Pervasive systems in healthcare have reached a high degree of maturity from a technical point of view. However, the interpretation of large amounts of medical sensor data with regard to a person's individual situation still remains a great challenge to the research community. Advanced medical data …
Pervasive systems in healthcare have reached a high degree of maturity from a technical point of view. However, the interpretation of large amounts of medical sensor data with regard to a person's individual situation still remains a great challenge to the research community. Advanced medical data analysis is one important prerequisite for providing individualized health services in Pervasive Health or Ambient Assisted Living environments. Situation recognition, in turn, is a key factor for individualization and adaptivity. The aim of this workshop is to present top research in the areas of situation recognition (e.g. detection of falls, Activities of Daily Living (ADL, iADL), context-aware situation recognition), medical data analysis (vital signs data analysis, short- and long-term deviations in the state of health, decision support), and behavior monitoring (trend analysis for the detection of long-term deviations in persons behavior for detecting age-related diseases like dementia or Alzheimer's) in Pervasive Health or Ambient Assisted Living environments. This workshop touches both technological aspects such as data fusion in pervasive healthcare environments and decision support algorithms, as well as social implications and acceptance of these technologies. Furthermore, real-life applications of situation recognition in home monitoring and clinical environments, e.g., for individualized feedback systems, are covered.
