Description: A new system for automatic registration, storage, processing and analysis of sedimentation curves for settling of micro anoparticles in technical or biological suspensions is studied/ The aim of the developed system is reasonable quantitative estimation of the aging indexes of technical suspensions, the activity level in the microbiological suspensions, or medical diagnostics of diseases on the samples of biological tissues of patients. The elaborated system includes a centrifuge to create an inhomogeneous force field that accelerates the settling process up to 10-20 minutes instead of 1-3 hours in the slow gravitation sedimentation. The sedimentation curves have been registered as the time dependencies of a height of the column of the base fluid at the top of the sedimentation tube using special optical sensors. The mathematical model of the liquid under study as a three-phase suspension of aggregating solid particles, and a computer code for curve processing and calculation of a series of indices characterizing the suspension’s state are developed. The engineered system with computer processing, statistical analysis and the developed mathematical model has been successfully tested on the patients with potential medical and food allergy for some allergens. An example of using the system is given on the evaluation of the erythrocyte aggregation rate in the settling blood sample for different groups of diseases. As it was shown on the accumulated database (726 curves of healthy volunteers and patients with oncology, stroke, pneumonia and diabetes) the proposed additional indicators like the value of the first local maximum of the settling speed and the time of its attainment, magnitudes of the initial and differential phase curves provide additional information for differential diagnostics of the diseases. The determined parameters could be used for more precise diagnostics based on the artificial intelligence that is promising for more reliable differential diagnostics of severe disease and the quantitative estimation of success of their medical treatment.
Keywords: diagnostic information, microparticles, nanoparticles, aggregation, sedimentation, mathematical modeling
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