This paper evaluates the potential for using robotic assistance for the insertion of commercial Perimodiolar Electrode Arrays (PEA's) that use a stylet and a pre-curved electrode body.We propose an algorithm for coordinated robotic insertion of the pre-curved electrode body and pulling of the stylet in order to provide partial control over the PEA shape. However, for robotic insertion to be a viable option for PEA's, an understanding of the statistical variability of their characteristics is essential. This paper investigates the kinematics of PEA's, their shape variability, and their expected performance during robotic insertion. An investigation of the required number of Degrees of Freedom (DoF) and the workspace is presented. A study of shape variability is carried out for characterizing shape repeatability across different insertion trials using the same electrode array. Also a study of shape variability is carried out between different electrode arrays. We simulate and evaluate the expected performance of three and four DoF robotic instruments for PEA insertion. The results support our proposed algorithm for coordinated insertion of the electrode array body and pulling of the stylet. They show that existing commerical perimodiolar arrays provide good shape repeatability. These results also point to the need for designing robotic insertion tools with at least four DoF. We believe that these results provide guidelines for future robotic instrument design for cochlear implant PEA's.

Robot-assisted cochlear implant surgery was proposed and proved to be efficient in reducing insertion forces on acrylic scala tympani models. During experiments, the authors discovered that the insertion force not only depends on the shape discrepancy between the scala tympani and the inserted electrode array, but also on the insertion speed. This paper presents a friction model that describes the whole insertion process and investigates the relationship between the insertion speed and the insertion force. Experimental and statistical results show the effectiveness of the model. Applying the friction model generates safety insertion force boundaries for future insertions and gives the optimal insertion speed. It also provides predictive force information for insertion speed feedback control law design which may be applied to robot-assisted cochlear implant surgeries.