Clinical evaluation of the Nucleus<sup>®</sup>6 cochlear implant system: Performance improvements with SmartSound iQ

Mauger, Stefan J.; Warren, Chris; Knight, Michelle R.; Goorevich, Michael; Nel, Esti

doi:10.3109/14992027.2014.895431

Cited by 91 publications

(112 citation statements)

References 36 publications

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“…In addition to these programs, which were used for all participants, each listener was assessed with 188 Hz (full overlap), 313 Hz, 438 Hz, 563 Hz, 688 Hz, and 813 Hz so that we could assess the effect of discrete LF CI cutoff frequencies. All programs incorporated SCAN SmartSound iQ, background-noise reduction (SNR-NR; Mauger et al 2014; Wolfe et al 2015), and wind-noise reduction (WNR) (Studebaker et al 1999). Study participants were asked to use all 4 programs equally for 3–4 weeks.…”

Section: Methodsmentioning

confidence: 99%

Combined Electric and Acoustic Stimulation With Hearing Preservation: Effect of Cochlear Implant Low-Frequency Cutoff on Speech Understanding and Perceived Listening Difficulty

et al. 2017

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Objective The primary objective of this study was to assess the effect of electric and acoustic overlap for speech understanding in typical listening conditions using semi-diffuse noise. Design This study used a within-subjects, repeated-measures design including 11 experienced adult implant recipients (13 ears) with functional residual hearing in the implanted and non-implanted ear. The aided acoustic bandwidth was fixed and the low-frequency cutoff for the cochlear implant was varied systematically. Assessments were completed in the R-SPACE™ sound-simulation system which includes a semi-diffuse restaurant noise originating from eight loudspeakers placed circumferentially about the subject’s head. AzBio sentences were presented at 67 dBA with signal-to-noise ratio (SNR) varying between +10 and 0 dB determined individually to yield approximately 50–60% correct for the cochlear implant (CI) alone condition with full CI bandwidth. Listening conditions for all subjects included CI alone, bimodal (CI + contralateral hearing aid, HA), and bilateral-aided electric and acoustic stimulation (EAS; CI + bilateral HA). Low-frequency cutoffs both below and above the original “clinical software recommendation” frequency were tested for all patients, in all conditions. Subjects estimated listening difficulty for all conditions using listener ratings based on a visual analog scale. Results Three primary findings were that 1) there was statistically significant benefit of preserved acoustic hearing in the implanted ear for most overlap conditions, 2) the default clinical software recommendation rarely yielded the highest level of speech recognition (1 out of 13 ears), and 3) greater EAS overlap than that provided by the clinical recommendation yielded significant improvements in speech understanding. Conclusions For standard-electrode CI recipients with preserved hearing, spectral overlap of acoustic and electric stimuli yielded significantly better speech understanding and less listening effort in a laboratory-based, restaurant-noise simulation. In conclusion, EAS patients may derive more benefit from greater acoustic and electric overlap than given in current software fitting recommendations which are based solely on audiometric threshold. These data have larger scientific implications, as previous studies may not have assessed outcomes with optimized EAS parameters, thereby underestimating the benefit afforded by hearing preservation.

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Section: Methodsmentioning

confidence: 99%

Combined Electric and Acoustic Stimulation With Hearing Preservation: Effect of Cochlear Implant Low-Frequency Cutoff on Speech Understanding and Perceived Listening Difficulty

et al. 2017

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“…SE algorithms can be divided into algorithms that make use of two or more microphones to exploit the spatial properties of target and noise sources, and algorithms that make use of a single microphone (or the output signal of a multi-microphone algorithm). Multi-microphone algorithms have been shown to deliver large benefits in SRT scores when the target signal and the interfering noise source are spatially separated (Mauger and Warren, 2014, Spriet et al., 2007, Wouters and Van den Berghe, 2001). However, in everyday listening situations, these requirements might not always be fulfilled, and single-microphone algorithms are still of interest for numerous applications, such as hearing devices, where the number of microphones is usually limited to two and the two microphones are on the same side of the head.…”

Section: Introductionmentioning

confidence: 99%

Speech enhancement based on neural networks improves speech intelligibility in noise for cochlear implant users

et al. 2017

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Speech understanding in noisy environments is still one of the major challenges for cochlear implant (CI) users in everyday life. We evaluated a speech enhancement algorithm based on neural networks (NNSE) for improving speech intelligibility in noise for CI users. The algorithm decomposes the noisy speech signal into time-frequency units, extracts a set of auditory-inspired features and feeds them to the neural network to produce an estimation of which frequency channels contain more perceptually important information (higher signal-to-noise ratio, SNR). This estimate is used to attenuate noise-dominated and retain speech-dominated CI channels for electrical stimulation, as in traditional n-of-m CI coding strategies. The proposed algorithm was evaluated by measuring the speech-in-noise performance of 14 CI users using three types of background noise. Two NNSE algorithms were compared: a speaker-dependent algorithm, that was trained on the target speaker used for testing, and a speaker-independent algorithm, that was trained on different speakers. Significant improvements in the intelligibility of speech in stationary and fluctuating noises were found relative to the unprocessed condition for the speaker-dependent algorithm in all noise types and for the speaker-independent algorithm in 2 out of 3 noise types. The NNSE algorithms used noise-specific neural networks that generalized to novel segments of the same noise type and worked over a range of SNRs. The proposed algorithm has the potential to improve the intelligibility of speech in noise for CI users while meeting the requirements of low computational complexity and processing delay for application in CI devices.

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“…Cochlear implant manufacturers provide several technologies to improve performance in noise. Directional microphones, advances in signal processing, and use of remote-microphone hearing assistance technology (HAT) have been shown to improve speech recognition in noise (7)(8)(9)(10)(11)(12)(13)(14)(15).…”

mentioning

confidence: 99%

Speech Recognition of Bimodal Cochlear Implant Recipients Using a Wireless Audio Streaming Accessory for the Telephone

Wolfe

Morais²,

Schafer³

2016

Otology &Amp; Neurotology

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Clinical evaluation of the Nucleus^®6 cochlear implant system: Performance improvements with SmartSound iQ

Cited by 91 publications

References 36 publications

Combined Electric and Acoustic Stimulation With Hearing Preservation: Effect of Cochlear Implant Low-Frequency Cutoff on Speech Understanding and Perceived Listening Difficulty

Combined Electric and Acoustic Stimulation With Hearing Preservation: Effect of Cochlear Implant Low-Frequency Cutoff on Speech Understanding and Perceived Listening Difficulty

Speech enhancement based on neural networks improves speech intelligibility in noise for cochlear implant users

Speech Recognition of Bimodal Cochlear Implant Recipients Using a Wireless Audio Streaming Accessory for the Telephone

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Clinical evaluation of the Nucleus®6 cochlear implant system: Performance improvements with SmartSound iQ

Cited by 91 publications

References 36 publications

Combined Electric and Acoustic Stimulation With Hearing Preservation: Effect of Cochlear Implant Low-Frequency Cutoff on Speech Understanding and Perceived Listening Difficulty

Combined Electric and Acoustic Stimulation With Hearing Preservation: Effect of Cochlear Implant Low-Frequency Cutoff on Speech Understanding and Perceived Listening Difficulty

Speech enhancement based on neural networks improves speech intelligibility in noise for cochlear implant users

Speech Recognition of Bimodal Cochlear Implant Recipients Using a Wireless Audio Streaming Accessory for the Telephone

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Clinical evaluation of the Nucleus^®6 cochlear implant system: Performance improvements with SmartSound iQ