Research On Signal Conditioning For Piezoresistive Intracranial Pressure Sensors

Intracranial pressure is an important neurosurgery clinical and research observationsindex, it is great significance for guiding treatment, evaluating disease, and improving theprognosis. For intracranial pressure monitoring, the traditional invasive detection method hashigh risk, and cause trauma in patients. With the development of sensor technology, more andmore silicon piezoresistive pressure sensor used in the measurement of intracranial pressure.In order to solve the temperature drift and non-linearity of silicon piezoresistive sensors,this thesis analyzes and compares the existing signal conditioning methods of the pressuresensor, then design solutions based on intelligent signal conditioning chip PGA309. Thesolution includes both hardware and software design. Before hardware and software design, itis important to analyze the error causes of the silicon piezoresistive sensors. To describe thePGA309’s temperature compensation and nonlinear correction principle, a reasonablemathematical model is chosen to describe the sensor. The signal conditioning circuit isdesigned based on PGA309. The circuit is used to amplify the signal, filtering, andanti-jamming. In order to communicate with the computer, the corresponding interface circuitis designed. In terms of software design, MATLAB is use to design the compensation andcalibration environment. The software has friendly graphical user interface. As MATLAB isgood at mathematics, it is very easy to maintain the arithmetic. On the basis of completehardware and software design, series of experiments is designed to evaluate the compensationeffect. The experimental results show that the compensated sensor’s signal has significantlyimproved and the sensor’s comprehensive error is less than0.5%.