Human Pose Estimation For Decubitus Prophylaxis

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Human pose estimation for decubitus prophylaxis

Human pose estimation for decubitus prophylaxis
Author :
Publisher : Universitätsverlag Potsdam
Total Pages : 82
Release :
ISBN-10 : 9783869565514
ISBN-13 : 3869565519
Rating : 4/5 (519 Downloads)

Book Synopsis Human pose estimation for decubitus prophylaxis by :

Download or read book Human pose estimation for decubitus prophylaxis written by and published by Universitätsverlag Potsdam. This book was released on 2023-06-27 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decubitus is one of the most relevant diseases in nursing and the most expensive to treat. It is caused by sustained pressure on tissue, so it particularly affects bed-bound patients. This work lays a foundation for pressure mattress-based decubitus prophylaxis by implementing a solution to the single-frame 2D Human Pose Estimation problem. For this, methods of Deep Learning are employed. Two approaches are examined, a coarse-to-fine Convolutional Neural Network for direct regression of joint coordinates and a U-Net for the derivation of probability distribution heatmaps. We conclude that training our models on a combined dataset of the publicly available Bodies at Rest and SLP data yields the best results. Furthermore, various preprocessing techniques are investigated, and a hyperparameter optimization is performed to discover an improved model architecture. Another finding indicates that the heatmap-based approach outperforms direct regression. This model achieves a mean per-joint position error of 9.11 cm for the Bodies at Rest data and 7.43 cm for the SLP data. We find that it generalizes well on data from mattresses other than those seen during training but has difficulties detecting the arms correctly. Additionally, we give a brief overview of the medical data annotation tool annoto we developed in the bachelor project and furthermore conclude that the Scrum framework and agile practices enhanced our development workflow.


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