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A Smart and Passive Floor-Vibration Based Fall Detector for Elderly
Abstract
Falls are very prevalent among the elderly. They are the second leading cause of unintentional-injury death for people of all ages and the leading cause of death for elders 79 years and older. Studies have shown that the medical outcome of a fall is largely dependent upon the response and rescue time. Hence, a highly accurate automatic fall detector is an important component of the living setting for older adult to expedite and improve the medical care provided to this population. Though there are several kinds of fall detectors currently available, they suffer from various drawbacks. Some of them are intrusive while others require the user to wear and activate the devices, and hence may fail in the event of user non-compliance. This paper describes the working principle and the design of a floor vibration-based fall detector that is completely passive and unobtrusive to the resident. The detector was designed to overcome some of the common drawbacks of the earlier fall detectors. The performance of the detector is evaluated by conducting controlled laboratory tests using anthropomorphic dummies. The results showed 100% fall detection rate with minimum potential for false alarms
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Cited by
A survey on ambient-assisted living tools for older adults
Rashidi, P., & Mihailidis, A. (2013) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2012.2234129 · Cited by 1,128
WiFall: Device-Free Fall Detection by Wireless Networks
Wang, Y., Wu, K., & Ni, L. M. (2017) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2016.2557792 · Cited by 836
Robust Video Surveillance for Fall Detection Based on Human Shape Deformation
Rougier, C., Meunier, J., St-Arnaud, A., & Rousseau, J. (2011) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2011.2129370 · Cited by 490
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
Successful aging: Advancing the science of physical independence in older adults
Anton, S. D., Woods, A. J., Ashizawa, T., Barb, D., Buford, T. W., Carter, C. S., Clark, D. J., Cohen, R. A., Corbett, D. B., Cruz-Almeida, Y., et al. (2015) · Ageing Research Reviews · doi:10.1016/j.arr.2015.09.005 · Cited by 292
Metadata
- Authors
- Alwan, M., Rajendran, P. J., Kell, S., Mack, D., Dalal, S., Wolfe, M., & Felder, R.
- Venue
- 2006 2nd International Conference on Information & Communication Technologies
- Publisher
- IEEE
- Published
- 2006-10-24
- Volume
- 1
- Pages
- 1003-1007
- OpenAlex
- W1566752807
- Cited by
- 402
- References
- 0
- FWCI
- 7.35
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A Smart and Passive Floor-Vibration Based Fall Detector for Elderly. https://app.cochat.ai/papers/10.1109/ictta.2006.1684511
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- Alwan, M., Rajendran, P. J., Kell, S., Mack, D., Dalal, S., Wolfe, M., & Felder, R. (2006). A Smart and Passive Floor-Vibration Based Fall Detector for Elderly. 2006 2nd International Conference on Information & Communication Technologies. https://doi.org/10.1109/ictta.2006.1684511
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
