The goal of the present study is to use computationally driven models of speech understanding in cochlear implant (CI) users to guide the search for which combination of active electrodes can yield the best speech understanding for a specific patient. It is hypothesized that model-recommended settings will result in significantly better speech understanding than standard-of-care settings.
Aim 1 is to quantify speech understanding and sound quality with model-recommended combinations of active electrodes compared to standard settings, and compared to two control active electrode combinations. Aim 2 is to translate the model-driven recommendations from Aim 1 into practical guidance about how many (and possibly which) CI electrodes to deactivate.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
DOUBLE
Enrollment
14
The computer model will use standard Cochlear Implant settings to evaluate psychophysical and speech understanding abilities and sound quality with standard CI settings and then use these measures to build subject-specific models and determine experimental active electrode conditions to be tested: model-optimized, and two best-electrodes settings (2 types); 3) evaluate speech understanding and sound quality measures after using experimental settings regularly for 1.5 months; and 4) compare performance across experimental and clinical conditions. The analysis will include four levels of repeated measures with active CI electrode conditions. These levels include the clinical baseline condition (all available electrodes active) and three experimental conditions (model-optimized, best-electrodes, and restricted best-electrodes).
NYU Langone Health
New York, New York, United States
Change in Vowel and consonant identification
Vowel and consonant identification testing will include 9 vowels in /hVd/ context and 16 consonants in /aCa/ context presented in quiet. Each phoneme will be presented 15 times. Vowel and consonant testing will be done during initial speech testing using clinical CI settings. Subject confusion matrices (i.e. number of correct responses and specific confusions) will serve as the basis for model construction.
Time frame: Baseline, Month 6
Change in Word recognition
Word recognition testing will consist of a Consonant-Nucleus-Consonant (CNC) monosyllabic word test that includes 30 lists of 50 words each presented in quiet. Participants will complete three CNC word lists per testing session, and word lists will be blocked across testing sessions so no word list is repeated. Word recognition scores will be used to evaluate performance with clinical and experimental CI settings. Word scores with clinical settings will also be used for model development.
Time frame: Baseline, Month 6
Change in Sentence recognition
Sentence recognition testing will consist of AzBio sentences tested in +10 decibel (dB) signal-to-noise ratio (SNR) multi-talker babble. The test includes 33 lists of 20 sentences with approximately 150 words per list. Participants will complete two lists per testing session, and lists will be blocked across testing sessions so no lists are repeated. Sentence recognition scores in noise will help evaluate generalization of performance with experimental settings to other speech tasks and in other listening conditions. Speech stimuli will be presented at 65 dB sound pressure level (SPL) (C-weighted) in a sound attenuated room as measured from CI user's microphone.
Time frame: Baseline, Month 6
Change in Electrode discrimination
Electrode discrimination will be measured as a JND relative to every active CI electrode in both basal and apical directions. Individual electrodes will be stimulated with 500ms pulse trains at comfortable loudness-balanced levels. JND for each reference electrode will be measured adaptively using a 4-interval 2-alternative forced-choice (2AFC) 2-down/1-up procedure. Electrode discrimination Just Noticeable Differences (JNDs) will serve as inputs to build the proposed subject-specific models.
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Time frame: Baseline, Month 6
Change in Pitch Scaling
Subjects will be instructed to assign a number from 1 to 100 that corresponds to their perceived pitch of a stimulated electrode (100 highest in pitch). Each electrode will be stimulated once per block using 500ms pulse trains at comfortable loudness-balanced levels, presented in random order. A trimmed mean of pitch ratings (discarding lowest and highest ratings) for the last eight of ten blocks will be used to determine the final score. Pitch scaling will be used to evaluate whether electrodes are perceived as well ordered in pitch, and will be measured with clinical CI settings.
Time frame: Baseline, Month 6
Change in Sound Quality
A shortened version of the speech, spatial, and qualities of hearing scale (SSQ12) will be administered when using clinical CI settings, and after using experimental CI settings for 1.5 months. The SSQ12 is a self-assessment questionnaire measuring hearing disability across three domains. The shortened version, SSQ12, includes 12 questions across the three domains. Each question is answered using a 10-point scale ranging for poorest (i.e. 0) to best (i.e 10) performance. The average score across questions will be used to evaluate sound quality across CI settings conditions and across subjects. The SSQ12 has previously been validated in CI users, and is highly correlated with results from the original 49 item SSQ.
Time frame: Baseline, Month 6