Research On Signal Processing Method Of Microfluidic Chip Based On Wavelet Transform

As the core of micro-total analysis system,micro-fluidic chip has many advantages,such as low sample consumption,fast and efficient analysis,simple operation,easy integration and so on,in judicial inspection,food safety,and so on.Medical medicine and environmental protection are widely used in many fields.At present,the research of microfluidic chip is mainly focused on the chip structure and the design of the detection circuit,but the research on the microfluidic chip signal is relatively less.The signal of microfluidic chip is non-stationary and weak,which is easy to be influenced by noise,so the research on signal processing method of microfluidic chip is helpful to improve the detection sensitivity of the system.It is of great significance to improve the detection limit of microfluidic chips.The research contents of this paper mainly include the following parts:The first part:the signal characteristic and signal simulation of microfluidic chip has been researched.Because the signals detected by the microfluidic chip analyzer are narrow pulse signals with different peaks,which represent different components.According to the characteristic of microfluidic chip signal,the simulation mathematical model of microfluidic chip signal was established based on Gaussian function.Based on the simulated microfluidic chip signal,the signal-to-noise ratio(SNR)and root mean square error(RMSE)were used as the evaluation indexes to verify the effectiveness of the designed signal denoising algorithm for micro-fluidic chips.Then the designed algorithm was applied to the actual microfluidic chip signal processing.Part two:the signal denoising method of microfluidic chip based on discrete stationary wavelet transform and wavelet coefficient energy element has been studied.In order to improve the signal denoising effect of microfluidic chip,a signal denoising method based on wavelet energy element and improved threshold function was proposed.The wavelet energy element double threshold function based on exponential and logarithmic function was constructed,and then the signal denoising algorithm of microfluidic chip was designed.Taking the simulated microfluidic chip signal as the research object,a 4-layer denoising simulation experiment based on db4 wavelet was carried out.The simulation results show that the proposed method is superior to the conventional threshold method,spatial correlation method and energy element floating threshold method.Part three:the signal denoising method based on double-tree complex wavelet transform and improved threshold function has been studied.In order to overcome the defect of traditional discrete wavelet transform threshold denoising method,an improved threshold-function signal denoising method based on double-tree complex wavelet transform was designed.The Bayesian theory was used to determine the threshold value of high frequency coefficient,and an improved threshold function was proposed.When the simulated microfluidic chip is processed by this method,the SNR is 75.39dB and the RMSE is 0.011.The results show that the denoising effect is better than that of discrete wavelet transform(DWT)and common double-tree complex wavelet transform.The signal denoising methods of microfluidic chips based on wavelet transform designed in this paper were applied to the analysis and detection equipment of microfluidic chips developed by ourselves.Specifically,the denoising of actual K~+,Na~+,Li~+signals detected by this equipment was carried out.The application results show that the methods can effectively process the signal and improve the performance of the microfluidic analysis and detection equipment.