PERVASIVEHEALTH 2010
AGEmap 2010PH-Home 2010PervaSense 2010UCD-PHA 2010

    PervaSense

    PervaSense WORKSHOP (PervasiveHealth) 2010

    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.

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    Editor(s): Heinz Gerhauser, Katie Siek, Joachim Hornegger and Tim Christian Lueth
    Publisher
    IEEE
    Conference dates
    22nd Mar 2010
    Location
    Munchen, Germany
    Appeared in EUDL
    7th Jun 2010
    Appears in
    IEEEXplore

    Copyright © 2010–2012 ICST

    • A long-term sensory logging device for subject monitoring

      Research Article in PervaSense WORKSHOP (PervasiveHealth) 2010

      Dawud Gordon, Florian Witt, Hedda Schmidtke, Michael Beigl

      Abstract
      In this paper we introduce a device for monitoring subjects by logging sensory data over long periods of time. The system consists of a sensory measurement unit, a memory unit and an application for …In this paper we introduce a device for monitoring subjects by logging sensory data over long periods of time. The system consists of a sensory measurement unit, a memory unit and an application for data preprocessing tasks, such as converting sensory measurements to desired units or calculating averages. In order to demonstrate usage, an activity level monitoring system inspired by medical applications is implemented using the device. A rudimentary threshold-based embedded classifier is trained using several different activities, yielding an activity level indicator. 2 subjects are monitored to train the classifier, and the system is then evaluated on new data using those two subjects plus a third not involved in the training process. The results indicate an activity classification of 74% into three levels using 2 simple data thresholds, with a system lifetime of 26 days on 2 AAA batteries.
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    • A sensor-enhanced health information system to support automatically controlled exercise training of COPD patients

      Research Article in PervaSense WORKSHOP (PervasiveHealth) 2010

      Axel Helmer, Bianying Song, Wolfram Ludwig, Mareike Schulze, Marco Eichelberg, Andreas Hein, Uwe Tegtbur, Riana Kayser, Reinhold Haux, Michael Marschollek

      Abstract
      For an improvement of the quality of life for patients suffering from chronic obstructive pulmonary disease (COPD) we developed a concept and prototype of a sensor-enhanced health information system.…For an improvement of the quality of life for patients suffering from chronic obstructive pulmonary disease (COPD) we developed a concept and prototype of a sensor-enhanced health information system. This system includes a component that is monitoring the rehabilitation training and automatically controls the target load for the exercise on the basis of his or her vital data. The system also detects potentially critical health states and communicates alarms to external users. The component interacts with a personal electronic health record (PHR) that provides additional health related information for the decision making process, as feedback to the user and as an opportunity for physicians to optimize the users exercise plan. The PHR uses current medical informatics standards to store and transmit training data to health care professionals and to provide a maximum of interoperability with their information systems. We have integrated these components in a service oriented platform design that is located in the home environment of the user.
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