Normative Data for a Rapid, Automated Test of Spatial Release From Masking
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Published on: June 26, 2013
Kasey M Jakien1,2, Frederick J Gallun1,2
1National Center for Rehabilitative Auditory Research, VA Portland Health Care System, Department of Veterans Affairs, OR.
Purpose:
The purpose of this study is to report normative data and predict thresholds for a rapid test of spatial release from masking for speech perception. The test is easily administered and has good repeatability, with the potential to be used in clinics and laboratories. Normative functions were generated for adults varying in age and amounts of hearing loss.
Method:
The test of spatial release presents a virtual auditory scene over headphones with 2 conditions: colocated (with target and maskers at 0°) and spatially separated (with target at 0° and maskers at ± 45°). Listener thresholds are determined as target-to-masker ratios, and spatial release from masking (SRM) is determined as the difference between the colocated condition and spatially separated condition. Multiple linear regression was used to fit the data from 82 adults 18-80 years of age with normal to moderate hearing loss (0-40 dB HL pure-tone average [PTA]). The regression equations were then used to generate normative functions that relate age (in years) and hearing thresholds (as PTA) to target-to-masker ratios and SRM.
Results:
Normative functions were able to predict thresholds with an error of less than 3.5 dB in all conditions. In the colocated condition, the function included only age as a predictive parameter, whereas in the spatially separated condition, both age and PTA were included as parameters. For SRM, PTA was the only significant predictor. Different functions were generated for the 1st run, the 2nd run, and the average of the 2 runs. All 3 functions were largely similar in form, with the smallest error being associated with the function on the basis of the average of 2 runs.
Conclusion:
With the normative functions generated from this data set, it would be possible for a researcher or clinician to interpret data from a small number of participants or even a single patient without having to first collect data from a control group, substantially reducing the time and resources needed.
Supplemental Material:
https://doi.org/10.23641/asha.7080878.
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