Research On The Control Target Positioning Error In Brain Tissue Phantom Of Deep Brain Stimulation Microelectrode

DBS has became one of the most important treatment of neurological diseases, such as Parkinson and Epilepsy. But because the embedded in the internal organization and the influence of probe with large length to diameter ratio, the current clinical target positioning accuracy is not high, cause unpredictable complications, cause greater harm to patients, even life threatening. This topic based on the relatively mature technology of DBS and many experiments done by the project group. The needle planting probe strategy which is based on fuzzy control put forward by this thesis has important effects on the improvement of needle planting probe precision.Based on current researches on mechanical property mechanical property, we used gelatin to take the place of brain tissues which can visualize the process of the probe implantation and STN or GPi error measurement. Through the experiments of implanting probes into pig brain and gelatin and analyzing the variation trend of axial force, we found they have similar elasticity and viscosity. The peak force at the deep of 10mm and 15mm in pig brain are 0.01308N and 0.01435N while 0.01511N and 0.01563N in gelatin.The experiments of gelatin probe under different motion parameters showing that in the experiments of straight implanting the force stiffness of probe is accumulating while the path is increasing. They also showing that rotary motion is very useful in decreasing the axial force and the deviation. And reciprocating implantation will help to release the stress of the probe which is help to improve the direction of the probe. After all the analysis above, we can conclude that we can decrease deviation by adjust motion parameter.This article put forward a implantation strategy which combined straight motion, rotary motion and reciprocated motion which uses fuzzy logic control to control the motion of probe. After analyze the influences of different motion parameters, then confirm the change in fuzzy controller. And the article set fuzzy controller in Matlab and output the results. Then we implement experiments under the fuzzy controller and observe the probe. Finally get the all result short than 1mm, which prove it is useful to use fuzzy controller.