Literature DB >> 28806335

A Smartphone Application for Customized Frequency Table Selection in Cochlear Implants.

Daniel Jethanamest1, Mahan Azadpour, Annette M Zeman, Elad Sagi, Mario A Svirsky.   

Abstract

HYPOTHESIS: A novel smartphone-based software application can facilitate self-selection of frequency allocation tables (FAT) in postlingually deaf cochlear implant (CI) users.
BACKGROUND: CIs use FATs to represent the tonotopic organization of a normal cochlea. Current CI fitting methods typically use a standard FAT for all patients regardless of individual differences in cochlear size and electrode location. In postlingually deaf patients, different amounts of mismatch can result between the frequency-place function they experienced when they had normal hearing and the frequency-place function that results from the standard FAT. For some CI users, an alternative FAT may enhance sound quality or speech perception. Currently, no widely available tools exist to aid real-time selection of different FATs. This study aims to develop a new smartphone tool for this purpose and to evaluate speech perception and sound quality measures in a pilot study of CI subjects using this application.
METHODS: A smartphone application for a widely available mobile platform (iOS) was developed to serve as a preprocessor of auditory input to a clinical CI speech processor and enable interactive real-time selection of FATs. The application's output was validated by measuring electrodograms for various inputs. A pilot study was conducted in six CI subjects. Speech perception was evaluated using word recognition tests.
RESULTS: All subjects successfully used the portable application with their clinical speech processors to experience different FATs while listening to running speech. The users were all able to select one table that they judged provided the best sound quality. All subjects chose a FAT different from the standard FAT in their everyday clinical processor. Using the smartphone application, the mean consonant-nucleus-consonant score with the default FAT selection was 28.5% (SD 16.8) and 29.5% (SD 16.4) when using a self-selected FAT.
CONCLUSION: A portable smartphone application enables CI users to self-select frequency allocation tables in real time. Even though the self-selected FATs that were deemed to have better sound quality were only tested acutely (i.e., without long-term experience with them), speech perception scores were not inferior to those obtained with the clinical FATs. This software application may be a valuable tool for improving future methods of CI fitting.

Entities:  

Mesh:

Year:  2017        PMID: 28806335      PMCID: PMC5556943          DOI: 10.1097/MAO.0000000000001409

Source DB:  PubMed          Journal:  Otol Neurotol        ISSN: 1531-7129            Impact factor:   2.311


  20 in total

1.  A new software tool to optimize frequency table selection for cochlear implants.

Authors:  Daniel Jethanamest; Chin-Tuan Tan; Matthew B Fitzgerald; Mario A Svirsky
Journal:  Otol Neurotol       Date:  2010-10       Impact factor: 2.311

2.  Diversity in cochlear morphology and its influence on cochlear implant electrode position.

Authors:  Kim S van der Marel; Jeroen J Briaire; Ron Wolterbeek; Jorien Snel-Bongers; Berit M Verbist; Johan H M Frijns
Journal:  Ear Hear       Date:  2014 Jan-Feb       Impact factor: 3.570

3.  Plasticity in human pitch perception induced by tonotopically mismatched electro-acoustic stimulation.

Authors:  L A J Reiss; C W Turner; S A Karsten; B J Gantz
Journal:  Neuroscience       Date:  2013-10-21       Impact factor: 3.590

4.  A model of incomplete adaptation to a severely shifted frequency-to-electrode mapping by cochlear implant users.

Authors:  Elad Sagi; Qian-Jie Fu; John J Galvin; Mario A Svirsky
Journal:  J Assoc Res Otolaryngol       Date:  2009-09-23

5.  The Relationship Between Insertion Angles, Default Frequency Allocations, and Spiral Ganglion Place Pitch in Cochlear Implants.

Authors:  David M Landsberger; Maja Svrakic; J Thomas Roland; Mario Svirsky
Journal:  Ear Hear       Date:  2015 Sep-Oct       Impact factor: 3.570

6.  Gradual adaptation to auditory frequency mismatch.

Authors:  Mario A Svirsky; Thomas M Talavage; Shivank Sinha; Heidi Neuburger; Mahan Azadpour
Journal:  Hear Res       Date:  2014-11-06       Impact factor: 3.208

7.  Neural adaptation and perceptual learning using a portable real-time cochlear implant simulator in natural environments.

Authors:  Christopher J Smalt; Thomas M Talavage; David B Pisoni; Mario A Svirsky
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2011

8.  Factors affecting open-set word recognition in adults with cochlear implants.

Authors:  Laura K Holden; Charles C Finley; Jill B Firszt; Timothy A Holden; Christine Brenner; Lisa G Potts; Brenda D Gotter; Sallie S Vanderhoof; Karen Mispagel; Gitry Heydebrand; Margaret W Skinner
Journal:  Ear Hear       Date:  2013 May-Jun       Impact factor: 3.570

9.  Neural correlates of adaptation in freely-moving normal hearing subjects under cochlear implant acoustic simulations.

Authors:  Christopher J Smalt; Javier Gonzalez-Castillo; Thomas M Talavage; David B Pisoni; Mario A Svirsky
Journal:  Neuroimage       Date:  2013-06-07       Impact factor: 6.556

10.  Interactions between unsupervised learning and the degree of spectral mismatch on short-term perceptual adaptation to spectrally shifted speech.

Authors:  Tianhao Li; John J Galvin; Qian-Jie Fu
Journal:  Ear Hear       Date:  2009-04       Impact factor: 3.570

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