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Home-Based Speech Perception Monitoring for Clinical Use With Cochlear Implant Users

Journal Contribution - Journal Article

Speech-perception testing is essential for monitoring outcomes with a hearing aid or cochlear implant (CI). However, clinical care is time-consuming and often challenging with an increasing number of clients. A potential approach to alleviating some clinical care and possibly making room for other outcome measures is to employ technologies that assess performance in the home environment. In this study, we investigate 3 different speech perception indices in the same 40 CI users: phoneme identification (vowels and consonants), digits in noise (DiN) and sentence recognition in noise (SiN). The first two tasks were implemented on a tablet and performed multiple times by each client in their home environment, while the sentence task was administered at the clinic. Speech perception outcomes in the same forty CI users showed that DiN assessed at home can serve as an alternative to SiN assessed at the clinic. DiN scores are in line with the SiN ones by 3-4 dB improvement and are useful to monitor performance at regular intervals and to detect changes in auditory performance. Phoneme identification in quiet also explains a significant part of speech perception in noise, and provides additional information on the detectability and discriminability of speech cues. The added benefit of the phoneme identification task, which also proved to be easy to administer at home, is the information transmission analysis in addition to the summary score. Performance changes for the different indices can be interpreted by comparing against measurement error and help to target personalized rehabilitation. Altogether, home-based speech testing is reliable and proves powerful to complement care in the clinic for CI users.
Journal: Front Neurosci
ISSN: 1662-4548
Volume: 15
Publication year:2021
BOF-keylabel:yes
IOF-keylabel:yes
BOF-publication weight:1
CSS-citation score:1
Authors from:Higher Education
Accessibility:Open