Technically representing clinical knowledge for rehabilitation care

Kai Gand (Vortragende:r), Lars Böcking, Karl Kreiner, Hannes Schlieter, Martin Burwitz, Carola Gißke, Patrick Philipp, Johannes Kropf

Publikation: Beitrag in Buch oder TagungsbandVortrag mit Beitrag in TagungsbandBegutachtung


Providing a suitable rehabilitation after an acute episode or a chronic disease helps people to live independently and enhance their quality of life. However, the continuity of care is often interrupted in the transition from hospital to home. Virtual coaches (VCs) could help these patients to engage in personalized home rehabilitation programs. These coaching systems need also to be fed with procedural precepts in order to work as intended. This, in turn, relates both to properly represent the clinical knowledge (as the VC somehow replaces the formal caregivers that cannot be fully present) as well guide the patient correctly (in order to follow the medically desired procedures given the need for personalisation according to individual needs). Therefore, we outline our technical approach to deal with this. In particular, clinical pathways in terms of semi-formal procedure models in combination with machine learning components processing and powerful user interfaces providing these pathway information and feeding the VC are presented. The system is currently under testing in a participatory design phase called Living Lab. Thus, initial user feedback for further improvements is about to come.
TitelPublic Health and Informatics
Herausgeber (Verlag)IOS Press
ISBN (Print)978-1-64368-185-6
PublikationsstatusVeröffentlicht - 2021
Veranstaltung31st Medical Informatics Europe Conference (#MIE2021) -
Dauer: 29 Mai 202131 Mai 2021


Konferenz31st Medical Informatics Europe Conference (#MIE2021)

Research Field

  • Exploration of Digital Health


  • Clinical pathways; Machine learning; Virtual Coaching


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