Libra3D: determining patient weight in the emergency department using optical sensors

In an emergency, every second counts: doctors administer medication adapted to the patient’s weight to counteract consequential damage from heart attacks and cerebral infarctions. In cooperation with the neurological head clinic of the University of Erlangen and Siemens Healthcare, the Libra3D project has set itself the task of supporting doctors in determining weight by means of a camera system.


A stroke patient with a brain haemorrhage is admitted to the University Hospital in Erlangen. The patient is not responsive. The emergency doctor gives the attending doctors a brief description of the symptoms, as well as the medication already administered. For further treatment, doctors administer a dose adapted on the basis of the patient’s weight. When every second counts, they resort to a common method: they estimate the weight. If a patient is given an overdosage or underdosage as a result of this, doctors can only correct this error in the further course of treatment once the exact weight has been determined by weighing the patient after the fact.

Previous studies conducted by Erlangen University Hospital have shown that when medical staff estimate a patient’s weight, about one third of the time the patient receives a dose that deviates from the ideal dose by more than ten percent. This is where a sensor system comes into play to estimate the patient’s weight. In contrast to an estimate made by a doctor, the system determines the weight on an objective basis. Doctors can easily estimate the weight of patients, if they have the same approximate stature as the patient in question.

Visual weight estimation in the Kopfklinik Erlangen.

Sensor systems

The Libra3D sensor system is based primarily on a Microsoft Kinect camera. In the clinical treatment room, this camera is hidden behind the ceiling. Various 3D sensors are suitable for compiling a three-dimensional image of the patient, but the Kinect camera stands out due to its affordable price. Many ideas investigated in research papers cannot be applied in practice. They either involve expensive sensor networks or require the patient to stand up or be moved. The appeal of this particular project is that we can obtain stable results using low-cost consumer electronics. Libra3D estimates the patient’s mass by measuring the surface area and modelling the human body. The density of the patient can then be inferred using anthropometric characteristics.

Sensor system composed of Microsoft Kinect and Optris PI400 thermal imager.
  • Fusionierte Punktwolke
  • 3D Punktwolke mit Farbinformation
  • Punktwolke mit Temperaturinformation


One of the most difficult tasks is locating the patient and filtering out the hospital beds and objects that do not need to be included in the weight estimation. The weight of the patient in the bed is issued within just a few moments.

  • Weight estimation according to Libra3d.
  • Doctors’ weight estimation.
  • Patient’s own weight estimation.
  • Weight estimation according to anthropometric characteristics.


Christian Pfitzner, Stefan May, Christian Merkl, Lorenz Breuer, Martin Köhrmann, Joel Braun, Franz Dirauf, and Andreas Nüchter. Libra3D: Body Weight Estimation for Emergency Patients in Clinical Environment with a 3D Structured Light Sensor, in Proceedings of the IEEE International Conference Robotics and Automation (ICRA '15), Seattle, WA, USA, May 2015.

Christian Pfitzner. Robotic Vision in Medical Applications: Visual Weight Estimation for Emergency Patients. Workshop Proposal to the Ph.D. Forum at the  International Conference Robotics and Automation (ICRA '15), Seattle, WA, USA, May 2015.

Christian Pfitzner, Stefan May, and Andreas Nüchter. Neural Network-based Visual Body Weight Estimation for Drug Dosage Finding. In Proceedings of the SPIE Medical Imaging Conference on Image Processing, San Diego, CA, USA, March 2016

Project participants from Nuremberg Tech

Project leader:Prof. Stefan May
Research associate:Christian Pfitzner
Research master’s candidates:Eduard Roth, Christian Merkl
Final thesis:Christian Merkl
Student project groups:Andreas Geiger, Eduard Roth, Kristina Sawinsky, Miriam Schmidmeier, Venelin Venelinov, Laura Werder
Johann Delchmann, Chris Espig, Marion Kaiser, Deniz Neufeld

Project partners

UK Erlangen

Dr Martin Köhrmann

Dr Lorenz Breuer

Senior physician in charge

Ward physician of the stroke unit


Dr. Joel Braun

Franz Dirauf

Julius Maximilians University of WürzburgProf. Andreas NüchterChair of Computer Science VII


The Libra3D project is funded by the German Federal Ministry of Education and Research (BMBF).

Reference number:03FH040PX3
Funding period:1 October 2013 to 30 September 2016
Contact:Christian Pfitzner