RESEARCH DATABASE

InBody Scholar

InBody continues to work closely with academic researchers on a global scale to develop more in-depth clinical applications of body composition.
With our long history in the industry, we provide more than 6,000 research and publications.
Research title with ★ indicates InBody recommended paper.

A human body physiological feature selection algorithm based on filtering and improved clustering

Principle/Accuracy
Author
B Chen et al.
Used Parameters : Impedance, TBW, FFM, BFM

Publication Year : 2018

Country : China

Journal : PLoS One

Research The body composition model is closely related to the physiological characteristics of the human body. At the same time there can be a large number of physiological characteristics, many of which may be redundant or irrelevant. In existing human physiological feature selection algorithms, it is difficult to overcome the impact that redundancy and irrelevancy may have on human body composition modeling. This suggests a role for selection algorithms, where human physiological characteristics are identified …
Full text