Feedback reduction system influence on additional gain before feedback and maximum stable gain in open-fitted hearing aids. (3rd October 2018)

• Record Type: Journal Article
• Authors: Marcrum, Steven C.; Picou, Erin M.; Bohr, Christopher; Steffens, Thomas
• Is Part Of: International journal of audiology. Volume 57:Number 10(2018)
• Page Start: 737
• Page End: 745
• Publication Date: 2018-10-03
• Subjects: Assistive technology -- hearing aids -- phase cancellation -- sound quality; Audiology -- Periodicals; Hearing disorders -- Periodicals; Deafness -- Prevention -- Periodicals; Hearing Disorders -- Periodicals; Hearing -- Periodicals; 617.8
• DOI: 10.1080/14992027.2018.1487088
• Languages: English
• ISSNs: 1499-2027

Abstract

Abstract: Objective: The primary purpose of this study was to update existing data on additional gain before feedback and maximum stable gain in commercially available, open-fit hearing instruments. A secondary purpose was to evaluate ratings of sound quality with feedback reduction systems active. Design: Additional gain before feedback, maximum stable gain and subjective sound quality ratings were obtained for six commercially available hearing instruments utilising modern feedback reduction systems. Study sample: Twenty adults (22–46 years) with normal hearing participated in gain measurement testing. Thirty adults (22–39 years) with normal hearing provided ratings of sound quality. Results: Mean additional gain before feedback for 2000–4000 Hz ranged from 5 to 16 dB across manufacturers. Mean maximum stable gain in the same frequency region ranged from 25 to 35 dB across manufacturers. However, meaningful performance differences between participants within each given manufacturer were also identified. Sound quality ratings were not related to the type of feedback reduction algorithm. Conclusions: AGBF and MSG continue to vary significantly both across manufacturers as well as individual ears within a given manufacturer. User satisfaction and performance with hearing aids might be improved by identifying the feedback reduction system optimal for the individual patient.