Demo Abstract: Multi-modal Fall Detection within the WeCare Framework

Date

2010-01-01

Author

Alemdar, Hande
Ozen, Mustafa Ozan
Kara, Yunus Emre
Incel, Ozlem Durmaz
Akarun, Lale
Ersoy, Cem

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Falls are identified as a major health risk for the elderly and a major obstacle to independent living. Considering the remarkable increase in the elderly population of developed countries, methods for fall detection have been a recent active area of research. However, existing methods often use only wearable sensors, such as acceloremeters, or cameras to detect falls. In this demonstration, in contrast to the state of the art solutions, we focus on the use of multi-modal wireless sensor networks within the WeCare framework. WeCare system is developed as a solution for independent living applications by remotely monitoring the health and well-being of its users. We describe the general structure of WeCare and demonstrate its fall detection method. Our set-up not only includes scalar sensors to detect falls and motion but also consists of embedded cameras and RFID tags and uses sensor fusion techniques to improve the success of fall detection and minimize the false positives.

Subject Keywords

Instruments, Independent living, WeCare framework, WeCare system

URI

https://hdl.handle.net/11511/38699

DOI

https://doi.org/10.1145/1791212.1791293

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

H. Alemdar, M. O. Ozen, Y. E. Kara, O. D. Incel, L. Akarun, and C. Ersoy, “Demo Abstract: Multi-modal Fall Detection within the WeCare Framework,” 2010, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/38699.