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Cochlear implant datalogging accurately characterizes children’s ‘auditory scenes’
Cochlear Implants International (2021)
  • Hillary Ganek, Western University
  • Deja Forde-Dixon
  • Sharon Cushing
  • Blake Papsin
  • Karen Gordon
Abstract
Objectives: This study sought to determine if children’s auditory environments are accurately captured by the automatic scene classification embedded in cochlear implant (CI) processors and to quantify the amount of electronic device use in these environments.

Methods: Seven children with CIs, 36.71 (SD = 11.94) months old, participated in this study. Three of the children were male and four were female. Eleven datalogs, containing outcomes from Cochlear’s™ Nucleus® 6 (Cochlear Corporation, Australia) CI scene classification algorithm, and seven day-long audio recordings collected with a Language ENvironment Analysis (LENA; LENA Research Foundation, USA) recorder were obtained for analysis.

Results: Results from the scene classification algorithm were strongly correlated with categories determined through human coding (ICC = .86, CI = [−0.2, 1], F(5,5.1) = 5.9, P = 0.04) but some differences …
Disciplines
Publication Date
2021
Citation Information
Hillary Ganek, Deja Forde-Dixon, Sharon Cushing, Blake Papsin, et al.. "Cochlear implant datalogging accurately characterizes children’s ‘auditory scenes’" Cochlear Implants International (2021)
Available at: http://works.bepress.com/hillary-ganek/1/