Rakszawski Bernadette, Wright Rose, Cadieux Jamie H, Davidson Lisa S, Brenner Christine
Program in Audiology and Communication Sciences, Washington University School of Medicine, St. Louis, MO.
St. Louis Children's Hospital, St. Louis, MO.
J Am Acad Audiol. 2016 Feb;27(2):85-102. doi: 10.3766/jaaa.14058.
Cochlear implants (CIs) have been shown to improve children's speech recognition over traditional amplification when severe-to-profound sensorineural hearing loss is present. Despite improvements, understanding speech at low-level intensities or in the presence of background noise remains difficult. In an effort to improve speech understanding in challenging environments, Cochlear Ltd. offers preprocessing strategies that apply various algorithms before mapping the signal to the internal array. Two of these strategies include Autosensitivity Control™ (ASC) and Adaptive Dynamic Range Optimization (ADRO(®)). Based on the previous research, the manufacturer's default preprocessing strategy for pediatrics' everyday programs combines ASC + ADRO(®).
The purpose of this study is to compare pediatric speech perception performance across various preprocessing strategies while applying a specific programming protocol using increased threshold levels to ensure access to very low-level sounds.
This was a prospective, cross-sectional, observational study. Participants completed speech perception tasks in four preprocessing conditions: no preprocessing, ADRO(®), ASC, and ASC + ADRO(®).
Eleven pediatric Cochlear Ltd. CI users were recruited: six bilateral, one unilateral, and four bimodal.
Four programs, with the participants' everyday map, were loaded into the processor with different preprocessing strategies applied in each of the four programs: no preprocessing, ADRO(®), ASC, and ASC + ADRO(®).
Participants repeated consonant-nucleus-consonant (CNC) words presented at 50 and 70 dB SPL in quiet and Hearing in Noise Test (HINT) sentences presented adaptively with competing R-Space(TM) noise at 60 and 70 dB SPL. Each measure was completed as participants listened with each of the four preprocessing strategies listed above. Test order and conditions were randomized. A repeated-measures analysis of was used to compare each preprocessing strategy for the group. Critical differences were used to determine significant score differences between each preprocessing strategy for individual participants.
For CNC words presented at 50 dB SPL, the group data revealed significantly better scores using ASC + ADRO(®) compared to all other preprocessing conditions while ASC resulted in poorer scores compared to ADRO(®) and ASC + ADRO(®). Group data for HINT sentences presented in 70 dB SPL of R-Space(TM) noise revealed significantly improved scores using ASC and ASC + ADRO(®) compared to no preprocessing, with ASC + ADRO(®) scores being better than ADRO(®) alone scores. Group data for CNC words presented at 70 dB SPL and adaptive HINT sentences presented in 60 dB SPL of R-Space(TM) noise showed no significant difference among conditions. Individual data showed that the preprocessing strategy yielding the best scores varied across measures and participants.
Group data reveal an advantage with ASC + ADRO(®) for speech perception presented at lower levels and in higher levels of background noise. Individual data revealed that the optimal preprocessing strategy varied among participants, indicating that a variety of preprocessing strategies should be explored for each CI user considering his or her performance in challenging listening environments.
研究表明,对于存在重度至极重度感音神经性听力损失的儿童,与传统放大装置相比,人工耳蜗(CI)能提高其言语识别能力。尽管有了这些进步,但在低强度声音环境或存在背景噪声的情况下理解言语仍然困难。为了在具有挑战性的环境中提高言语理解能力,科利耳有限公司提供了预处理策略,即在将信号映射到内部阵列之前应用各种算法。其中两种策略包括自动灵敏度控制(ASC)和自适应动态范围优化(ADRO)。根据先前的研究,制造商针对儿科日常程序的默认预处理策略是ASC + ADRO。
本研究的目的是在应用特定编程协议并提高阈值水平以确保能接收到非常低强度声音的情况下,比较各种预处理策略下儿科患者的言语感知表现。
这是一项前瞻性、横断面观察性研究。参与者在四种预处理条件下完成言语感知任务:无预处理、ADRO、ASC以及ASC + ADRO。
招募了11名使用科利耳有限公司人工耳蜗的儿科患者:6名双侧植入者,1名单侧植入者,4名双模植入者。
将四个带有参与者日常设置的程序加载到处理器中,每个程序应用不同的预处理策略:无预处理、ADRO、ASC以及ASC + ADRO。
参与者重复在安静环境中以50和70 dB SPL呈现的辅音-元音-辅音(CNC)单词,以及在60和70 dB SPL的竞争性R-Space噪声下自适应呈现的噪声环境下言语测试(HINT)句子。在参与者使用上述四种预处理策略聆听时,完成每项测量。测试顺序和条件是随机的。采用重复测量分析来比较该组的每种预处理策略。使用临界差异来确定个体参与者在每种预处理策略之间的显著分数差异。
对于在50 dB SPL呈现的CNC单词,与所有其他预处理条件相比,该组数据显示使用ASC + ADRO时得分显著更高,而与ADRO和ASC + ADRO相比,ASC导致得分更低。在70 dB SPL的R-Space噪声中呈现的HINT句子的组数据显示,与无预处理相比,使用ASC和ASC + ADRO时得分显著提高,且ASC + ADRO的得分优于单独使用ADRO的得分。在70 dB SPL呈现的CNC单词以及在60 dB SPL的R-Space噪声中呈现的自适应HINT句子的组数据显示,各条件之间无显著差异。个体数据表明,产生最佳分数的预处理策略因测量和参与者而异。
组数据显示,对于较低强度和较高背景噪声水平下呈现的言语感知,ASC + ADRO具有优势。个体数据表明,最佳预处理策略因参与者而异,这表明应针对每个人工耳蜗使用者在具有挑战性的聆听环境中的表现探索多种预处理策略。