Detection Technique Of Variation Of Blood Oxygen At Specific Position Of Human Brain For PSoC Platform

Among the techniques that can detect the variation of blood oxygen at specific position of human brain,functional Near-Infra Red Spectroscopy,known as f NIRS,is promising for its accuracy and timeliness,which provides a way to prevent communication errors and misjudgments caused by changes in cerebral blood oxygen,especially for those who are in high-risk special industries such as pilots.However,the unusual variation of the blood oxygen happening at ectocinerea,which is the main factor that disturbs the right decisions,is hard to be detected because it is submerged in the physiological disturbances such as cardiac cycle,respiration,and human body's low-frequency oscillations.The purpose of this thesis is to find an efficient way to extract the signal of interest so as to improve the detection accuracy of cerebral blood oxygen signals.In this thesis,the main research work is as follows.1.Based on the analysis of mechanism of physiological interference and signals measured by the cerebral blood oxygen detection system,a signal extraction method based on crosscorrelation technology was proposed,the main idea of which is estimating physiological signals of deep signals through shallow physiological interference using a dual banana model instead of a single banana model.2.Aiming to the signal characteristics of the shallow and deep signals detected from the head,two adaptive filtering algorithms,LMS and RLS,are designed to extract the signals.The experiments which are conducted using both the simulating signals and measured interference plus quasi-true stimulus signals respectively verified the effectiveness of the two adaptive filtering algorithms.3.Based on the in-depth analysis of the blood oxygen saturation measurement system‘s measurement principle and module configuration based on PSoC 5,the program optimization for the hardware platform was completed,and the LMS adaptive filtering algorithm was transplanted on the PSoC platform successfully,as well as the design of data transmission programs for upper and lower computers.4.The experiments for human brain blood oxygen detection was carried out.It was proved that the adaptive filter algorithms designed in this thesis can extract the difference signal which is independent of the reference signal from the oxygen signal containing physiological interference.Theoretical analysis and experimental verification show that the two adaptive filter algorithms designed in this thesis can detect the blood oxygen change signals from blood oxygen signals containing physiological interference,which provides a design basis and technical support for the actual application of this technology.