ArticleSensors (Basel, Switzerland)2018
Body Weight Estimation for Dose-Finding and Health Monitoring of Lying, Standing and Walking Patients Based on RGB-D Data.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Machine learning assisted noncontact neonatal anthropometry using FMCW radar.Scientific reports · 2025Article
- Measurement of Human Body Segment Properties Using Low-Cost RGB-D Cameras.Sensors (Basel, Switzerland) · 2025Article
- Total body weight estimation by 3D camera systems: Potential high-tech solutions for emergency medicine applications? A scoping review.Journal of the American College of Emergency Physicians open · 2024Article
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Authors and funding
3 authors.
Funding
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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.
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Registered trials
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