title: Problems of video-based pain detection in patients with dementia: a road map to an interdisciplinary solution.
abstract: Given the unreliable self-report in patients with dementia, pain assessment should also rely on the observation of pain behaviors, such as facial expressions. Ideal observers should be well trained and should observe the patient continuously in order to pick up any pain-indicative behavior; which are requisitions beyond realistic possibilities of pain care. Therefore, the need for video-based pain detection systems has been repeatedly voiced. Such systems would allow for constant monitoring of pain behaviors and thereby allow for a timely adjustment of pain management in these fragile patients, who are often undertreated for pain.
  
  
  
  In this road map paper we describe an interdisciplinary approach to develop such a video-based pain detection system. The development starts with the selection of appropriate video material of people in pain as well as the development of technical methods to capture their faces. Furthermore, single facial motions are automatically extracted according to an international coding system. Computer algorithms are trained to detect the combination and timing of those motions, which are pain-indicative.
  
  
  
  We hope to encourage colleagues to join forces and to inform end-users about an imminent solution of a pressing pain-care problem. For the near future, implementation of such systems can be foreseen to monitor immobile patients in intensive and postoperative care situations.
authors.affiliation: Physiological Psychology, Otto-Friedrich University Bamberg, Bamberg, Germany. m.kunz@umcg.nl.|Department of General Practice, Section Gerontology, University of Groningen, University Medical Center Groningen, PO Box 196 (HPC FA21), 9700 AD, Groningen, The Netherlands. m.kunz@umcg.nl.
authors.forename: Miriam
authors.initials: M
authors.lastname: Kunz
authors.affiliation: Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany.|Cognitive Systems Group, Faculty Information Systems and Applied Computer Science, Otto-Friedrich University Bamberg, Bamberg, Germany.
authors.forename: Dominik
authors.initials: D
authors.lastname: Seuss
authors.affiliation: Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany.
authors.forename: Teena
authors.initials: T
authors.lastname: Hassan
authors.affiliation: Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany.
authors.forename: Jens U
authors.initials: JU
authors.lastname: Garbas
authors.affiliation: Cognitive Systems Group, Faculty Information Systems and Applied Computer Science, Otto-Friedrich University Bamberg, Bamberg, Germany.
authors.forename: Michael
authors.initials: M
authors.lastname: Siebers
authors.affiliation: Cognitive Systems Group, Faculty Information Systems and Applied Computer Science, Otto-Friedrich University Bamberg, Bamberg, Germany.
authors.forename: Ute
authors.initials: U
authors.lastname: Schmid
authors.affiliation: Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany.
authors.forename: Michael
authors.initials: M
authors.lastname: Schöberl
authors.affiliation: Physiological Psychology, Otto-Friedrich University Bamberg, Bamberg, Germany.
authors.forename: Stefan
authors.initials: S
authors.lastname: Lautenbacher
mesh_terms: D000368:Aged; D003704:Dementia / Q000150:complications*; D005149:Facial Expression; D006801:Humans; D010146:Pain / Q000150:complications / Q000175:diagnosis / Q000523:psychology; D059408:Pain Management / Q000379:methods; D010147:Pain Measurement / Q000379:methods*; D010348:Patient Care Team / Q000458:organization & administration; D058998:Remote Sensing Technology / Q000379:methods*
keywords: Automatic pain detection; Dementia; Facial expression; Pain diagnostics