When tested in challenging and realistic noise environments, the Naida CI UltraZoom adaptive beamformer resulted in significantly lower mean SRTs than when the T-Mic alone was used.

Access to low-frequency acoustic information in cochlear implant patients leads to better speech understanding in noise. Electrocochleography (ECochG) can provide real-time feedback about the health of the cochlea during the insertion process with the potential to reduce insertion trauma. We describe our experiences of using this technique. Data from 47 adult subjects with measurable residual hearing and an Advanced Bionics (Valencia, CA) SlimJ (46) or MidScala (1) electrode array were analyzed. ECochGs were recorded intraoperatively via the implant. The surgeon adjusted the course of the electrode insertion based on drops in the ECochG. The final array position was assessed using postoperative imaging and pure tone thresholds were measured before and after surgery. Three different patterns of ECochG response amplitude were observed: Growth, Fluctuating and Total Loss. Subjects in the growth group showed the smallest postoperative hearing loss. However, the group with fluctuating amplitudes showed no meaningful correlation between the ECochG responses and the postoperative hearing loss, indicating that amplitude alone is insufficient for detecting damage. Considering the phase of the signal additionally to the amplitude and reclassifying the data by both the phase and amplitude of the response into three groups Type I–Type III produced statistically significant correlations between postoperative hearing loss and the grouping based on amplitude and phase respectively. We showed significantly better hearing preservation for Type I (no drop in amplitude) and Type II (drop with a concurrent phase shift), while Type III (drop without concurrent phase shift) had more surgery induced hearing loss. ECochG potentials measured through the implant could provide valuable feedback during the electrode insertion. Both the amplitude and phase of the ECochG response are important to consider. More data needs to be evaluated to better understand the impact of the different signal components to design an automated system to alert the surgeon ahead of damaging the cochlea.

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