Key Design Of The Wireless Passive DBS And Detection Of Deep Brain Evoked Potentials In Strong Noise

Deep Brain Stimulating could cure Parkinson’s disease without causing damageto the brain tissues. But the monopolization of foreign DBS’s technology drives up theprice of this device. Moreover, due to the limit of battery, the Deep Brain Stimulator(DBS) include its battery will have to be replaced via surgery in clinical application.And all of this will increase patient’s suffering and economic burden. So research ofthe DBS overall design and development of lifetime use and low cost DBS isimperative.Compared to the DBS technology development, its therapeutic mechanism is notclear, the detection and research of weak evoked potentials signal under strongstimulation are particularly important for its mechanism study, as the result in thatthese could not only further improve the DBS, but also be of great significance for theresearch and treatment of neurological diseases.This paper proposed two designs for lifelong DBS: wireless passive DBS andrechargeable DBS, the design of the nerve signal acquisition system in strong noise ispresented too. Then rat EEG under stimulating is detected and the evoked potentialsare extracted from them.The main parts and achievements are as following:1) A design of wireless passive pulse generator was innovatively proposed, and itcould adjust parameters of the stimulation pulses. This design didn’t need battery invivo stimulation parts, so the DBS could be lifetime use after the first implant. Thewireless passive DBS prototype was developed.2) Super-capacitor was used as the energy storage unit in vivo, the wirelesscharging scheme and output voltage regulation circuit was designed. A pulsegenerator based on MOSFET was presented which made it easier to adjust theparameters of the DBS, and the system has a high stability. The rechargeable DBSprototype was produced.3) The high-precision signal acquisition system was developed for the detectionof weak EEG which differed six orders in magnitude from stimulation signal.Combining the oversampling technology and high-resolution, high-speed ADCdevices to achieve large dynamic range signal acquisition, thus the acquisition of the rat deep brain potential was completed under the strong noise which includessynchronization stimulation.4) The signal-to-noise ratio of stimulation evoked EEG is very low because itwas buried in strong noise and Spontaneous EEG. This paper studied the extractionmethods of deep evoked potential in rat brain under different requirements based onlinear and nonlinear theory. The algorithm utilized the signal de-noised by liftingwavelet transform as the input of adaptive signal enhancer to extract evoked potential.This method could take very short time to achieve a high precise, and it hadprominent effect on the real-time processing. What’s more, the method of combiningempirical mode decomposition method with blind source separation was raised toextract single channel deep brain evoked potentials. This method can not only be usedin the separation of non-stationary signal, but also be applied to the situation wherethere were more source signals than observed signals.