EVALUATION OF COCHLEAR IMPLANT (CI)-MEDIATED MUSIC PROCESSING USING ELECTRODOGRAM MAPPING TO COMPARE WITH PERCEPTION
Citation
Hodges, Aaron. 2021. EVALUATION OF COCHLEAR IMPLANT (CI)-MEDIATED MUSIC PROCESSING USING ELECTRODOGRAM MAPPING TO COMPARE WITH PERCEPTION. Bachelor's thesis, Harvard College.Abstract
Appreciating and perceiving music has been a persistent challenge for using cochlear implants (CIs). Despite having speech perception capabilities in quiet environments, CI users struggle with foundational components of music like pitch discrimination and in many cases are unable to enjoy music to the same degree previously. There are a few studies, such as the one by Rubinstein and colleagues where they validated a Clinical Assessment of Music Perception (CAMP) test, that provide a basis for understanding how well CI users can perceive different musical signals. However, most of these studies rely on the surveying and experimentation of patients to determine music perception. This study seeks to provide a methodology that analyzes the spectral differences between musical notes and instruments after processing by the cochlear implant. We hypothesize that comparing cochlear implant processed signals (electrodograms) of different musical instruments and notes will match the performance of cochlear implant users when tasked with distinguishing musical signals from one another.In this study, we used an electrodogram analysis to visually show how musical signals are processed by a 16 channel cochlear implant speech processor. Signal processing strategies have previously been proposed to affect music perception, so we focused on two commonly used CI programs: HiRes and Optima. We used wav files from the CAMP study that provided comparable pitch and timbre between common instrument families. A correlogram was computed comparing the electrodograms representing musical notes and the notes within an instrumental group was used to quantify the similarities and differences of the electrodogram. This provided an overall correlation, determining which instrument and/or note was the most distinguishable from the other signals. Having additionally investigated music making in the CI community, we hoped to make connections to explain some of the findings in the results.
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