HYPOTHESIS: When cochlear implant (CI) users are allowed to self-select the "most intelligible" frequency-to-electrode table, some of them choose one that differs from the default frequency table that is normally used in clinical practice. BACKGROUND: CIs reproduce the tonotopicity of normal cochleas using frequency-to-electrode tables that assign stimulation of more basal electrodes to higher frequencies and more apical electrodes to lower frequency sounds. Current audiologic practice uses a default frequency-to-electrode table for most patients. However, individual differences in cochlear size, neural survival, and electrode positioning may result in different tables sounding most intelligible to different patients. No clinical tools currently exist to facilitate this fitting. METHODS: A software tool was designed that enables CI users to self-select a most intelligible frequency table. Users explore a 2-dimensional space that represents a range of different frequency tables. Unlike existing tools, this software enables users to interactively audition speech processed by different frequency tables and quickly identify a preferred one. Pilot testing was performed in 11 long-term, postlingually deaf CI users. RESULTS: The software tool was designed, developed, tested, and debugged. Patients successfully used the tool to sample frequency tables and to self-select tables deemed most intelligible, which for approximately half of the users differed from the clinical default. CONCLUSION: A software tool allowing CI users to self-select frequency-to-electrode tables may help in fitting postlingually deaf users. This novel approach may transform current methods of CI fitting.
HYPOTHESIS: When cochlear implant (CI) users are allowed to self-select the "most intelligible" frequency-to-electrode table, some of them choose one that differs from the default frequency table that is normally used in clinical practice. BACKGROUND: CIs reproduce the tonotopicity of normal cochleas using frequency-to-electrode tables that assign stimulation of more basal electrodes to higher frequencies and more apical electrodes to lower frequency sounds. Current audiologic practice uses a default frequency-to-electrode table for most patients. However, individual differences in cochlear size, neural survival, and electrode positioning may result in different tables sounding most intelligible to different patients. No clinical tools currently exist to facilitate this fitting. METHODS: A software tool was designed that enables CI users to self-select a most intelligible frequency table. Users explore a 2-dimensional space that represents a range of different frequency tables. Unlike existing tools, this software enables users to interactively audition speech processed by different frequency tables and quickly identify a preferred one. Pilot testing was performed in 11 long-term, postlingually deaf CI users. RESULTS: The software tool was designed, developed, tested, and debugged. Patients successfully used the tool to sample frequency tables and to self-select tables deemed most intelligible, which for approximately half of the users differed from the clinical default. CONCLUSION: A software tool allowing CI users to self-select frequency-to-electrode tables may help in fitting postlingually deaf users. This novel approach may transform current methods of CI fitting.
Authors: Jill B Firszt; Laura K Holden; Margaret W Skinner; Emily A Tobey; Ann Peterson; Wolfgang Gaggl; Christina L Runge-Samuelson; P Ashley Wackym Journal: Ear Hear Date: 2004-08 Impact factor: 3.570
Authors: Margaret W Skinner; Darlene R Ketten; Laura K Holden; Gary W Harding; Peter G Smith; George A Gates; J Gail Neely; G Robert Kletzker; Barry Brunsden; Barbara Blocker Journal: J Assoc Res Otolaryngol Date: 2002-02-27
Authors: Mario A Svirsky; Matthew B Fitzgerald; Arlene Neuman; Elad Sagi; Chin-Tuan Tan; Darlene Ketten; Brett Martin Journal: J Am Acad Audiol Date: 2012-06 Impact factor: 1.664
Authors: Robert F Labadie; Jack H Noble; Andrea J Hedley-Williams; Linsey W Sunderhaus; Benoit M Dawant; René H Gifford Journal: Otol Neurotol Date: 2016-02 Impact factor: 2.311
Authors: Mario A Svirsky; Nai Ding; Elad Sagi; Chin-Tuan Tan; Matthew Fitzgerald; E Katelyn Glassman; Keena Seward; Arlene C Neuman Journal: Proc IEEE Int Conf Acoust Speech Signal Process Date: 2013-05
Authors: Chin-Tuan Tan; Mario Svirsky; Abbas Anwar; Shaun Kumar; Bernie Caessens; Paul Carter; Claudiu Treaba; J Thomas Roland Journal: Laryngoscope Date: 2013-04 Impact factor: 3.325
Authors: Daniel E Aguiar; N Ellen Taylor; Jing Li; Daniel K Gazanfari; Thomas M Talavage; J Brandon Laflen; Heidi Neuberger; Mario A Svirsky Journal: Hear Res Date: 2015-09-25 Impact factor: 3.208