A Hundred Ways to Encode Sound Signals for Cochlear Implants

Cochlear implants are the most successful neural prostheses used to restore hearing in severe-to-profound hearing-impaired individuals. The field of cochlear implant coding investigates interdisciplinary approaches to translate acoustic signals into electrical pulses transmitted at the electrode-neuron interface, ranging from signal preprocessing algorithms, enhancement, and feature extraction methodologies to electric signal generation. In the last five decades, numerous coding strategies have been proposed clinically and experimentally. Initially developed to restore speech perception, increasing computational possibilities now allow coding of more complex signals, and new techniques to optimize the transmission of electrical signals are constantly gaining attention. This review provides insights into the history of multichannel coding and presents an extensive list of implemented strategies. The article briefly addresses each method and considers promising future directions of neural prostheses and possible signal processing, with the ultimate goal of providing a current big picture of the large field of cochlear implant coding.

The effects of estimation accuracy, estimation approach, and number of selected channels using formant-priority channel selection for an "n-of-m" sound processing strategy for cochlear implants

Previously, selection of l channels was prioritized according to formant frequency locations in an l-of-n-of-m-based signal processing strategy to provide important voicing information independent of listening environments for cochlear implant (CI) users. In this study, ideal, or ground truth, formants were incorporated into the selection stage to determine the effect of accuracy on (1) subjective speech intelligibility, (2) objective channel selection patterns, and (3) objective stimulation patterns (current). An average +11% improvement (p < 0.05) was observed across six CI users in quiet, but not for noise or reverberation conditions. Analogous increases in channel selection and current for the upper range of F1 and a decrease across mid-frequencies with higher corresponding current, were both observed at the expense of noise-dominant channels. Objective channel selection patterns were analyzed a second time to determine the effects of estimation approach and number of selected channels (n). A significant effect of estimation approach was only observed in the noise and reverberation condition with minor differences in channel selection and significantly decreased stimulated current. Results suggest that estimation method, accuracy, and number of channels in the proposed strategy using ideal formants may improve intelligibility when corresponding stimulated current of formant channels are not masked by noise-dominant channels.

Combination and Comparison of Sound Coding Strategies Using Cochlear Implant Simulation With Mandarin Speech

Three cochlear implant (CI) sound coding strategies were combined in the same signal processing path and compared for speech intelligibility with vocoded Mandarin sentences. The three CI coding strategies, biologically-inspired hearing aid algorithm (BioAid), envelope enhancement (EE), and fundamental frequency modulation (F0mod), were combined with the advanced combination encoder (ACE) strategy. Hence, four singular coding strategies and four combinational coding strategies were derived. Mandarin sentences with speech-shape noise were processed using these coding strategies. Speech understanding of vocoded Mandarin sentences was evaluated using short-time objective intelligibility (STOI) and subjective sentence recognition tests with normal-hearing listeners. For signal-to-noise ratios at 5 dB or above, the EE strategy had slightly higher average scores in both STOI and listening tests compared to ACE. The addition of EE to BioAid slightly increased the mean scores for BioAid+EE, which was the combination strategy with the highest scores in both objective and subjective speech intelligibility. The benefits of BioAid, F0mod, and the four combinational coding strategies were not observed in CI simulation. The findings of this study may be useful for the future design of coding strategies and related studies with Mandarin.

Phenomenological model of auditory nerve population responses to cochlear implant stimulation

BACKGROUND

Models of auditory nerve fiber (ANF) responses to electrical stimulation are helpful to develop advanced coding for cochlear implants (CIs). A phenomenological model of ANF population responses to CI electrical stimulation with a lower computational complexity compared to a biophysical model would be beneficial to evaluate new CI coding strategies.

NEW METHOD

This study presents a phenomenological model which combines four temporal characteristics of ANFs (refractoriness, facilitation, accommodation and spike rate adaptation) in addition to a spatial spread of the electric field.

RESULTS

The model predicts the performances of CI subjects in the melodic contour identification (MCI) experiment. The simulations for the MCI experiment were consistent with CI recipients' experimental outcomes that were not predictable from the electrical stimulation patterns themselves.

COMPARISON WITH EXISTING METHODS

Previously, no phenomenological population model of ANFs has combined all four aforementioned temporal phenomena.

CONCLUSIONS

The proposed model would help the further investigations of ANFs responses to different electrical stimulation patterns and comparison of different sound coding strategies in CIs.