For cochlear implants (CI) a final position of the electrode array (EA) along the inner wall of the spirally shaped cochlea is considered to be beneficial because it results in a closer proximity to the auditory nerve fibers. A shape memory effect (SME) could facilitate such shift of the EA toward the cochlear inner wall, but its implementation remains to be solved. The current study presents an EA prototype featuring the SME with minute adjustments of the material properties of Nitinol, a shape memory alloy, in combination with a suitable cooling strategy to prevent premature curling. Ten samples were successfully inserted by a CI surgeon into an artificial cochlear model submerged into a temperature‐controllable water bath to simulate temporary hypothermia of the inner ear (31°C). Gentle insertions were possible, with an average insertion speed of 0.81 ± 0.14 mm/s. After recovery of body temperature, the desired position shift toward the modiolus was observed in all trials. Angular insertion depth increased by approximately 81.8° ± 23.4°. We demonstrate for the first time that using the body temperature responsive SME for perimodiolar EA positioning is feasible and does not impede a gentle surgical insertion.

Electric stimulation of the auditory nerve using a cochlear implant (CI) is presumed to be superior when the electrode array (EA) is placed close to the inner wall of the cochlea. Nitinol is investigated as an actuator that enables an intracochlear shape change of the EA from a straight configuration (also necessary for the insertion) to a spiral shape fitting to the inner wall. As shape setting of the thin Nitinol wires is crucial, a method to quantify the accuracy of the shape setting is presented. To measure the trained shape of thin Nitinol wires (ø 100 μm) a contactless, optical method was developed. For each wire, a photomicrograph was captured and processed using a custom Matlab algorithm. Threshold based segmentation followed by morphological operations to remove artefacts were applied to extract the wire’s shape. Utilizing an iterative closest point (ICP) algorithm the actual shape was registered to the desired spiral path. Finally, the root mean squared error describing the deviation between both spirals was calculated as a measure for the “shape error” (εshape). In total 147 Nitinol wires of 16 batches were analyzed to quantify the reliability of the shape setting procedure. The proposed method was successfully applied in all samples. On average εshape was 0.06 ± 0.02 mm. Deviation from the desired shape was < 0.1 mm (< 0.15 mm) in 95% (99%) of the samples. In summary, the presented method is suitable to control the trained shape of thin Nitinol wires. Furthermore, our results confirm a high reliability of the shape setting procedure used for our thin Nitinol actuators intended for future applications in CI EAs.

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