Evaluation of a New Algorithm to Optimize Audibility in Cochlear Implant Recipients

评估一种优化人工耳蜗植入者听力的新算法

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Abstract

OBJECTIVES: A positive relation between audibility and speech understanding has been established for cochlear implant (CI) recipients. Sound field thresholds of 20 dB HL across the frequency range provide CI users the opportunity to understand soft and very soft speech. However, programming the sound processor to attain good audibility can be time-consuming and difficult for some patients. To address these issues, Advanced Bionics (AB) developed the SoftVoice algorithm designed to remove system noise and thereby improve audibility of soft speech. The present study aimed to evaluate the efficacy of SoftVoice in optimizing AB CI recipients' soft-speech perception. DESIGN: Two studies were conducted. Study 1 had two phases, 1A and 1B. Sixteen adult, AB CI recipients participated in Study 1A. Acute testing was performed in the unilateral CI condition using a Harmony processor programmed with participants' everyday-use program (Everyday) and that same program but with SoftVoice implemented. Speech recognition measures were administered at several presentation levels in quiet (35 to 60 dB SPL) and in noise (60 dB SPL). In Study 1B, 10 of the participants compared Everyday and SoftVoice at home to obtain feedback regarding the use of SoftVoice in various environments. During Study 2, soft-speech perception was acutely measured with Everyday and SoftVoice for 10 participants using the Naida CI Q70 processor. Results with the Harmony (Study 1A) and Naida processors were compared. Additionally, Study 2 evaluated programming options for setting electrode threshold levels (T-levels or Ts) to improve the usability of SoftVoice in daily life. RESULTS: Study 1A showed significantly higher scores with SoftVoice than Everyday at soft presentation levels (35, 40, 45, and 50 dB SPL) and no significant differences between programs at a conversational level (60 dB SPL) in quiet or in noise. After take-home experience with SoftVoice and Everyday (Study 1B), 5 of 10 participants reported preferring SoftVoice over Everyday; however, 6 reported bothersome environmental sound when listening with SoftVoice at home. Results of Study 2 indicated similar soft-speech perception between Harmony and Naida processors. Additionally, implementing SoftVoice with Ts at the manufacturer's default setting of 10% of Ms reduced reports of bothersome environmental sound during take-home experience; however, soft-speech perception was best with SoftVoice when Ts were behaviorally set above 10% of Ms. CONCLUSIONS: Results indicate that SoftVoice may be a potential tool for optimizing AB users' audibility and, in turn, soft-speech perception. To achieve optimal performance at soft levels and comfortable use in daily environments, setting Ts must be considered with SoftVoice. Future research should examine program parameters that may benefit soft-speech perception when used in combination with SoftVoice (e.g., increased input dynamic range).

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