Acta CAMU
Published May 11, 2023 | Version 2
Journal article Open

AUTOMATION MEASUREMENT OF HUMAN ANTHROPOMETRY DATA FOR DIAGNOSTICS ASSESSMENT OF HEALTH LEVEL

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This paper presents the automation of the measurement of the main parameters of the human body using a high-level Python programming language using the MediaPipe and OpenCV libraries to study practically important issues in screening the population to determine the level of health. For medical institutions and public health authorities, anthropometric data of the population are of considerable interest, the mass character of anthropometric studies makes it possible to compare and evaluate the variability of the characteristics of different groups based on measurements of a large number of individuals, as well as to establish the features of their physical structure, which makes it possible to quantify their variability and make it possible to constantly monitor and predict the level of public health. We propose a method for automating the measurement of the human body in real time based on a unified deep learning architecture, and the architecture of the model is embedded in the structure of a neural network using artificial intelligence. The results of comparing the values of these dimensional features taken with the help of a centimeter tape with standards and calculated on the basis of non-contact measurements showed sufficient accuracy. The relative error is no more than 2% by measuring the height of a person, no more than 3.5% by weight, which is acceptable for scientific analysis and forecasting the state of human health loss according to anthropometric data with known methods to this day.

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References

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