PubMed · 11892224
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R Laszig. 2000. Cochlear implants in children (soft surgery).. https://doi.org/10.1159/000059157
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OBJECTIVE: The goal of this study was to model a cochlear implant fitting protocol based on the electrically evoked whole nerve action potential (EAP) measured using the Neural Response Telemetry capabilities of the Nucleus C124M cochlear implant. The model and data were based on the significant correlations found between the EAP threshold and growth function slope and psychophysical threshold and, dynamic range, respectively, in 12 subjects (Franck, Reference Note 3; Franck & Norton, 2001). DESIGN: Using a retrospective split-half study design, these correlations found between psychophysical mapping levels and EAP data from six of the subjects were used in a model to predict psychophysical mapping levels from EAP data of the other six subjects. RESULTS: Predicted psychophysical mapping levels from the model of the EAP-based fitting protocol closely approximated measured cochlear implant fitting psychophysics. CONCLUSIONS: The close approximation of the measured data to the model data indicates the feasibility of the clinical use of an EAP-based cochlear implant fitting protocol. The realization of this model would only require two loudness judgments from the patient, whereas traditional fitting requires 44, and would be fit in a live-voice mode, accounting for across-electrode loudness summation.
OBJECTIVE: Objective measurements can be helpful for cochlear implant fitting of difficult populations, as for example very young children. One method, the recording of the electrically evoked compound action potential (EAP), measures the nerve recruitment in the cochlea in response to stimulation through the implant. For coding strategies implemented at a moderate stimulation rate of 250 pps per channel, useful correlations between EAP data and psychophysical data have been already found. With new systems running at higher rates, it is important to check these correlations again. DESIGN: This study investigates the correlations between psychophysical data and EAP measures calculated from EAP amplitude growth functions. EAP data were recorded in 12 Ineraid subjects. Additionally, behavioral thresholds (THR) and maximum acceptable loudness levels (MAL) were determined for stimulation rates of 80 pps and 2,020 pps for each electrode. RESULTS: Useful correlations between EAP data and psychophysical data were found at the low stimulation rate (80 pps). However, at the higher stimulation rate (2,020 pps) correlations were not significant. They were improved substantially, however, by introducing a factor that corrected for disparities due to temporal integration. Incorporation of this factor, which controls for the influence of the stimulation rate on the threshold, improved the correlations between EAP measures recorded at 80 pps and psychophysical MALs measured at 2,020 pps to better than r = 0.70. CONCLUSIONS: EAP data as such can only be used to predict behavioral THRs or MCLs at low stimulation rates. To cope with temporal integration effects at higher stimulation rates, EAP data must be rate corrected. The introduction of a threshold-rate-factor is a promising way to achieve that goal. Further investigations need to be performed.