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Wearable Sensors for Reliable Fall Detection
Abstract
Unintentional falls are a common cause of severe injury in the elderly population. By introducing small, non-invasive sensor motes in conjunction with a wireless network, the Ivy Project aims to provide a path towards more independent living for the elderly. Using a small device worn on the waist and a network of fixed motes in the home environment, we can detect the occurrence of a fall and the location of the victim. Low-cost and low-power MEMS accelerometers are used to detect the fall while RF signal strength is used to locate the person.
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Cited by
A tutorial on human activity recognition using body-worn inertial sensors
Bulling, A., Blanke, U., & Schiele, B. (2014) · ACM Computing Surveys · doi:10.1145/2499621 · Cited by 1,668
A survey on fall detection: Principles and approaches
Mubashir, M., Shao, L., & Seed, L. (2013) · Neurocomputing · doi:10.1016/j.neucom.2011.09.037 · Cited by 869
Preprocessing techniques for context recognition from accelerometer data
Figo, D., Diniz, P. C., Ferreira, D. R., & Cardoso, J. M. P. (2010) · Personal and Ubiquitous Computing · doi:10.1007/s00779-010-0293-9 · Cited by 578
UniMiB SHAR: A Dataset for Human Activity Recognition Using Acceleration Data from Smartphones
Micucci, D., Mobilio, M., & Napoletano, P. (2017) · Applied Sciences · doi:10.3390/app7101101 · Cited by 596
Evaluation of Accelerometer-Based Fall Detection Algorithms on Real-World Falls
Bagalà, F., Becker, C., Cappello, A., Chiari, L., Aminian, K., Hausdorff, J. M., Zijlstra, W., & Klenk, J. (2012) · PLoS ONE · doi:10.1371/journal.pone.0037062 · Cited by 464
Metadata
- Authors
- Chen, J., Kwong, K., Chang, D., Luk, J., & Bajcsy, R.
- Venue
- 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference
- Publisher
- IEEE
- Published
- 2005
- Volume
- 2005
- Pages
- 3551-3554
- OpenAlex
- W2104706302
- Cited by
- 443
- References
- 0
- FWCI
- 4.95
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Chen, J., Kwong, K., Chang, D., Luk, J., & Bajcsy, R. (2005). Wearable Sensors for Reliable Fall Detection. 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. https://doi.org/10.1109/iembs.2005.1617246
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