These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Performance of subjects fit with the Advanced Bionics CII and Nucleus 3G cochlear implant devices.
    Author: Spahr AJ, Dorman MF.
    Journal: Arch Otolaryngol Head Neck Surg; 2004 May; 130(5):624-8. PubMed ID: 15148187.
    Abstract:
    OBJECTIVE: To determine if subjects who used different cochlear implant devices and who were matched on consonant-vowel-consonant (CNC) identification in quiet would show differences in performance on speech-based tests of spectral and temporal resolution, speech understanding in noise, or speech understanding at low sound levels. DESIGN: The performance of 15 subjects fit with the CII Bionic Ear System (CII Bionic Ear behind-the-ear speech processor with the Hi-Resolution sound processing strategy; Advanced Bionics Corporation) was compared with the performance of 15 subjects fit with the Nucleus 24 electrode array and ESPrit 3G behind-the-ear speech processor with the advanced combination encoder speech coding strategy (cochlear corporation). SUBJECTS: Thirty adults with late-onset deafness and above-average speech perception abilities who used cochlear implants. MAIN OUTCOME MEASURES: Vowel recognition, consonant recognition, sentences in quiet (74, 64, and 54 dB SPL [sound pressure level]) and in noise (+10 and +5 dB SNR [signal-to-noise ratio]), voice discrimination, and melody recognition. RESULTS: Group differences in performance were significant in 4 conditions: vowel identification, difficult sentence material at +5 dB and +10 dB SNR, and a measure that quantified performance in noise and low input levels relative to performance in quiet. CONCLUSIONS: We have identified tasks on which there are between-group differences in performance for subjects matched on CNC word scores in quiet. We suspect that the differences in performance are due to differences in signal processing. Our next goal is to uncover the signal processing attributes of the speech processors that are responsible for the differences in performance.
    [Abstract] [Full Text] [Related] [New Search]