Fitting hearing aids to individual loudness-perception measures.

OBJECTIVE

The purpose of this study was to compare the prescribed gain, compression ratios, compression thresholds, and the relative predicted speech intelligibility (Speech Intelligibility Index [SII], American National Standards Institute 3.79, proposed) provided by four strategies proposed for selecting hearing aid parameters for low-threshold compression hearing instruments and by a traditional threshold-based hearing aid fitting procedure. The strategies used were Desired Sensation Level Input/Output (DSLTM[i/o]; Cornelisse, Seewald, & Jamieson, 1994), Visual Input-Output Locator Algorithm (VIOLA; Cox, 1994), FIG6 strategy (Killion, Reference Note 2), Ricketts and Bentler strategy (RAB), and a threshold-based hearing aid fitting procedure (National Acoustics Laboratories-Revised [NAL-R]; Byrne & Dillion, 1986). These new strategies have been suggested as alternatives to threshold-based strategies, which do not provide the varying amounts of target gain, as a function of input level, necessary to fit low-threshold compression hearing aids.

DESIGN

The electroacoustic prescriptions and the predicted speech intelligibility were calculated across all five fitting strategies for 20 subjects. The threshold and loudness growth information used for each fitting was reported previously (Ricketts & Bentler, in press).

RESULTS

Comparison across prescriptions revealed that the NAL-R strategy (due to the linear gain provided) prescribed the least gain for low-level inputs and the greatest gain for high-level inputs. Gain comparisons across fitting by loudness (FBL) strategies revealed a more shallow frequency response slope for strategies that require individual measures of loudness growth (RAB, VIOLA) in comparison with strategies that assumed average data (FIG6, DSLTM[i/o]). SII results revealed greater predicted speech intelligibility for the FIG6 and the DSLTM[i/o] compared with the NAL-R, RAB, and VIOLA. These differences were most apparent in noise backgrounds and least evident when loudness differences were minimized.

CONCLUSIONS

It appears that differences in SII scores across the FBL fitting strategies are due, in part, to differences in the loudness of the output signal. It is assumed that differences in high-frequency shaping may also be a factor. These data do not appear to support the use of additional clinical time to obtain individual loudness growth measures. However, due to the fact that SII results are based on average performance, it is difficult to predict whether differences across these fitting strategies would be realized in actual measures of speech intelligibility or sound quality on an individual basis.