Body Weight Estimation for Dose-Finding and Health Monitoring of Lying, Standing and Walking Patients Based on RGB-D Data
Sensors (April 2018)
Abstract
This paper describes the estimation of the body
weight of a person in front of an RGB-D camera. A
survey of different methods for body weight
estimation based on depth sensors is given. First,
an estimation of people standing in front of a
camera is presented. Second, an approach based on a
stream of depth images is used to obtain the body
weight of a person walking towards a sensor. The
algorithm first extracts features from a point cloud
and forwards them to an artificial neural network
(ANN) to obtain an estimation of body
weight. Besides the algorithm for the estimation,
this paper further presents an open-access dataset
based on measurements from a trauma room in a
hospital as well as data from visitors of a public
event. In total, the dataset contains 439
measurements. The article illustrates the efficiency
of the approach with experiments with persons lying
down in a hospital, standing persons, and walking
persons. Applicable scenarios for the presented
algorithm are body weight-related dosing of
emergency patients.
Links and resources
- DOI:
- 10.3390/s18051311
- URL:
- https://robotik.informatik.uni-wuerzburg.de/telematics/download/mdpi2018.pdf
- BibTeX key:
- SENSORS2018
- search on:
There is no review or comment yet. You can write one!