Waldo Nogueira

Signal processing strategies for cochlear implants using current steering

In contemporary cochlear implant systems, the audio signal is decomposed into different frequency bands, each assigned to one electrode. Thus, pitch perception is limited by the number of physical electrodes implanted into the cochlea and by the wide bandwidth assigned to each electrode. The Harmony HiResolution bionic ear (Advanced Bionics LLC, Valencia, CA, USA) has the capability of creating virtual spectral channels through simultaneous delivery of current to pairs of adjacent electrodes. By steering the locus of stimulation to sites between the electrodes, additional pitch percepts can be generated. Two new sound processing strategies based on current steering have been designed, SpecRes and SineEx. In a chronic trial, speech intelligibility, pitch perception, and subjective appreciation of sound were compared between the two current steering strategies and standard HiRes strategy in 9 adult Harmony users. There was considerable variability in benefit, and the mean results show similar performance with all three strategies.

Recurrence quantification analysis features for environmental sound recognition

This paper tackles the problem of feature aggregation for recognition of auditory scenes in unlabeled audio. We describe a new set of descriptors based on Recurrence Quantification Analysis (RQA), which can be extracted from the similarity matrix of a time series of audio descriptors. We analyze their usefulness for environmental audio recognition combined with traditional feature statistics in the context of the AASP D-CASE[1] challenge. Our results show the potential of non-linear time series analysis techniques for dealing with environmental sounds.

Results from a psychoacoustic model-based strategy for the nucleus-24 and freedom cochlear implants.

Objective: In normal-hearing listeners acoustic masking occurs depending on frequency, amplitude, and energy of specific signals. If the selection of stimulated channels in cochlear implant systems was based on psychoacoustic masking models, the bandwidth of the electrode/nerve interface could be used more effectively by concentrating on relevant signal components and neglecting those that are usually not perceived by normal hearing listeners. Subsequently, a new strategy called PACE (Psychoacoustic Advanced Combination Encoder) has been developed which uses a psychoacoustic model for the channel selection instead of the simple maxima selection algorithm of the ACE strategy. Study Design: Only subjects having at least 2 years experience with the ACE strategy were included. A counterbalanced cross-over design was used to compare the new speech coding strategy with the ACE strategy. Setting: The investigation was a prospective, within-subject, repeated-measures experiment. Patients: The study group consisted of 10 postlingually deafened adult subjects. Interventions: The following programs were evaluated: (1) ACE with 8 maxima selected; (2) PACE with 8 channels selected; and (3) PACE with 4 channels selected. Main Outcome Measures: Speech perception tests in quiet and noise, Quality Assessment Questionnaire. Results: Results indicate a trend towards better performance with PACE. Scores in the Freiburg monosyllabic word test increased by 8% while the SNR50 in the Oldenburger sentence test improved significantly by 1.3 dB. Conclusion: The use of psychoacoustic masking models in speech coding strategies has the potential to improve speech perception performance in cochlear implant subjects.

Wavelet Packet Filterbank for Speech Processing Strategies in Cochlear Implants

Current speech processing strategies for cochlear implants use a filterbank which decomposes the audio signals into multiple frequency bands each associated with one electrode. Pitch perception with cochlear implants is related to the number of electrodes inserted in the cochlea and to the rate of stimulation of these electrodes. The filterbank should, therefore, be able to analyze the time-frequency features of the audio signals while also exploiting the time-frequency features of the implant. This study investigates the influence on speech intelligibility in cochlear implant users when filterbanks with different time-frequency resolutions are used. Three filter-banks, based on the structure of a wavelet packet transform but using different basis functions, were designed. The filter-banks were incorporated into a commercial speech processing strategy and were tested on device users in an acute study

Design and Evaluation of a Cochlear Implant Strategy Based on a “Phantom” Channel

Unbalanced bipolar stimulation, delivered using charge balanced pulses, was used to produce “Phantom stimulation”, stimulation beyond the most apical contact of a cochlear implant’s electrode array. The Phantom channel was allocated audio frequencies below 300Hz in a speech coding strategy, conveying energy some two octaves lower than the clinical strategy and hence delivering the fundamental frequency of speech and of many musical tones. A group of 12 Advanced Bionics cochlear implant recipients took part in a chronic study investigating the fitting of the Phantom strategy and speech and music perception when using Phantom. The evaluation of speech in noise was performed immediately after fitting Phantom for the first time (Session 1) and after one month of take-home experience (Session 2). A repeated measures of analysis of variance (ANOVA) within factors strategy (Clinical, Phantom) and interaction time (Session 1, Session 2) revealed a significant effect for the interaction time and strategy. Phantom obtained a significant improvement in speech intelligibility after one month of use. Furthermore, a trend towards a better performance with Phantom (48%) with respect to F120 (37%) after 1 month of use failed to reach significance after type 1 error correction. Questionnaire results show a preference for Phantom when listening to music, likely driven by an improved balance between high and low frequencies.

Validation of a Cochlear Implant Patient-Specific Model of the Voltage Distribution in a Clinical Setting

Cochlear Implants (CIs) are medical implantable devices that can restore the sense of hearing in people with profound hearing loss. Clinical trials assessing speech intelligibility in CI users have found large intersubject variability. One possibility to explain the variability is the individual differences in the interface created between electrodes of the CI and the auditory nerve. In order to understand the variability, models of the voltage distribution of the electrically stimulated cochlea may be useful. With this purpose in mind, we developed a parametric model that can be adapted to each CI user based on landmarks from individual cone beam computed tomography (CBCT) scans of the cochlea before and after implantation. The conductivity values of each cochlea compartment as well as the weighting factors of different grounding modes have also been parameterized. Simulations were performed modeling the cochlea and electrode positions of 12 CI users. Three models were compared with different levels of detail: a homogeneous model (HM), a non-patient-specific model (NPSM), and a patient-specific model (PSM). The model simulations were compared with voltage distribution measurements obtained from the backward telemetry of the 12 CI users. Results show that the PSM produces the lowest error when predicting individual voltage distributions. Given a patient-specific geometry and electrode positions, we show an example on how to optimize the parameters of the model and how to couple it to an auditory nerve model. The model here presented may help to understand speech performance variability and support the development of new sound coding strategies for CIs.

Spectral contrast enhancement improves speech intelligibility in noise for cochlear implants

Spectral smearing causes, at least partially, that cochlear implant (CI) users require a higher signal-to-noise ratio to obtain the same speech intelligibility as normal hearing listeners. A spectral contrast enhancement (SCE) algorithm has been designed and evaluated as an additional feature for a standard CI strategy. The algorithm keeps the most prominent peaks within a speech signal constant while attenuating valleys in the spectrum. The goal is to partly compensate for the spectral smearing produced by the limited number of stimulation electrodes and the overlap of electrical fields produced in CIs. Twelve CI users were tested for their speech reception threshold (SRT) using the standard CI coding strategy with and without SCE. No significant differences in SRT were observed between conditions. However, an analysis of the electrical stimulation patterns shows a reduction in stimulation current when using SCE. In a second evaluation, 12 CI users were tested in a similar configuration of the SCE strategy with the stimulation being balanced between the SCE and the non-SCE variants such that the loudness perception delivered by the strategies was the same. Results show a significant improvement in SRT of 0.57 dB (p < 0.0005) for the SCE algorithm.

Loudness and pitch perception using Dynamically Compensated Virtual Channels.

&NA; Reducing power consumption is important for the development of smaller cochlear implant (CI) speech processors. Simultaneous electrode stimulation may improve power efficiency by minimizing the required current applied to a given electrode. Simultaneous in‐phase stimulation on adjacent electrodes (i.e. virtual channels) can be used to elicit pitch percepts intermediate to the ones provided by each of the physical electrodes in isolation. Virtual channels are typically implemented in monopolar stimulation mode, producing broad excitation patterns. Focused stimulation may reduce the excitation patterns, but is inefficient in terms of power consumption. To create a more power efficient virtual channel, we developed the Dynamically Compensated Virtual Channel (DC‐VC) using four adjacent electrodes. The two central electrodes are current steered using the coefficient Symbol (Symbol) whereas the two flanking electrodes are used to focus/unfocus the stimulation with the coefficient Symbol (Symbol). With increasing values of Symbol, power can be saved at the potential expense of generating broader electric fields. Additionally, reshaping the electric fields might also alter place pitch coding. Symbol. No caption available. Symbol. No caption available. Symbol. No caption available. Symbol. No caption available. The goal of the present study is to investigate the tradeoff between place pitch encoding and power savings using simultaneous electrode stimulation in the DC‐VC configuration. A computational model and psychophysical experiments in CI users have been used for that purpose. Results from 10 adult Advanced Bionics CI users have been collected. Results show that the required current to produce comfortable levels is significantly reduced with increasing Symbol as predicted by the computational model. Moreover, no significant differences in the estimated number of discriminable steps were detected for the different values of Symbol. From these results, we conclude that DC‐VCs can reduce power consumption without decreasing the number of discriminable place pitch steps. HighlightsDynamically Compensated Virtual Channels (DC‐VC), a new stimulation mode for CIs.Loudness and pitch perception with DC‐VC are investigated using a model and experiments in CI users.DC‐VC can be used to reduce power consumption without degradation of pitch perception.

An Auditory Model Based Strategy for Cochlear Implants

A physiological and computational model of the human auditory system has been fitted in a signal processing strategy for cochlear implants (CIs). The aim of the new strategy is to obtain more natural sound in CIs by better mimicking the human auditory system. The new strategy was built in three independent stages as proposed in [6]. First a basilar membrane motion model was substituted by the filterbank commonly used in commercial strategies. Second, an inner hair cell model was included in a commercial strategy while maintaining the original filterbank. Third, both the basilar membrane motion and the inner-hair cell model were included in the commercial strategy. This paper analyses the properties and presents results obtained with CI recipients for each algorithm designed.

Speech Recognition Technology in CI Rehabilitation

eHealth is a topic that is gaining increasing interest throughout all sectors of health care, driven by a constant drive towards greater efficiency and quality, and by the fact that patients desire a more active, prominent role in their therapeutic care. IT and computer technologies can support this evolution in a structured way. A good example can be found in cochlear implant care. Children could benefit in the development of their auditory and language skills by more intense exercises. However, there are relatively few speech therapists, operating in specialized centres. If children could perform exercises on the computer, in their own home or school environments, the care could be intensified in a playful manner, while at the same time keeping the cost acceptable.