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Posture classification of lying down human bodies based on pressure sensors array

William Cruz-Santos, Alberto Beltrán-Herrera, Eduardo Vázquez-Santacruz, Mariano Gamboa-Zúñiga

发表年份
2014
引用次数
9

摘要

Human posture classification is an important tasks in medical applications, i.e., patient monitoring, ulcer prevention, and conduct diagnostic. We propose a system for posture recognition of lying-down human bodies using a low-resolution pressure sensor array. A support vector-machine was used to perform the classification of pressure maps. Three databases were constructed in order to represent the pressure maps: pressure raw-data, HOG and SIFT image descriptor vectors. It was found that the image descriptors have improved complexity time to build the classification models rather than using raw pressure maps. Experimental results was performed in order to control a robotic hospital bed.

关键词

Artificial intelligenceLyingSupport vector machineComputer visionComputer sciencePattern recognition (psychology)Scale-invariant feature transformImage (mathematics)Medicine

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