Self-Adjusted Amplification Parameters Produce Large Between-Subject Variability and Preserve Speech Intelligibility - PubMed (original) (raw)

Self-Adjusted Amplification Parameters Produce Large Between-Subject Variability and Preserve Speech Intelligibility

Peggy B Nelson et al. Trends Hear. 2018 Jan-Dec.

Abstract

The current study used the self-fitting algorithm to allow listeners to self-adjust hearing-aid gain or compression parameters to select gain for speech understanding in a variety of quiet and noise conditions. Thirty listeners with mild to moderate sensorineural hearing loss adjusted gain parameters in quiet and in several types of noise. Outcomes from self-adjusted gain and audiologist-fit gain indicated consistent within-subject performance but a great deal of between-subject variability. Gain selection did not strongly affect intelligibility within the range of signal-to-noise ratios tested. Implications from the findings are that individual listeners have consistent preferences for gain and may prefer gain configurations that differ greatly from National Acoustic Laboratories-based prescriptions in quiet and in noise.

Keywords: hearing aids; hearing-aid outcomes; self-fit.

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Figures

Figure 1.

Figure 1.

Long-term average spectra of the three restaurant recordings. The steady PB noise had the same long-term spectrum as the PB recording.

Figure 2.

Figure 2.

Mean participant audiograms for left and right ears. The dashed blue lines and dotted red lines indicate 1 standard deviation from mean thresholds for left and right ears, respectively.

Figure 3.

Figure 3.

Examples of insertion gain resulting from self-adjustment in quiet for two subjects (S1 and S18). Black dashed lines indicate insertion gain for the subject’s NAL fit. Solid orange lines are insertion gain resulting from the first self-adjustment in quiet. Dotted blue lines indicate gain resulting from a second self-adjustment in quiet. Data from S1 (upper panel) exemplify pattern of consistency in self-adjustment between repetitions of self-adjustment, while data from S18 (lower panel) reflect common pattern for subjects to reduce high-frequency gain relative to their NAL fit.

Figure 4.

Figure 4.

Insertion gain for NAL fit and self-adjusted fits obtained in quiet. The left panel displays average gain for frequencies up to 1000 Hz, while the right panel displays average gain for frequencies between 1000 and 8000 Hz. Subjects are ordered from left-to-right on the abscissa according to the average high-frequency insertion gain in their NAL fits. Orange and blue triangles indicate, respectively, the average gain resulting from the first and second trials of self-adjustment in quiet.

Figure 5.

Figure 5.

Test–retest histogram for insertion gain in the low- and high-frequency bands. Counts of absolute test–retest differences are shown in blue for the low-frequency band (125–1000 Hz), and in black for the high-frequency band (2000–8000 Hz).

Figure 6.

Figure 6.

Gain deviation from NAL (self-adjusted gain minus NAL gain) for the listening conditions. Positive deviations indicate more insertion gain in the self-adjusted fit than the NAL fit. Negative deviations indicate less gain in the self-adjusted fit than in the NAL fit. Rows of plots correspond to different SNR conditions, while noise environments are indicated by marker shape and color. Gain from self-adjustment was averaged across repetitions within each condition. Subjects are ordered from left-to-right on the abscissa according to the average high-frequency insertion gain in their NAL fits (as in Figure 4).

Figure 7.

Figure 7.

Gain deviation from NAL for individual listeners making self-adjustments in varying levels of noise. Deviations have been averaged across noise environments (within the same SNR) and repetitions. Data from low frequencies are shown in the left column; high frequencies are shown in the right. Data from individual subjects are connected with lines of varying line type; the thick, black line indicates the average deviation from NAL across subjects.

Figure 8.

Figure 8.

IEEE key word recognition achieved using NAL (circles) and self-adjusted (triangles) fits. Large, filled symbols indicate average key word recognition across subjects. Smaller, open symbols are data from individual subjects.

Figure 9.

Figure 9.

Difference in speech recognition performance between self-adjusted and NAL fits plotted with respect to gain deviation from NAL in the low-frequency band (bottom row) and high-frequency band (top row). Each column of panels shows data from a different SNR condition. A positive score difference indicates better performance with the self-adjusted fit than the NAL fit, while a negative score difference (lower on the ordinate) indicates worse performance with the self-adjusted fit.

Figure 10.

Figure 10.

Histogram of IEEE key word score differences (self-adjusted fit minus NAL fit) across all subjects that completed the speech recognition assessment. Data from different SNR conditions are displayed as separate lines.

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