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Bibliografías temáticas / Signal processing. Cochlear implants

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Literatura académica sobre el tema "Signal processing. Cochlear implants"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 1 de febrero de 2022

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Artículos de revistas sobre el tema "Signal processing. Cochlear implants"

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Mehrzad, M., M. D. Abolhassani, A. H. Jafari, J. Alirezaie y M. Sangargir. "Cochlear Implant Speech Processing Using Wavelet Transform". ISRN Signal Processing 2012 (1 de agosto de 2012): 1–6. http://dx.doi.org/10.5402/2012/628706.

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We present a method for coding speech signals for the simulation of a cochlear implant. The method is based on a wavelet packet decomposition strategy. We used wavelet packet db4 for 7 levels, generated a series of channels with bandwidths exactly the same as nucleus device, and applied an input stimulus to each channel. The processed signal was then reconstructed and compared to the original signal, which preserved the contents to a high percentage. Finally, performance of the wavelet packet decomposition in terms of computational complexity was compared to other commonly used strategies in cochlear implants. The results showed the power of this method in processing of the input signal for implant users with less complexity than other methods, while maintaining the contents of the input signal to a very good extent.

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Laizou, P. C. "Signal-processing techniques for cochlear implants". IEEE Engineering in Medicine and Biology Magazine 18, n.º 3 (1999): 34–46. http://dx.doi.org/10.1109/51.765187.

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Nie, Kaibao. "ENHANCED SIGNAL PROCESSING FOR COCHLEAR IMPLANTS". Journal of the Acoustical Society of America 131, n.º 3 (2012): 2351. http://dx.doi.org/10.1121/1.3696845.

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Elberling, C. "Discussion of Signal-processing Potentials; Cochlear Implants". Acta Oto-Laryngologica 109, sup469 (1 de enero de 1990): 164–65. http://dx.doi.org/10.1080/00016489.1990.12088424.

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Tobey, Emily A., Lana Britt, Ann Geers, Philip Loizou, Betty Loy, Peter Roland, Andrea Warner-Czyz y Charles G. Wright. "Cochlear Implantation Updates: The Dallas Cochlear Implant Program". Journal of the American Academy of Audiology 23, n.º 06 (junio de 2012): 438–45. http://dx.doi.org/10.3766/jaaa.23.6.6.

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This report provides an overview of many research projects conducted by the Dallas Cochlear Implant Program, a joint enterprise between the University of Texas at Dallas, the University of Texas Southwestern Medical Center, and Children’s Medical Center. The studies extend our knowledge of factors influencing communication outcomes in users of cochlear implants. Multiple designs and statistical techniques are used in the studies described including both cross sectional and longitudinal analyses. Sample sizes vary across the studies, and many of the samples represent large populations of children from North America. Multiple statistical techniques are used by the team to analyze outcomes. The team has provided critical information regarding electrode placement, signal processing, and communication outcomes in users of cochlear implants.

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Tyler, Richard S. y Mary W. Lowder. "Audiological Management and Performance of Adult Cochlear-Implant Patients". Ear, Nose & Throat Journal 71, n.º 3 (marzo de 1992): 117–28. http://dx.doi.org/10.1177/014556139207100302.

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We review the signal-processing strategies of three of the most common cochlear implants in use today, the single-channel House, the multichannel Nucleus, and the Ineraid devices. The results of 65 postlinguistically-deafened patients tested at The University of Iowa are reviewed. The tests include everyday sound, accent, word and sentence recognition, as well as noise/voice differentiation. For all tests, patients with the Nucleus and Ineraid cochlear implants outperformed those with the House implant. In general, selection criteria should focus on comparing the performance of Patients who have already received an implant. Prelinguistically-deafened adults are typically not good cochlear-impact candidates. Cochlear-implant teams should be aware of the enormous time commitment for testing and rehabilitation of these patients, and be prepared to handle frequent implant breakdowns. Nevertheless, cochlear-implant patients have been helped significantly be these devices.

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S.Hallikar, Rohini, M. Uttarakumari, Padmaraju K y Yashas D. "Modified Turbo and SDROM Method for Speech Processing for Cochlear Implants". International Journal of Engineering & Technology 7, n.º 4.5 (22 de septiembre de 2018): 179. http://dx.doi.org/10.14419/ijet.v7i4.5.20040.

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A performance comparison of Signal Dependent Rank Order Mean (SDROM) method of speech signal enhancement with a speech enhancement method which makes use of a Turbo combination and SDROM filter referred to as modified Turbo and SDROM technique is made in this paper. Normally, speech signals are used as inputs to a cochlear implant signal processing unit.Sounds are corrupted by different noises such as AWGN, Impulsive noise and babble. The results are evaluated in terms of enhancements evaluations done by basically three parameters namely correlation coefficient, log spectral distortion (LSD) and segmental signal to noise ratio(SSNR). These parameters are calculated between the processed and the clean signals.. Results prove the superior performance of the new method especially for AWGN corrupted speech.

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Rubinstein, Jay T. y Robert Hong. "Signal Coding in Cochlear Implants: Exploiting Stochastic Effects of Electrical Stimulation". Annals of Otology, Rhinology & Laryngology 112, n.º 9_suppl (septiembre de 2003): 14–19. http://dx.doi.org/10.1177/00034894031120s904.

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Speech perception in quiet with cochlear implants has increased substantially over the past 17 years. If current trends continue, average monosyllabic word scores will be nearly 80% by 2010. These improvements are due to enhancements in speech processing strategies, to the implantation of patients with more residual hearing and shorter durations of deafness, and to unknown causes. Despite these improvements, speech perception in noise and music perception are still poor in most implant patients. These deficits may be partly due to poor representation of temporal fine structure by current speech processing strategies. It may be possible to improve both this representation and the dynamic range of electrical stimulation through the exploitation of stochastic effects produced by high-rate (eg, 5-kilopulse-per-second) pulse trains. Both the loudness growth and the dynamic range of low-frequency sinusoids have been enhanced via this technique. A laboratory speech processor using this strategy is under development. Although the clinical programming for such an algorithm is likely to be complex, some guidelines for the psychophysical and electrophysiological techniques necessary can be described now.

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Smiljanic, Rajka y Douglas Sladen. "Acoustic and Semantic Enhancements for Children With Cochlear Implants". Journal of Speech, Language, and Hearing Research 56, n.º 4 (agosto de 2013): 1085–96. http://dx.doi.org/10.1044/1092-4388(2012/12-0097).

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Purpose In this study, the authors examined how signal clarity interacts with the use of sentence context information in determining speech-in-noise recognition for children with cochlear implants and children with normal hearing. Method One hundred and twenty sentences in which the final word varied in predictability (high vs. low semantic context) were produced in conversational and clear speech. Nine children with cochlear implants and 9 children with normal hearing completed the sentence-in-noise listening tests and a standardized language measure. Results Word recognition in noise improved significantly for both groups of children for high-predictability sentences in clear speech. Children with normal hearing benefited more from each source of information compared with children with cochlear implants. There was a significant correlation between more developed language skills and the ability to use contextual enhancements. The smaller context gain in clear speech for children with cochlear implants is in accord with the effortfulness hypothesis (McCoy et al., 2005) and points to the cumulative effects of noise throughout the processing system. Conclusion Modifications of the speech signal and the context of the utterances through changes in the talker output hold substantial promise as a communication enhancement technique for both children with cochlear implants and children with normal hearing.

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Nittrouer, Susan, Amanda Caldwell-Tarr, Keri E. Low y Joanna H. Lowenstein. "Verbal Working Memory in Children With Cochlear Implants". Journal of Speech, Language, and Hearing Research 60, n.º 11 (9 de noviembre de 2017): 3342–64. http://dx.doi.org/10.1044/2017_jslhr-h-16-0474.

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Purpose Verbal working memory in children with cochlear implants and children with normal hearing was examined. Participants Ninety-three fourth graders (47 with normal hearing, 46 with cochlear implants) participated, all of whom were in a longitudinal study and had working memory assessed 2 years earlier. Method A dual-component model of working memory was adopted, and a serial recall task measured storage and processing. Potential predictor variables were phonological awareness, vocabulary knowledge, nonverbal IQ, and several treatment variables. Potential dependent functions were literacy, expressive language, and speech-in-noise recognition. Results Children with cochlear implants showed deficits in storage and processing, similar in size to those at second grade. Predictors of verbal working memory differed across groups: Phonological awareness explained the most variance in children with normal hearing; vocabulary explained the most variance in children with cochlear implants. Treatment variables explained little of the variance. Where potentially dependent functions were concerned, verbal working memory accounted for little variance once the variance explained by other predictors was removed. Conclusions The verbal working memory deficits of children with cochlear implants arise due to signal degradation, which limits their abilities to acquire phonological awareness. That hinders their abilities to store items using a phonological code.

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Tesis sobre el tema "Signal processing. Cochlear implants"

1

Wagner, Eva-Maria. "Across channel processing in auditory perception a study in gerbils (Meriones unguiculatus) and cochlear implant subjects /". [S.l.] : [s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=966507231.

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af, Ekenstam Love. "Modellering av signalbehandlingen i ett cochleaimplantat och utvärdering av modellen". Thesis, Uppsala universitet, Signaler och System, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-214582.

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Ett program som simulerar signalbehandlingen i ett cochleaimplantat med signalbehandlingsstrategin ACE (Advanced Combined Encoder) har konstruerats. Programmets främsta syfte är att i förväg prova ut inställningar i ett cochleaimplantat och genom detta försöka förutsäga olika användares individuella inställningar. Programmet har validerats med utsignaler bearbetade av Cochlear Limited i deras egenkonstruerade Matlab-modul för forskning inom cochleaimplantat, NMT (Nucleus Matlab Toolbox). Samma insignal som använts av Cochlear Limited har processats av programmet och utsignalerna från detta jämfördes med utsignalerna från NMT. De bägge utsignalerna, producerade med samma inställningar, stämde bra överens. Komprimeringsfunktionen i programmet, som är en vital del av signalbehandlingen, visade sig stämma bra överens med NMT:s komprimeringsfunktion, sånär som på en relativ minskning av värdet vid starka insignaler. Programmet ska nu användas på Cochleaimplantat-sektionen vid Uppsala Akademiska sjukhus för att pröva ut individuella inställningar till användare av cochleaimplantat. Förhoppningen är att bättre inställningar ska leda till bättre talförståelse och i förlängningen, bättre upplevelse av musik.
A program that simulates the signal processing in a cochlear implant using the signal processing strategy ACE (Advanced Combination Encoder) was constructed. Its main purpose is to, in advance, predict and test different implant settings with the purpose to be able to predict individual patient's differences in implant settings. The program was validated using output signals processed by Cochlear Limited using their own Matlab Toolbox for implant research, NMT (Nucleus Matlab Toolbox). Identical signals were processed by the program and then compared with NMT:s output. The outputs, produced with several different identical settings matched each other well. The amplitude compression function, a vital part of the signal processing, also matched well, apart from a relative loss of strength at high input amplitudes. The program will now be used by the cochlear implant section at Uppsala University Hospital to try out individual settings for cochlear implant users. The hope for the future is that better implant settings will lead to improved speech and sound experience, especially, in the long run, with regards to music.

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Barrett, Jenna. "Perception of Spectrally-Degraded, Foreign-Accented Speech". Ohio University Honors Tutorial College / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ouhonors1619012518297988.

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Hallum, Luke Edward Graduate School of Biomedical Engineering Faculty of Engineering UNSW. "Prosthetic vision : Visual modelling, information theory and neural correlates". Publisher:University of New South Wales. Graduate School of Biomedical Engineering, 2008. http://handle.unsw.edu.au/1959.4/41450.

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Electrical stimulation of the retina affected by photoreceptor loss (e.g., cases of retinitis pigmentosa) elicits the perception of luminous spots (so-called phosphenes) in the visual field. This phenomenon, attributed to the relatively high survival rates of neurons comprising the retina's inner layer, serves as the cornerstone of efforts to provide a microelectronic retinal prosthesis -- a device analogous to the cochlear implant. This thesis concerns phosphenes -- their elicitation and modulation, and, in turn, image analysis for use in a prosthesis. This thesis begins with a comparative review of visual modelling of electrical epiretinal stimulation and analogous acoustic modelling of electrical cochlear stimulation. The latter models involve coloured noise played to normal listeners so as to investigate speech processing and electrode design for use in cochlear implants. Subsequently, four experiments (three psychophysical and one numerical), and two statistical analyses, are presented. Intrinsic signal optical imaging in cerebral cortex is canvassed appendically. The first experiment describes a visual tracking task administered to 20 normal observers afforded simulated prosthetic vision. Fixation, saccade, and smooth pursuit, and the effect of practice, were assessed. Further, an image analysis scheme is demonstrated that, compared to existing approaches, assisted fixation and pursuit (but not saccade) accuracy (35.8% and 6.8%, respectively), and required less phosphene array scanning. Subsequently, (numerical) information-theoretic reasoning is provided for the scheme's superiority. This reasoning was then employed to further optimise the scheme (resulting in a filter comprising overlapping Gaussian kernels), and may be readily extended to arbitrary arrangements of many phosphenes. A face recognition study, wherein stimuli comprised either size- or intensity-modulated phosphenes, is then presented. The study involved unpracticed observers (n=85), and showed no 'size' --versus--'intensity' effect. Overall, a 400-phosphene (100-phosphene) image afforded subjects 89.0% (64.0%) correct recognition (two-interval forced-choice paradigm) when five seconds' scanning was allowed. Performance fell (64.5%) when the 400-phosphene image was stabilised on the retina and presented briefly. Scanning was similar in 400- and 100-phosphene tasks. The final chapter presents the statistical effects of sampling and rendering jitter on the phosphene image. These results may generalise to low-resolution imaging systems involving loosely packed pixels.

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Magalhães, Ana Tereza de Matos. "Contribuição do avanço tecnológico do processador de fala para usuários de implante coclear Nucleus 22®". Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/5/5143/tde-03012014-123922/.

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Objetivo: Identificar as contribuições tecnológicas do processador de fala Freedom® para pacientes implantados com Nucleus 22® e a satisfação dos usuários com a nova tecnologia. Entre os novos recursos disponíveis, foram analisados o efeito da tabela de alocação de frequências, o T-SPL e C-SPL e o ajuste de pré-processamento do som (ADRO®). Material: Este estudo foi prospectivo e exploratório. Foram incluídos adolescentes e adultos implantados com Nucleus 22® no Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, usuários efetivos do processador de fala Spectra®, com alguma percepção de frases em contexto fechado e sem experiência anterior com a nova tecnologia. Foram selecionados 17 pacientes, entre as idades de 15 e 82 anos, e implantados há mais de oito anos. Para determinar a contribuição do Freedom®, os limiares auditivos e os testes de percepção de fala foram realizados com o último mapa utilizado com o Spectra® e comparados os mapas criados com o Freedom®. Para identificar o efeito da tabela de alocação de frequências, ambos os mapas convertidos (mesma tabela) e atualizados (tabela nova) foram programados. A tabela escolhida foi mantida, e foram realizados três mapas com diferentes parâmetros: o programa 1 (P1) com T-SPL de 30 dB e do C-SPL de 70 dB, programa 2 (P2) com T-SPL de 25 dB e do C-SPL de 65 dB, e o programa 3 (P3) com ADRO®. A ordem de apresentação dos mapas e dos testes foi randomizada. Para avaliar a satisfação com seus dispositivos auditivos foram utilizados os questionários SADL e APHAB após um mês e um ano de uso do Freedom®. Resultados: A contribuição do processador de fala Freedom® para pacientes usuários do Nucleus 22® foi estatisticamente superior em comparação com o Spectra® em todos os testes de percepção da fala e em todos os limiares audiométricos, tanto individualmente quanto em média, com exceção de 8000 Hz. Em relação à escolha da tabela de frequência, 64,7% dos pacientes (n=11) mantiveram o mapa com a tabela de frequências do Spectra®. Comparando os mapas com diferentes T-SPL e C-SPL, houve diferença estatística tanto nos limiares audiométricos de 500, 1000, 1500 e 2000 Hz quanto na média. Não houve diferença estatística entre os testes de fala com ou sem o uso do ADRO®. Os questionários de satisfação mostraram uma melhora estatisticamente significativa, apenas na subescala que avalia o desempenho em ambiente ruidoso e uso do telefone. Conclusão: A tecnologia contribuiu no desempenho de percepção de fala e nos limiares audiométricos dos pacientes usuários de Nucleus22®. A maioria manteve a tabela de frequência original. As mudanças nos parâmetros de T-SPL e C-SPL mostraram uma melhora dos limiares audiométricos nas frequências principais da fala. As diferenças significantes foram sutis nos questionários de satisfação, demonstrando que os pacientes já estavam adaptados e satisfeitos com o implante coclear
Objective: To identify the technological contributions of the Freedom® speech processor to the patients implanted with Nucleus 22® and the satisfaction of users of the new technology. Among the new features available, we focused on the effect of the frequency allocation table, the T-SPL and C-SPL and the pre-processing gain adjustments (ADRO®). Methods: This study was prospective and exploratory. It included teenage and adult patients implanted with Nucleus 22® who effectively used the implant with no previous experience with the new technology and had at least some speech recognition on a closed set with the Spectra® processor. Seventeen patients met the inclusion criteria, ranging in age from 15 to 82 years and deployed for over 8 years. To determine the contribution of the Freedom®, thresholds and speech perception tests were performed with the last map used with the Spectra® and the maps created for Freedom®. To identify the effect of the frequency allocation table, both converted (same table) and upgraded (new table) maps were programmed. The table selected is maintained, and maps were performed with three different parameters: the first program (P1) was programmed with 30 dB T-SPL and 70 dB C-SPL; the second program (P2) with was programmed with 25 dB T-SPL and 65 dB C-SPL; and the program 3 (P3) with ADRO®. The order of presentation of the maps and the testing was randomized. To assess satisfaction were used SADL and APHAB after one moth and one year of using the Freedom®. Results: The contribution of the Freedom® speech processor to patients with the Nucleus 22® was statistically superior compared to the Spectra® in all tests of speech perception and in all audiometric thresholds, both individually and on average, except for 8000 Hz. Regarding the choice of a frequency allocation table, 64.7% of patients (n=11) maintained the same map that had been used with the Spectra® processor. The sound field threshold was statistically significant at 500, 1000, 1500 and 2000 Hz with 25 dB T-SPL/ 65 dB C-SPL. The patients\' satisfaction there was a statistically significant improvement, only in the sub-scale of speech in noise abilities and telephone use. Conclusions: The Freedom® technology improved the performance of patients with the Nucleus 22®. Most of the patients retained the original frequency table. The changes in the parameters of T-SPL and C-SPL showed an improvement in the audiometric thresholds for the main frequencies of speech. Significant differences were subtle in questionnaires of satisfaction, demonstrating that patients were already adapted and satisfied with the cochlear implant

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6

Pieterse-Randall, Candice. "The speech processing skills of children with cochlear implants". Thesis, Stellenbosch : Stellenbosch University, 2008. http://hdl.handle.net/10019.1/2398.

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Thesis (MSL and HT (Interdisciplinary Health Sciences. Speech-Language and Hearing Therapy))--Stellenbosch University, 2008.
This study aims to describe the speech processing skills of three children ages 6;0, 6;10 and 8; 10, with cochlear implants. A psycholinguistic framework was used to profile each child’s strengths and weaknesses, using a single case study approach. Each child’s speech processing skills are described based on detailed psycholinguistically-orientated assessments. In addition, retrospective data from 1-2 years post-implantation were examined in the light of the psycholinguistic framework in order to describe each child’s development over time and in relation to time of implantation. Results showed each child to have a unique profile of strengths and weaknesses, and widely varying outcomes in terms of speech processing even though all three children had the same initial difficulty (congenital bilateral hearing loss). Links between speech processing and other aspects of development as well as contextual factors are discussed in relation to outcomes for each child. The case studies contribute to knowledge of speech processing skills in children with cochlear implants, and have clinical implications for those who work with children with cochlear implants and their families.

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Wolmarans, Hendrik Petrus. "Cochlear implant speech processing, based on the cochlear travelling wave". Diss., Pretoria : [s.n.], 2005. http://upetd.up.ac.za/thesis/available/etd-01242006-112642.

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Titterington, Jill. "Aspects of short-term memory and phonological processing in children with cochlear implants". Thesis, University of Ulster, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.400846.

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Meyer, Georg. "Models of neurons in the ventral cochlear nucleus : signal processing and speech recognition". Thesis, Keele University, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334715.

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Lim, Seow-Chuan. "Investigations into the feasibility of digital neuromorphic signal processing circuits". Thesis, Loughborough University, 1999. https://dspace.lboro.ac.uk/2134/28189.

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Modelling of the mammalian auditory system is valuable in understanding perception processes and has benefits in the design of signal processing systems and human prosthetic implants. However, as models increase in complexity, traditional methods of modelling using general purpose computers become very slow. One method of overcoming this is to use electronic implementations of these models. This thesis looks into the feasibility of auditory system implementations in digital technology, through the implementation of the Four-Stage Pitch System for pitch detection in hearing proposed by Hewitt and Meddis.

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Libros sobre el tema "Signal processing. Cochlear implants"

1

Titterington, Jill. Aspects of short-term memory and phonological processing in children with cochlear implants. [S.l: The author], 2004.

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2

Statistical signal processing for neuroscience and neurotechnology. Burlington, MA: Academic Press, 2011.

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3

Introduction to biomechatronics. Raleigh, NC: SciTech Pub., 2012.

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4

Cochlear Implants: Fundamentals and Applications (Modern Acoustics and Signal Processing). Springer, 2003.

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5

Mason, Peggy. Audition. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190237493.003.0016.

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Hearing loss is devastating because it prevents communication through verbal language and thereby produces social isolation. The experience of hearing loss or deafness is the most common sensory deficit. The experience of affected individuals is highly variable because it depends on age of onset and treatment efficacy, among many factors. The roles of the external and middle ears in conduction and of the internal ear in sensorineural processing are used as a framework for understanding common forms of hearing loss. The contributions of inner and outer hair cells to cochlear function are detailed. How cochlear amplification results from the actions of prestin in outer hair cells is explained. The roles of age, noise, genetic background, and environmental factors in presbyacusis are considered. Approaches to hearing loss, including cochlear implants and sign language, are discussed. Finally, the brain regions involved in speech production and comprehension are detailed.

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Kronenberger, William G. y David B. Pisoni. Neurocognitive Functioning in Deaf Children with Cochlear Implants. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190880545.003.0016.

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Cochlear implantation restores some attributes of hearing and spoken language to prelingually deaf children. However, reduced access to auditory and spoken-language experiences for children with cochlear implants can alter the development of downstream neurocognitive functions such as sequential processing and self-regulatory language skills, which are critical building blocks for executive functioning. Executive functioning is the active regulation of cognitive, behavioral, and emotional processes in the service of planned, organized, controlled, goal-driven behavior. This chapter presents findings from two primary lines of research on the development of executive functioning in prelingually deaf, early implanted children with cochlear implants. The first is identification of specific executive function domains that are at risk for delay in children with cochlear implants compared to hearing children. The second is reciprocal influences of executive function and spoken-language skills throughout development in children and adolescents with cochlear implants.

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Advances in Therapeutic Engineering. Taylor & Francis Group, 2012.

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Capítulos de libros sobre el tema "Signal processing. Cochlear implants"

1

Maheswari, K. T., R. Baranikumar, D. Lavanya, A. Nandhakumar y M. Srinivasan. "Audio Signal Processing for Cochlear Implants". En Springer Proceedings in Materials, 81–88. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8319-3_9.

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Grantham, D. Wesley, Daniel H. Ashmead y Todd A. Ricketts. "Sound localization in the frontal horizontal plane by post-lingually deafened adults fitted with bilateral cochlear implants". En Auditory Signal Processing, 389–96. New York, NY: Springer New York, 2005. http://dx.doi.org/10.1007/0-387-27045-0_48.

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Clopton, Ben M., James A. Wiler y Patricia M. Backoff. "Neural Processing of Complex Electric and Acoustic Stimuli". En Cochlear Implants, 223–46. New York, NY: Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4612-3256-8_16.

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Sachs, Murray B. y C. C. Blackburn. "Processing Rate Representation of Complex Stimuli in the Anteroventral Cochlear Nucleus". En Cochlear Implants, 219–21. New York, NY: Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4612-3256-8_15.

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Loizou, Philipos C. "Speech Processing in Vocoder-Centric Cochlear Implants". En Cochlear and Brainstem Implants, 109–43. Basel: S. KARGER AG, 2006. http://dx.doi.org/10.1159/000094648.

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6

Chatterjee, Monita, Shu-Chen Peng, Lauren Wawroski y Cherish Oberzut. "Voice Pitch Processing with Cochlear Implants". En IFMBE Proceedings, 49–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14998-6_13.

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7

Maki, Katuhiro y Masato Akagi. "A computational model of cochlear nucleus neurons". En Auditory Signal Processing, 84–90. New York, NY: Springer New York, 2005. http://dx.doi.org/10.1007/0-387-27045-0_11.

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8

MacLeod, Katrina M. y Catherine E. Carr. "Synaptic dynamics and intensity coding in the cochlear nucleus". En Auditory Signal Processing, 500–508. New York, NY: Springer New York, 2005. http://dx.doi.org/10.1007/0-387-27045-0_61.

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9

Neely, Stephen T., Kim S. Schairer y Walt Jesteadt. "Estimates of Cochlear Compression from Measurements of Loudness Growth". En Auditory Signal Processing, 50–59. New York, NY: Springer New York, 2005. http://dx.doi.org/10.1007/0-387-27045-0_7.

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10

Lopez-Najera, Alberto, Ray Meddis y Enrique A. Lopez-Poveda. "A computational algorithm for computing cochlear frequency selectivity: Further studies". En Auditory Signal Processing, 14–20. New York, NY: Springer New York, 2005. http://dx.doi.org/10.1007/0-387-27045-0_3.

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Actas de conferencias sobre el tema "Signal processing. Cochlear implants"

1

Cappotto, Drew, Wenye Xuan, Qinglin Meng, Chaogang Zhang y Jan Schnupp. "Dominant Melody Enhancement in Cochlear Implants". En 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). IEEE, 2018. http://dx.doi.org/10.23919/apsipa.2018.8659661.

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2

Swanson, Brett, Erika van Baelen, Mark Janssens, Michael Goorevich, Tony Nygard y Koen van Herck. "Cochlear Implant Signal Processing ICs". En 2007 IEEE 29th Custom Integrated Circuits Conference. IEEE, 2007. http://dx.doi.org/10.1109/cicc.2007.4405768.

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3

Nogueira, Waldo, Martin Haro, Perfecto Herrera y Xavier Serra. "Music perception with current signal processing strategies for cochlear implants". En the 4th International Symposium. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2093698.2093881.

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4

Meng, Qinglin, Nengheng Zheng y Xia Li. "A temporal limits encoder for cochlear implants". En ICASSP 2015 - 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2015. http://dx.doi.org/10.1109/icassp.2015.7179096.

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5

Wu, Shaoyang, Songping Mai y Chun Zhang. "FPGA implementation of CIS speech processing strategy for Cochlear Implants". En 2011 4th International Congress on Image and Signal Processing (CISP). IEEE, 2011. http://dx.doi.org/10.1109/cisp.2011.6099967.

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6

"FACE AND EYE TRACKING FOR PARAMETERIZATION OF COCHLEAR IMPLANTS". En International Conference on Bio-inspired Systems and Signal Processing. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0003792604290433.

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7

Kaibao Nie, Les Atlas y Jay Rubinstein. "Single sideband encoder for music coding in cochlear implants". En ICASSP 2008 - 2008 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2008. http://dx.doi.org/10.1109/icassp.2008.4518583.

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8

Zheng, Nengheng, Yupeng Shi, Yuyong Kang y Qinglin Meng. "A Noise-Robust Signal Processing Strategy for Cochlear Implants Using Neural Networks". En ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021. http://dx.doi.org/10.1109/icassp39728.2021.9413452.

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9

Li, Xing, Kaibao Nie, Les Atlas y Jay Rubinstein. "Harmonic coherent demodulation for improving sound coding in cochlear implants". En 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2010. http://dx.doi.org/10.1109/icassp.2010.5494908.

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10

Buyens, Wim, Marc Moonen, Jan Wouters y Bas van Dijk. "A model for music complexity applied to music preprocessing for cochlear implants". En 2017 25th European Signal Processing Conference (EUSIPCO). IEEE, 2017. http://dx.doi.org/10.23919/eusipco.2017.8081352.

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