The benefit method: fitting hearing aids in noise
- PMID: 17478965
- DOI: 10.4103/1463-1741.31874
The benefit method: fitting hearing aids in noise
Abstract
The most common complaint among individuals with hearing impairment is the inability to follow a conversation when several people are talking simultaneously, a noisy listening situation which is completely different from the quiet surrounding of the conventional pure tone audiometry used as basis for the hearing aid settings. The purpose of this report was to present important characteristics of the BeneFit Method (BFM), a procedure that fits the hearing aid under simulated conditions of competing speech and also a clinical pilot evaluation study comparing the BFM to the NAL-R recommendations and also to the Logic procedure, a GN resound proprietary fitting algorithm representing a modern digital hearing aid fitting procedure. Speech recognition scores in noise (SRSN) using monosyllabic words presented under different background noise levels were evaluated on 21 randomly selected subjects with hearing impairment. The subjects were fitted with the same type of hearing aid Danalogic 163D according to the BFM procedure as well as the logic procedure, the latter developed and recommended by the manufacturer. A comparison of the SRSN when using the subjects' current hearing aid fitted according to the NAL-R procedure was also made. Only the BFM procedure provided a significant SRSN improvement compared to the unaided condition (P< 0.01) in a signal/speech-noise level of 75/65 dB corresponding to a normal cocktail party condition. Moreover, patients performed significantly higher SRSN when fitted according to the BFM, than when fitted according the Logic or NAL-R procedures. The BFM procedure, which is based on individual and functional detection of hearing thresholds in noise levels corresponding to a cocktail party condition, can improve SRSN significantly. Hearing aids should be fitted under conditions similar to those when the hearing disability is perceived the most, i.e, in an environment with background noise.
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