John M. Heasman

Effect of interphase gap and pulse duration on electrically evoked potentials is correlated with auditory nerve survival.

We investigated the effect of pulse duration (PD) and interphase-gap (IPG) on the electrically-evoked auditory brain stem response (EABR) and viiith nerve compound action potential (ECAP) of deafened guinea pigs in order to test the hypothesis that the extent of change in these neural responses is affected by the histological status of the auditory nerve. Fifteen guinea pigs were deafened by co-administration of kanamycin and furosemide. Animals were acutely implanted with an 8-band electrode array at 1, 4 or 12 weeks following deafening. EABR and ECAP input/output functions were recorded in response to charge balanced biphasic current pulses. We determined the change in current required to equalize; (i) the EABR amplitude when the duration of the current pulse was doubled (104-208 micros/phase); and (ii) the EABR and ECAP amplitudes when the IPG was increased from 8 to 58 micros using a 104 micros/phase current pulse. Following the completion of each experiment the cochleae were examined quantitatively for spiral ganglion neuron survival. As expected, the current level required to evoke an EABR with equal amplitude was lower when the animal was stimulated with current pulses of 208 compared with 104 micros/phase. Moreover, the current level required to evoke EABR/ECAPs with equal amplitude was lower when current pulses had an IPG of 58 versus 8 micros. Importantly, there was a reduction in the magnitude of this effect with greater neural loss; the reduced efficacy of changing both PD and IPG on these electrically-evoked potentials was statistically correlated with neural survival. These results may provide a tool for investigating the contribution of auditory nerve survival to clinical performance among cochlear implant subjects.

A Wavelet-Based Noise Reduction Algorithm and Its Clinical Evaluation in Cochlear Implants

Noise reduction is often essential for cochlear implant (CI) recipients to achieve acceptable speech perception in noisy environments. Most noise reduction algorithms applied to audio signals are based on time-frequency representations of the input, such as the Fourier transform. Algorithms based on other representations may also be able to provide comparable or improved speech perception and listening quality improvements. In this paper, a noise reduction algorithm for CI sound processing is proposed based on the wavelet transform. The algorithm uses a dual-tree complex discrete wavelet transform followed by shrinkage of the wavelet coefficients based on a statistical estimation of the variance of the noise. The proposed noise reduction algorithm was evaluated by comparing its performance to those of many existing wavelet-based algorithms. The speech transmission index (STI) of the proposed algorithm is significantly better than other tested algorithms for the speech-weighted noise of different levels of signal to noise ratio. The effectiveness of the proposed system was clinically evaluated with CI recipients. A significant improvement in speech perception of 1.9 dB was found on average in speech weighted noise.