Journal of Computing Science and Engineering

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Acoustic Monitoring and Localization for Social Care

  • Goetze, Stefan (Fraunhofer Institute for Digital Media Technology, Project group Hearing, Speech and Audio Technology) ;
  • Schroder, Jens (Fraunhofer Institute for Digital Media Technology, Project group Hearing, Speech and Audio Technology) ;
  • Gerlach, Stephan (Fraunhofer Institute for Digital Media Technology, Project group Hearing, Speech and Audio Technology) ;
  • Hollosi, Danilo (Fraunhofer Institute for Digital Media Technology, Project group Hearing, Speech and Audio Technology) ;
  • Appell, Jens-E. (Fraunhofer Institute for Digital Media Technology, Project group Hearing, Speech and Audio Technology) ;
  • Wallhoff, Frank (Fraunhofer Institute for Digital Media Technology, Project group Hearing, Speech and Audio Technology, and Jade-Hochschule)
  • Received : 2011.07.18
  • Accepted : 2012.02.06
  • Published : 2012.03.30
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Abstract

Increase in the number of older people due to demographic changes poses great challenges to the social healthcare systems both in the Western and as well as in the Eastern countries. Support for older people by formal care givers leads to enormous temporal and personal efforts. Therefore, one of the most important goals is to increase the efficiency and effectiveness of today's care. This can be achieved by the use of assistive technologies. These technologies are able to increase the safety of patients or to reduce the time needed for tasks that do not relate to direct interaction between the care giver and the patient. Motivated by this goal, this contribution focuses on applications of acoustic technologies to support users and care givers in ambient assisted living (AAL) scenarios. Acoustic sensors are small, unobtrusive and can be added to already existing care or living environments easily. The information gathered by the acoustic sensors can be analyzed to calculate the position of the user by localization and the context by detection and classification of acoustic events in the captured acoustic signal. By doing this, possibly dangerous situations like falls, screams or an increased amount of coughs can be detected and appropriate actions can be initialized by an intelligent autonomous system for the acoustic monitoring of older persons. The proposed system is able to reduce the false alarm rate compared to other existing and commercially available approaches that basically rely only on the acoustic level. This is due to the fact that it explicitly distinguishes between the various acoustic events and provides information on the type of emergency that has taken place. Furthermore, the position of the acoustic event can be determined as contextual information by the system that uses only the acoustic signal. By this, the position of the user is known even if she or he does not wear a localization device such as a radio-frequency identification (RFID) tag.

Keywords

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