• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.205-211
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• 2007

A novel envelope extraction algorithm for speech processor of cochlear implants, called adaptation algorithm, was developed which is based on a adaptation effect of the inner hair cell(IHC)/auditory nerve(AN) synapse. We achieved acoustic simulation and hearing experiments with 12 normal hearing persons to compare this adaptation algorithm with existent standard envelope extraction method. The results shows that speech processing strategy using adaptation algorithm showed significant improvements in speech recognition rate under most channel/noise condition, compared to conventional strategy We verified that the proposed adaptation algorithm may yield better speech perception under considerable amount of noise, compared to the conventional speech processing strategy.

• Journal of Biomedical Engineering Research
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• v.29 no.1
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• pp.25-31
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• 2008

It is well known that temporal information, i.e speech onset, about input speech can be represented to the response nerve signal of auditory nerve better depending on the adaptation effect occurred in the auditory nerve synapse. In addition, the performance of a speech processor of cochlear implant can be improved by the adaptation effect. In this paper, we observed the emphasis characteristic of speech onset in the recently proposed adaptation algorithm, analyzed the characteristic of performance change according to the variation of parameters and compared with transient emphasis spectral maxima (TESM) is the previous typical strategy. When observing false peaks which are generated everywhere except speech onset, in the case of the proposed model, the false peak were generated much less than in the case of the TESM and it is more distinguishable under noise.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.531-531
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• 2000

The challenge is to control unstable nonlinear dynamic systems using only sparse feedback from the environment concerning its performance. The design of such controllers can be achieved by evolving neural networks. An evolutionary approach to train neural networks in realtime is proposed. Evolutionary strategies adapt the weights of neural networks and the threshold values of neuron's synapses. The proposed method has been successfully implemented for pole balancing problem.

• Journal of Biomedical Engineering Research
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• v.28 no.5
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• pp.694-702
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• 2007

The adaptation effect originating from the chemical synapse between auditory nerve and inner hair cell gives advantage in accurate representation of temporal cues of incoming speech such as speech onset. Thus it is expected that the modification of conventional speech processing strategies of cochlear implant(CI) by incorporating the adaptation effect will result in considerable improvement of speech perception performance such as consonant perception score. Our purpose in this paper was to evaluate our new CI speech processing strategy incorporating the adaptation effect by the observation of auditory nerve responses. By classifying the presence or absence of speech from the auditory nerve responses, i. e. spike trains, we could quantitatively compare speech onset detection performances of conventional and improved strategies. We could verify the effectiveness of the adaptation effect in improving the speech onset representation characteristics.