A response surface model predicting the in vivo insertion behavior of micromachined neural implants

Abstract

The mechanical damage caused by the insertion of a foreign body into living tissue is inevitable, especially when a considerable stiffness mismatch is present, as in the case of micromachined neural implants and brain tissue. However, the response surface model based on a central composite experimental design described in this study showed that for particular configurations of the implant tip angle, width, thickness or insertion speed, some of these factors could be safely increased without causing an unwanted significant force or tissue dimpling increase. The model covers chisel tip angles between 10° and 50°, implant widths within the 200-400 µm range and thicknesses between 50 and 150 µm. The insertion speed has been varied from 10 up to 100 µm s(-1) to reach a final insertion depth of 6 mm. Coating the implant with parylene C proved to be beneficial in reducing the friction between the implant and the surrounding tissue. Successfully validated for a particular implant geometry, this model could be used as an insertion behavior prediction tool for the design optimization of future neural implants.