Music sound quality assessment in bimodal cochlear implant users – toward improved hearing aid fitting

The use of cochlear implants (CI) is the common treatment to counteract severe-profound hearing loss. CI often allow reasonable speech understanding but are generally limited in terms of spectro-temporal resolution. Many CI recipients use a hearing aid (HA) on the non-implanted ear (so called bimodal patients) that complements the electrical stimulation of the CI by providing acoustical fine structure information. Amongst others, this might be especially beneficial for music appraisal. However, it is not clear how the HA should be fitted in conjunction with the CI in order to provide the best sound quality. The purpose of this study was to vary different fitting parameters of the HA systematically and to determine the resulting music sound quality. To this end, a master hearing aid was used in order to have controlled access to the different parameters. Three different music excerpts (pop with and without vocals, classic) were presented to 13 bimodally fitted CI users and the sound quality was assessed using the “multiple-stimulus with hidden reference and anchor” (MUSHRA) test. Since the goal was to gain information on possible improvement of fitting, a complete retest was performed and individual reliability of the assessments was determined by the eGauge method. It could be shown that most of the listeners were able to provide reliable sound quality judgements. In terms of HA fitting it turned out that changing compression and varying low frequency gain had a significant effect compared to a standard prescriptive fitting based on DSL v5.0. However, especially the effect of changing low frequency gain depended on the music excerpts presented, since pop music with vocals revealed the largest effect. The study gives evidence that hearing aid fitting can be optimized relative to a standard prescriptive rule in order to improve music sound quality in bimodal CI users. Moreover, the method might be helpful in a clinical setting to determine the best fitting based on individual results.