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UID:146-409@gi.de
CLASS: PUBLIC
SUMMARY:5th international Workshop on Sensor-based Activity Recognition and
  Interaction
DESCRIPTION:Wearable sensors potentially enable for a better and unobtrusiv
 e recognition of human activity and the state of rest, sleep, stress and dr
 ive the ongoing trend of the quantified self-movement. As an enabling techn
 ology, powerful, while yet inexpensive MEMS-Chips (micro-electro-mechanical
  system) push the penetration of a broad variety of mobile devices. Thereby
 , these devices gain high interest, not only in terms of general customer p
 roducts, but also as integrated systems in an industrial context, either wa
 y to enable continuous monitoring of complex life processes and workplace s
 ituations.\n\nAnother challenge that research is facing concerns the limite
 d human abilities of interaction in context of mobility and in situations, 
 in which high attention is being demanded. New and alternative ways are nee
 ded to be found in order to take advantage of all human capabilities to ena
 ble safe and unobtrusive interaction.\n\nThis conference-like workshop is i
 nitiated and organized by the Fraunhofer IGD and the University of Rostock.
  It offers scientists, interested parties, and users in the area of sensor-
 based activity recognition and interaction the possibility to an exchange o
 f experiences and a presentation of best-practice examples, as well as tech
 nical and scientific results. The workshop focuses on technologies for huma
 n activity recognition and interaction via inertial sensors (accelerometers
 , gyroscopes etc.) and their scientific applications.\n\nThereby, the follo
 wing topics and fields of application will be addressed:\n\n\n\nTopics:\n\n
 \n\n- Human Activity Recognition\n\n- Human Performance Measuring\n\n- Huma
 n Monitoring\n\n- Wearable Sensing in Healthcare Informatics Wearable Compu
 ting\n\n- Interaction Techniques\n\n- Intelligent User Interfaces\n\n- Inpu
 t & Output modalities\n\n- Context Awareness\n\n- Machine Learning\n\n- Art
 ificial Intelligence\n\n- Deep Learning\n\n- Feature Extraction\n\n- Data C
 lassification\n\n- Data Imputation\n\n- Signal Reconstruction and Interpola
 tion\n\n\n\nApplication Fields:\n\n\n\n- Ambient Assisted Living\n\n-Techno
 logies for Senior Living\n\n- Quantified Self\n\n- Lifestyle & Behavior Cha
 nge\n\n- Pervasive Healthcare\n\n- Occupational Health, Health Care and Wel
 lness\n\n- Telemedicine and Biotechnology\n\n- Assisted Production\n\n- Mai
 ntenance and Service\n\n- Alternative Control of Everyday Life's Products\n
 \n- Assistive Technologies for Urban Environments\n\n\n\niWOAR 2018 aims to
  foster the relationship between academia and industry. We strongly encoura
 ge industry participants to present challenges, ideas, experiences, novel a
 pplications, and studies of existing methods. Accepted industrial papers wi
 ll be presented in an industrial session during the workshop.
LOCATION:Fraunhofer Forum
DTSTAMP:20180215T081235Z
DTSTART:20180920T070000Z
DTEND:20180921T160000Z
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