Prediction method of human body composition based on physiological information entropy
A prediction method and physiological information technology, applied in the field of bioinformatics, can solve problems such as high dimensionality, nonlinearity, and few samples, and achieve the effects of effective detection methods, simplified fitting models, and improved prediction accuracy
Active Publication Date: 2018-05-22
DALIAN UNIV
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There are also highly nonlinear and serious correlations between these physiological parameters, and the existing human body composition models are difficult to meet this need
[0003] With the continuous advancement of medical measurement technology, the measurable physiological characteristics have developed on a large scale, and present the characteristics of few samples and high dimensionality, which brings great challenges to the processing and analysis of traditional physiological data, among which redundant features The existence of the indirect aggravated the adverse effects, resulting in insufficient prediction of human body composition
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[0031] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.
[0032] Before detailing the prediction method of human body composition based on physiological information entropy, the collection of parameters required by this method and related calculation formulas are introduced first.
[0033] First, the original feature set of human physiological parameters is constructed. Use the eight-segment human body impedance measuring instrument to measure the eight-segment impedance value and the general physiological characteristic parameters of the human body, and select the eight-segment impedance value, gender, age, height, weight, and race as the first feature. Then, the second feature is generated from the first feature through algebraic transformation, that is, the combination of the square, reciprocal and pr...
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The invention discloses a method for predicting human body composition based on physiological information entropy. Compared with the prior art, the human body composition prediction method based on physiological information entropy of the present invention can effectively reduce the redundancy among characteristic parameters, simplify the fitting model of human body composition prediction; solve the modeling problem of numerous parameters and parameter coupling ; The established human body composition prediction model can improve the prediction accuracy of human body composition, and provide more effective detection means for human body composition research and clinical application.
Description
technical field [0001] The invention relates to the field of bioinformatics, in particular to a method for predicting human body composition based on physiological information entropy. Background technique [0002] Changes in body composition reflect changes in physical health to a certain extent. Accurate prediction of body composition is of great significance to the regulation of human nutritional status and the prevention of diseases. There are many parameters that affect body composition, mainly including physiological electrical impedance parameters and general physiological characteristic parameters. There are also highly nonlinear and serious correlations between these physiological parameters, and the existing human body composition models are difficult to meet this need. [0003] With the continuous advancement of medical measurement technology, the measurable physiological characteristics have developed on a large scale, and present the characteristics of few samp...
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IPC IPC(8): G06F19/00
Inventor 陈波张爱强高秀娥王运明
Owner DALIAN UNIV