A Platform Based On Smartphone And Microfluidic Device For Quantitative Point-of-Care Testing

Point-of-care testing(POCT),refers to a medical diagnosis method that can analyze the samples and obtains the detection results at the sampling site^[1].Microfluidic chip is small,integrated and automatic,which has been touted as a promising tools for point-of-care testing.However,microfluidic experiment can only be carried out in the laboratory because it relies on electron microscope,computer and other large-scale equipment to output and analysis the results.Therefore,this paper proposes to build a portable platform with smartphone-microscope that can replace electron microscope as an output device in microfluidic experiment.This platform can be used to analyse the particle concentration of some specific solution with the help of induced charge electroosmosis(ICEO).In addition,this paper also developed a mini app that can be used to count the particle in picture very quickly,which facilitates more researchers to use the platform to carry out scientific research.Firstly,this paper analyzes the formation mechanism of ICEO,and deduces the slip velocity formula of electroosmotic flow under AC signal based on RC equivalent circuit and Helmholtz formula.The relationship between ICEO and particle aggregation is then explained.We also analyze the forces acting on particles and its influences on particle velocity.Secondly,this paper establishes the numerical simulation model of electroosmotic flow in microchannel in COMSOL.We analyze the changes of slip velocity and particle concentration status caused by different parameters of electrical signal amplitude,frequency and channel structure.Then,we determine the geometric parameters of the microchannel and design the microfluidic chip.At the same time,according to the simulation results,the optimal time of electroosmosis capture is preliminarily established,that is,the time when the number of particles in the field of vision reaches the maximum and the dispersion is high,which is good for the identification of particles.Then,this paper investigates the imaging effects of four types of smartphone microscopes on polystyrene microspheres,and compares their advantages and disadvantages from various aspects.Wi Fi-connecting smartphone microscope is selected because of its best performance.The POCT microscopy platform for microfluidic chip is built based on Wi Fi-connecting smartphone microscope with the help of some workpieces desgined by ourselves.Then,we count t he number of particles in the field of vision by smart phone and POCT platform,and draw the relationship curve between the number of particles and its concentration with the help of ICEO.Finally,taking the particle images as samples,this paper realizes the recognition and counting of particles on computer by Open CV,and we encapsulate the particle-counting module into a Web application by using a web development framework named Django.Then,we deploy the hole project on Tencent cloud server.We also design and develop the front-end pages of mini app.At last,we debug and improve the particle counting program.The POCT microscopy platform established in this paper can be used for the rapid detection of particle concentration of some specific solution by cooperating with the self-developed mini app,which has a broad application prospect in the field of POCT.