A new approach for speech synthesis in cochlear implant systems based on electrophysiological factors

A Fast Approximate Method for Predicting the Behavior of Auditory Nerve Fibers and the Evoked Compound Action Potential (ECAP) Signal

Background:

The goal of the current research is to develop a model based on computer simulations which describes both the behavior of the auditory nerve fibers and the cochlear implant system as a rehabilitation device.

Methods:

The approximate method was proposed as a low error and fast tool for predicting the behavior of auditory nerve fibers as well as the evoked compound action potential (ECAP) signal. In accurate methods every fiber is simulated; whereas, in approximate method information related to the response of every fiber and its characteristics such as the activation threshold of cochlear fibers are saved and interpolated to predict the behavior of a set of nerve fibers.

Results:

The approximate model can predict and analyze different stimulation techniques. Although precision is reduced to <1.66% of the accurate method, the required execution time for simulation is reduced by more than 98%.

Conclusion:

The amplitudes of the ECAP signal and the growth function were investigated by changing the parameters of the approximate model including geometrical parameters, electrical, and temporal parameters. In practice, an audiologist can tune the stimulation parameters to reach an effective restoration of the acoustic signal.

Low variable rate stimulation strategy for cochlear implants using temporal cues and electrophysiological factors

BACKGROUND

The performance of a cochlear implant (CI), especially in conveying pitch depends on its electrical stimulation strategy.

OBJECTIVE

The present study proposes a variable-rate stimulation algorithm which improves speech emotion perception by using temporal fine-structure cues and electrophysiological parameters of the patient.

METHODS

This method is based on the coding of the phase information at the peak time intervals of the band-passed signals. The stimulation pulse is generated at the time of peak occurrence, which is able to excite the number of fibers with a discharge probability above a threshold. Calculating the discharge probability is based on the excitable fiber model and taking into account the biological characteristics of the patient, such as the fiber threshold and the distribution of remaining intact fibers.

RESULTS

The results of the emotion detection test on selective reconstructed sentences from the Persian emotional speech database (Persian ESD) indicated that the listeners have been able to detect the emotion by an average of 83.82% using the proposed stimulation algorithm while it was 75% and 48.03% for the zero-crossing and the continuous interleaved sampling (CIS), respectively. Furthermore, the number of pulses compared to the zero-crossing and the CIS has decreased by 76.3% and 75.4%, respectively.

CONCLUSIONS

In this paper, a stimulation method was proposed for cochlear implants by considering the patient's biological parameters. It has been successful in transmitting speech emotion despite the reduction of stimulating pulses. This has some advantages such as reducing the interaction of current fields between electrodes during stimulation and reducing battery usage.