Research On Key Technology Of Colorimetric Point-of-care Detection Based On Smartphone

Colorimetric point-of-care detection has always been a research hotspot in the field of chemical analysis and medical detection as an on-site diagnostic method.Compared with the traditional detection method,the colorimetric point-of-care detection has the advantages of rapid acquisition of results,simple operation,real time,portability and low cost,etc.,and it solves the problem of lack of medical facilities in the developing countries.With the development of science and technology,smartphones have become the preferred device for colorimetric point-of-care detection due to their superior camera performance and portability.However,the existing colorimetric detection system still has two disadvantages:(1)the light-tight box is needed to isolate the influence of ambient light,(2)the computational complexity increases with the number of probes.In order to solve the above problems,this paper proposes a probe color calibration method(PCCM)and an optimal probe selection algorithm(OPSA),and develops a system that can directly perform colorimetric detection in natural light conditions indoor.The main work and innovation of the paper are as follows.1.In order to perform colorimetric detection directly in natural light conditions,PCCM is proposed in this paper,and a separate color calibration formula is established for each probe to eliminate the effects of ambient light.The experimental results show that for the analyte combinations of a variety of concentration levels,the classification accuracies after using PCCM are higher than the accuracies after using traditional color calibration method.With PCCM,colorimetric detection in natural light conditions can be achieved,and the light-tight box is not needed to isolate the effects of ambient light.2.This paper proposes OPSA based on the traditional stepwise discriminant analysis algorithm.OPSA can remove redundant probes in the probe array,lower the amount of calculation,and reduce the detection cost.The experimental results show that for the analyte combinations of multiple concentrations,the classification accuracies after OPSA are equal to or even higher than the original classification accuracies,which proves the feasibility and correctness of OPSA.3.A colorimetric real-time detection system based on smartphones is developed,and a smartphone is used to extract color information of probes after reaction.The results of the discrimination will be returned to the smartphone immediately after sending the color information to the remote server.The colorimetric detection system can perform rapid and real-time colorimetric detection in natural light conditions.4.A paper-based microfluidic chip is designed and manufactured.Combined with the smartphone-based colorimetric point-of-care detection system,the chip further enhance the portability of colorimetric point-of-care detection.