An automated insertion tool for cochlear implants with integrated force sensing capability

• Published in: International journal for computer assisted radiology and surgery 2014-05, Vol.9 (3), p.481-494
• Main Authors: Kobler, Jan-Philipp, Beckmann, Daniel, Rau, Thomas S., Majdani, Omid, Ortmaier, Tobias
• Format: Article
• Language: English
• Subjects: Cochlea - surgery; Cochlear Implantation - instrumentation; Cochlear Implants; Computer Imaging; Computer Science; Equipment Design; Health Informatics; Humans; Imaging; Medicine; Medicine & Public Health; Minimally Invasive Surgical Procedures - instrumentation; Models, Theoretical; Original Article; Pattern Recognition and Graphics; Radiology; Robotics - instrumentation; Surgery; Vision
• ISSN: 1861-6410; 1861-6429
• DOI: 10.1007/s11548-013-0936-1

Purpose Minimally invasive cochlear implantation and residual hearing preservation require both the surgical approach to the cochlea as well as the implant insertion to be performed in an atraumatic fashion. Considering the geometric limitations of this approach, specialized instrumentation is required to insert the electrode while preserving intracochlear membranes carrying the sensory hair cells. Methods An automated insertion tool for cochlear implants, which is capable of sensing insertion forces with a theoretical resolution of 30 μ N , is presented. In contrast to previous designs, the custom force sensor is integrated in the insertion mechanism. Moreover, a test bench for insertion studies under constant and reproducible boundary conditions is proposed. It is used to experimentally validate the force sensing insertion tool, which is achieved by comparing the acquired forces to a ground truth measurement. The results of insertion studies on both an acrylic cochlear phantom and temporal bone specimen are given and discussed. Results Results reveal that friction, occurring between the electrode carrier and the inside of the insertion tool guide tube, is likely to affect the force output of the proposed sensor. An appropriate method to compensate for these disturbances is presented and experimentally validated. Using the proposed approach to friction identification, a mean accuracy of ( 4.0 ± 3.2 ) mN is observed. Conclusions The force information provided by the proposed, automated insertion tool can be used to detect complications during electrode insertion. However, in order to obtain accurate results, an identification of frictional forces prior to insertion is mandatory. The insertion tool is capable of automatically executing the appropriate trajectories.