Background: The default mapping procedure for electric-acoustic stimulation (EAS) devices uses the cochlear implant recipient's unaided detection thresholds in the implanted ear to derive the acoustic settings and assign the lowest frequency filter of electric stimulation. Individual differences for speech recognition with EAS may be due to discrepancies between the electric frequency filters of individual electrode contacts and the cochlear place of stimulation, known as a frequency-to-place mismatch. Frequency-to-place mismatch of greater than 1/2 octave has been demonstrated in up to 60% of EAS users. Aligning the electric frequency filters via a place-based mapping procedure using postoperative imaging may improve speech recognition with EAS. Methods: Masked sentence recognition was evaluated for normal-hearing subjects (n = 17) listening with vocoder simulations of EAS, using a place-based map and a default map. Simulation parameters were based on audiometric and imaging data from a representative 24-mm electrode array recipient and EAS user. The place-based map aligned electric frequency filters with the cochlear place frequency, which introduced a gap between the simulated acoustic and electric output. The default map settings were derived from the clinical programming software and provided the full speech frequency range. Results: Masked sentence recognition was significantly better for simulated EAS with the place-based map as compared with the default map. Conclusion: The simulated EAS place-based map supported better performance than the simulated EAS default map. This indicates that individualizing maps may improve performance in EAS users by helping them achieve better asymptotic performance earlier and mitigate the need for acclimatization.
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