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Detection of bed position for automation of patient‐monitoring function
Author(s) -
Inoue Madoka,
Yasui Toshiyuki,
Taguchi Ryo,
Umezaki Taizo
Publication year - 2018
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.12122
Subject(s) - computer vision , artificial intelligence , position (finance) , automation , computer science , process (computing) , falling (accident) , image (mathematics) , monocular , engineering , medicine , mechanical engineering , environmental health , finance , economics , operating system
In hospitals, in order to prevent a patient from falling and fall accidents, there is an increasing demand to detect a lifting movement and a leaving‐off movement of a patient with a camera installed in a hospital room. As a measure for efficiently detecting these operations, a process of specifying a bed position which is an occurrence position of an action is effective. We propose a method to detect bed position from image of monocular camera, using image features and framework of machine learning. By generating a viewpoint conversion image for an input image, a uniform bed shape is acquired even for images at different camera positions. Evaluation was made with 2160 still images and 3888 scene moving images to confirm the usefulness of the method.