the frequency response of the devices or investigate the frequency range over which audibility was attained. As such, it is possible, if not likely, that the underlying assumptions of the various fitting rationales, including loudness equalization & normalization, are in fact unlikely to be achieved after modification to the fitting.

! Other authors (e.g., Keidser et al, 2003; Bretz, 2006; Lutzen, 2005) observe that significant differences exist between the gain and output prescribed by various fitting algorithms. These differences exist due to the differing assumptions and goals of each fitting approach.

! In previous work, the differences in the computed target response of the hearing aid at various input levels have been investigated. These investigations have often been conducted to lend credence to the validity of a particular algorithm. This study, however, instead looks to compare the modeled real ear responses achieved with various fitting algorithms across a large number of individuals with common sensorineural hearing loss (SNHL) configurations and severities. This builds upon the work of previous authors by investigating the similarities and differences that occur in hearing aid fittings after subjective fine tuning, regardless of the initial fitting algorithm used to calculate fitting targets.

! The four most commonly identified audiograms from the cluster analysis are presented in figure 1. Modeled responses were compared to the final frequency response contained within each device as a function of the fitting target selected for the fitting, for soft, average and loud speech shaped inputs (50, 65 and 80dB SPL, respectively). These data are represented at the audiometric frequencies .5, 1, 2 & 4KHz in Figures 2, 3, 4 & 5.

! For average input levels (i.e., 65dB SPL speech) little difference in median achieved response was observed across fitting targets for a given hearing loss. In the great majority of cases, median achieved responses were adjusted toward the grand mean, suggesting a tendency toward a single frequency shaping. This observation is interesting in that the initial individual prescriptive targets varied substantially due to the differing goals of each. Despite the central tendency of the median responses however, the variability in achieved response is quite large, belying the idea that a single prescriptive algorithm could truly be ‘one size fits all’ without individualized fine tuning. Fittings implemented for more severe losses showed greater variability in achieved output than those implemented for milder hearing losses.

Audiogram 1: ! For average input responses, no significant difference between median achieved responses were observed. Median soft responses were below target for all prescriptions except DSLv5. For loud inputs, median responses tended to decrease on the order of 2-6 dB relative to the prescribed target. These decreases occurred across frequencies, with responses converging toward the grand mean. The median response achieved with NAL-R, however, was significantly more intense than the other prescriptions despite substantial decreases in output relative to the initial fitting target.

Audiogram 2: ! Median responses to average level inputs were observed to be very close to target responses across prescriptions. For soft inputs, median responses were below target values for all fittings except DSLv5. For loud inputs there was a tendency to decrease output relative to the prescriptive target, and responses tended to converge for all prescriptions with the exception of NAL-R.

Audiogram 3: ! For average inputs, achieved outputs were virtually identical across prescriptions, tending to vary in the direction of the grand mean. For soft inputs, median responses tended away from the target toward the grand mean. At this input level, DSLv5 fittings resulted in significantly higher output than the other prescriptions. For loud inputs, achieved responses were very similar across prescriptions, with the exception of NAL-R fittings. In this case, outputs were substantially higher than those of the other prescriptions.

Audiogram 4: ! For average inputs, achieved outputs tended to vary towards the grand mean. At soft input levels, responses also tended toward the grand mean, although median deviation from target was insufficient to achieve a similar response in the high frequencies. For loud input levels, changes from the prescription were smaller than in other audiograms, but tended to shift to lower output levels.

Byrne D. Dillon H. Ching T. Katsch R. Keidser G. (2001). NAL-NL1 procedure for fitting nonlinear hearing ! aids: characteristics and comparisons with other procedures. Journal of the American Academy of ! Audiology, 12(1):37-51.Keidser G and Dillon H (2007). What's new in prescriptive fittings Down Under? In Seewald R (Ed.), ! Hearing Care for Adults. (pp.133-142).Keidser, G., Dillon, H., Flax, M., Ching, T. & Brewer, S. (2011). The NAL-NL2 prescription procedure. Audiology Research 1 (e24), 88-90.

Scollie, S., Seewald, R., Cornelisse, L., Moodie, S., Bagatto, M., et al. 2005. The Desired Sensation ! Level Multistage Input/Output Algorithm. Trends in Amplif, 4(9), 159–197.Keidser G. Brew C. Peck A. (2003). How proprietary fitting algorithms compare to each other and to ! some generic algorithms. The Hearing Journal, 56(3):28-38.Lutzen M. (no date). How much fine tuning does a modern hearing system require? Phonak Focus. ! Retrieved May 6, 2012, from http://www.phonak.com/com_028-0610-xx_focus_35.pdf

Research Ques9ons1. What changes from the initial fitting target are implemented by the hearing healthcare provider?

2. What is the typical range of adjustments away from the fitting targets?

3. Do implemented changes differ as a function of hearing loss configuration or severity? Fitting target?

! Gain/frequency response data and audiometric data were extracted from unique devices that were received for inspection or repair over a three-year period. Audiometric threshold data read from each device was used to identify the most common audiometric configurations encountered. Rounding up the air conduction thresholds to the nearest 10dB increment at 500, 1000, 2000 & 4000Hz simplified this process. Each set of octave thresholds from 500-4000Hz could then be represented as a four-integer string of the form 30,40,50,60. Cluster analysis suggested that four large clusters existed. These were designated audiograms 1-4 (Figure 1). Audiograms that fit the criteria of these clusters resulted in a sample of 127,061 unique devices.! Some fitting algorithms were significantly more popular than others. This resulted in unequal sample sizes within each audiogram group of devices. Sampling without replacement was performed within each fitting prescription group to arrive at group sizes equal to the number of devices in the group with the smallest number of samples.! Modeled real ear target responses (i.e., modeled REAR) for the audiograms associated with the devices were calculated for the DSL-v5, NAL-NL1, NAL-R and eSTAT (Starkey’s proprietary) algorithms. Input stimuli consisted of speech shaped inputs with overall levels of 50, 65 and 80dB SPL. The modeled responses were compared to the final frequency response contained within each device as a function of the fitting target selected for the fitting. ! Analyses of variance were conducted on the modeled outputs for soft, average and loud inputs, at 0.5, 1, 2 & 4 KHz. Where significant differences in output were detected (p<.01), Tukey honest significant difference post hoc testing was conducted to quantify differences between groups.

Results

Reprints

For Reprints:Snap the QR code, or email:[email protected]

Audiometric Thresholds

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Figure 1. Four sensorineural hearing loss severities and configurations identified by cluster analysis. Thresholds are plotted at 0.5, 1, 2 & 4 KHz. From left; Audiogram 1, 30,40,50,60 (mild sloping to moderate), Audiogram 2, 40,50,60,70 (moderate sloping to moderately severe), Audiogram 3, 60,60,60,60 (flat moderate), Audiogram 4, 60,60,70,80 (Moderate sloping to severe).

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Figure 4: Median predicted REAR by fitting algorithm for n=2864 samples of audiogram 3. Box limits represent upper and lower quartiles. Whiskers indicate ± 1.5x interquartile range. Black bar indicates sample median. Open circles represent outliers. Left to right within each block, response for DSLv5, NAL-NL1, NAL-R and eSTAT. Left to right across blocks, responses at 0.5, 1, 2 & 4 KHz. Top to bottom, soft, average and loud inputs corresponding to speech shaped noise input levels of 50dB, 65 dB & 80 dB. Red lines indicate calculated targets for the audiogram for each fitting algorithm, blue triangles note response grand mean, red stars note overall significant differences in modeled response between fitting methods.

Audiogram 1 Audiogram 2 Audiogram 3 Audiogram 4

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Audiogram 1

Audiogram 2

Audiogram 4

Audiogram 3

Table 1: Significance values (p) from Tukey HSD post hoc tests comparing median responses across DSLv5, NAL-NL1, NAL-R and eSTAT fittings. Responses were compared at each frequency (Left to right, 0.5, 1, 2 & 4 KHz) and input level (top to bottom (soft, average & loud speech). Comparisons resulting in significant differences are highlighted in blue.

•Prescriptive fitting targets are intended as an audiometric threshold-based starting place for hearing aid fitting.

•Each fitting target is based on varying assumptions and goals, including, but not limited to, optimizing audibility of speech level inputs, maximizing the speech intelligibility index, normalizing overall loudness, equalizing specific loudness and/or preserving comfort for loud sounds.

•Parameters including gain, compression and maximum output are calculated based on these assumptions and goals.

•These varying goals result in differing output response levels and shaping across methods.•Hearing aid users often request changes from the prescriptive target, in order to address sound quality and loudness comfort issues.

•When large numbers of hearing aid users with similar audiograms are fit to different fitting targets, the eventual fine-tuned fitting varies significantly from the initial fitting across frequencies and levels.

•Median modeled responses tend to converge towards similar response shaping and predicted response levels.

•Individual variability in achieved response is large, with 50% of modeled responses typically falling into the ± 4-8dB range relative to the initially calculated target.

•This variability may be due to individual acoustic differences in the hearing instruments, ear canal acoustics and/or personal preference as influenced, in part, by prior experience, loudness tolerance and individual loudness growth functions.

•It is clear that individualized subjective and objective fine-tuning remains a necessary part of the hearing aid fitting process.

Discussion

Soft Input! ! 500Hz! 1000Hz! 2000Hz! 4000Hz!(50dB SPL)! Audiogram! DSL! NAL-NL1! NAL-R! eSTAT! DSL! NAL-NL1! NAL-R! eSTAT! DSL! NAL-NL1! NAL-R! eSTAT! DSL! NAL-NL1! NAL-R! eSTAT!

DSL!

1! 1! 0.111! 0.002! 0.001!1`! 0.988! 0.981! 0.756! 1! 0.776! 0.297! 0.436! 1! 0.001! 0.017! 0.014!2! 1! 0.225! 0.011! 0.09! 1! 0! 0.244! 0.328! 1! 0.824! 0.553! 0.879! 1! 0! 0.018! 0.024!3! 1! 0! 0! 0! 1! 0! 0.999! 0.125! 1! 0.053! 0.167! 0.972! 1! 0! 0! 0!4! 1! 0.143! 0.002! 0! 1! 0.003! 0.815! 0.912! 1! 0.986! 0.027! 0.606! 1! 0! 0.076! 0.085!

NAL-NL1!

1! 0.111! 1! 0.569! 0.42! 0.988! 1! 0.897! 0.909! 0.776! 1! 0.037! 0.07! 0.001! 1! 0.891! 0.917!2! 0.225! 1! 0.633! 0.972! 0! 1! 0.029! 0.018! 0.824! 1! 0.133! 0.378! 0! 1! 0.062! 0.045!3! 0! 1! 0.98! 0.957! 0! 1! 0! 0.042! 0.053! 1! 0! 0.148! 0! 1! 0.841! 0.991!4! 0.143! 1! 0.46! 0.083! 0.003! 1! 0.048! 0.026! 0.986! 1! 0.009! 0.395! 0! 1! 0.185! 0.169!

NAL-R!

1! 0.002! 0.569! 1! 0.995! 0.981! 0.897! 1! 0.524! 0.297! 0.037! 1! 0.994! 0.017! 0.891! 1! 0.999!2! 0.011! 0.633! 1! 0.873! 0.244! 0.029! 1! 0.998! 0.553! 0.133! 1! 0.939! 0.018! 0.062! 1! 0.999!3! 0! 0.98! 1! 0.999! 0.999! 0! 1! 0.143! 0.167! 0! 1! 0.061! 0! 0.841! 1! 0.948!4! 0.002! 0.46! 1! 0.795! 0.815! 0.048! 1! 0.996! 0.027! 0.009! 1! 0.392! 0.076! 0.185! 1! 0.999!

eSTAT!

1! 0.001! 0.42! 0.995! 1! 0.756! 0.909! 0.524! 1! 0.436! 0.07! 0.994! 1! 0.014! 0.917! 0.999! 1!2! 0.09! 0.972! 0.873! 1! 0.328! 0.018! 0.998! 1! 0.879! 0.378! 0.939! 1! 0.024! 0.045! 0.999! 1!3! 0! 0.957! 0.999! 1! 0.125! 0.042! 0.143! 1! 0.972! 0.148! 0.061! 1! 0! 0.991! 0.948! 1!4! 0! 0.083! 0.795! 1! 0.912! 0.026! 0.996! 1! 0.606! 0.395! 0.392! 1! 0.085! 0.169! 0.999! 1!

Average Input! ! 500Hz! 1000Hz! 2000Hz! 4000Hz!

(65dB SPL)! Audiogram! DSL! NAL-NL1! NAL-R! eSTAT! DSL! NAL-NL1! NAL-R! eSTAT! DSL! NAL-NL1! NAL-R! eSTAT! DSL! NAL-NL1! NAL-R! eSTAT!

DSL!

1! 1! 0.015! 0.014! 0! 1! 0.949! 0.999! 0.973! 1! 0.999! 0.998! 0.873! 1! 0.191! 0.028! 0.468!2! 1! 0.162! 0.675! 0.097! 1! 0.323! 0.305! 0.024! 1! 0.267! 0.939! 0.999! 1! 0! 0.773! 0.117!3! 1! 0! 0.002! 0! 1! 0.473! 0.031! 0.399! 1! 0.009! 0.147! 0.52! 1! 0.022! 0.878! 0.619!4! 1! 0.448! 0.776! 0.075! 1! 0.064! 0.235! 0.999! 1! 0.99! 0.998! 0.987! 1! 0.001! 0.814! 0.67!

NAL-NL1!

1! 0.015! 1! 0.999! 0.435! 0.949! 1! 0.93! 0.769! 0.999! 1! 0.992! 0.822! 0.191! 1! 0.855! 0.946!2! 0.162! 1! 0.771! 0.995! 0.323! 1! 0.999! 0.661! 0.267! 1! 0.599! 0.261! 0! 1! 0.003! 0.131!3! 0! 1! 0.158! 0.565! 0.473! 1! 0.559! 0.999! 0.009! 1! 0.732! 0.283! 0.022! 1! 0.001! 0.35!4! 0.448! 1! 0.955! 0.785! 0.064! 1! 0.923! 0.066! 0.99! 1! 0.999! 0.924! 0.001! 1! 0! 0.047!

NAL-R!

1! 0.014! 0.999! 1! 0.439! 0.999! 0.93! 1! 0.983! 0.998! 0.992! 1! 0.936! 0.028! 0.855! 1! 0.53!2! 0.675! 0.771! 1! 0.63! 0.305! 0.999! 1! 0.683! 0.939! 0.599! 1! 0.935! 0.773! 0.003! 1! 0.576!3! 0.002! 0.158! 1! 0.004! 0.031! 0.559! 1! 0.638! 0.147! 0.732! 1! 0.875! 0.878! 0.001! 1! 0.205!4! 0.776! 0.955! 1! 0.468! 0.235! 0.923! 1! 0.239! 0.998! 0.999! 1! 0.959! 0.814! 0! 1! 0.186!

eSTAT!

1! 0! 0.435! 0.439! 1! 0.973! 0.769! 0.983! 1! 0.873! 0.822! 0.936! 1! 0.468! 0.946! 0.53! 1!2! 0.097! 0.995! 0.63! 1! 0.024! 0.661! 0.683! 1! 0.999! 0.261! 0.935! 1! 0.117! 0.131! 0.576! 1!3! 0! 0.565! 0.004! 1! 0.399! 0.999! 0.638! 1! 0.52! 0.283! 0.875! 1! 0.619! 0.35! 0.205! 1!4! 0.075! 0.785! 0.468! 1! 0.999! 0.066! 0.239! 1! 0.987! 0.924! 0.959! 1! 0.67! 0.047! 0.186! 1!

Loud Input! ! 500Hz! 1000Hz! 2000Hz! 4000Hz!(80dB SPL)! Audiogram! DSL! NAL-NL1! NAL-R! eSTAT! DSL! NAL-NL1! NAL-R! eSTAT! DSL! NAL-NL1! NAL-R! eSTAT! DSL! NAL-NL1! NAL-R! eSTAT!

DSL!

1! 1! 0.019! 0.056! 0.32! 1! 0.479! 0.977! 0.011! 1! 0.801! 0.172! 0.99! 1! 0.515! 0.959! 0.991!2! 1! 0.277! 0.968! 0.027! 1! 0.998! 0! 0.566! 1! 0.998! 0.008! 0.134! 1! 0.653! 0.364! 0.999!3! 1! 0! 0.97! 0.018! 1! 0.995! 0! 0.275! 1! 0.838! 0! 0.086! 1! 0.161! 0! 0.318!4! 1! 0.075! 0.236! 0.111! 1! 0.584! 0! 0.492! 1! 0.653! 0.001! 0.385! 1! 0.162! 0.037! 0.811!

NAL-NL1!

1! 0.019! 1! 0.98! 0.614! 0.479! 1! 0.257! 0.331! 0.801! 1! 0.018! 0.623! 0.515! 1! 0.242! 0.699!2! 0.277! 1! 0.535! 0.741! 0.998! 1! 0! 0.474! 0.998! 1! 0.013! 0.185! 0.653! 1! 0.029! 0.594!3! 0! 1! 0! 0.013! 0.995! 1! 0! 0.178! 0.838! 1! 0! 0.423! 0.161! 1! 0! 0!4! 0.075! 1! 0! 0.998! 0.584! 1! 0.004! 0.998! 0.653! 1! 0.048! 0.972! 0.162! 1! 0! 0.017!

NAL-R!

1! 0.056! 0.98! 1! 0.836! 0.977! 0.257! 1! 0.002! 0.172! 0.018! 1! 0.299! 0.959! 0.242! 1! 0.858!2! 0.968! 0.535! 1! 0.089! 0! 0! 1! 0.005! 0.008! 0.013! 1! 0.72! 0.364! 0.029! 1! 0.418!3! 0.97! 0! 1! 0.064! 0! 0! 1! 0! 0! 0! 1! 0! 0! 0! 1! 0!4! 0.236! 0! 1! 0! 0! 0.004! 1! 0.007! 0.001! 0.048! 1! 0.136! 0.037! 0! 1! 0.27!

eSTAT!

1! 0.32! 0.614! 0.836! 1! 0.011! 0.331! 0.002! 1! 0.99! 0.623! 0.299! 1! 0.991! 0.699! 0.858! 1!2! 0.027! 0.741! 0.089! 1! 0.566! 0.474! 0.005! 1! 0.134! 0.185! 0.72! 1! 0.999! 0.594! 0.418! 1!3! 0.018! 0.013! 0.064! 1! 0.275! 0.178! 0! 1! 0.086! 0.423! 0! 1! 0.318! 0! 0! 1!4! 0.111! 0.998! 0! 1! 0.492! 0.998! 0.007! 1! 0.385! 0.972! 0.136! 1! 0.811! 0.017! 0.27! 1!

http://www.phonak.com/com_028-0610-xx_focus_35.pdf

http://www.phonak.com/com_028-0610-xx_focus_35.pdf

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Large scale objective assessment of preferred gain and ... · Large scale objective assessment of...

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