The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
A Method for Automatic Fall Detection of Elderly People Using Floor Vibrations and Sound—Proof of Concept on Human Mimicking Doll Falls
Abstract
Falls are a major risk for the elderly people living independently. Rapid detection of fall events can reduce the rate of mortality and raise the chances to survive the event and return to independent living. In the last two decades, several technological solutions for detection of falls were published, but most of them suffer from critical limitations. In this paper, we present a proof of concept to an automatic fall detection system for elderly people. The system is based on floor vibration and sound sensing, and uses signal processing and pattern recognition algorithm to discriminate between fall events and other events. The classification is based on special features like shock response spectrum and mel frequency ceptral coefficients. For the simulation of human falls, we have used a human mimicking doll: "Rescue Randy." The proposed solution is unique, reliable, and does not require the person to wear anything. It is designed to detect fall events in critical cases in which the person is unconscious or in a stress condition. From the preliminary research, the proposed system can detect human mimicking dolls falls with a sensitivity of 97.5% and specificity of 98.6%.
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Cited by
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
Evaluation of Accelerometer-Based Fall Detection Algorithms on Real-World Falls
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Research of Fall Detection and Fall Prevention Technologies: A Systematic Review
Ren, L., & Peng, Y. (2019) · IEEE Access · doi:10.1109/access.2019.2922708 · Cited by 266
Fall Detection Devices and Their Use With Older Adults: A Systematic Review
Chaudhuri, S., Thompson, H., & Demiris, G. (2014) · Journal of Geriatric Physical Therapy · doi:10.1519/jpt.0b013e3182abe779 · Cited by 215
Homecare robotic systems for healthcare 4.0: visions and enabling technologies
Yang, G., Pang, Z., Jamal Deen, M., Dong, M., Zhang, Y.-T., Lovell, N., & Rahmani, A. M. (2020) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2020.2990529 · Cited by 213
Metadata
- Authors
- Zigel, Y., Litvak, D., & Gannot*, I.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2009-12
- Volume
- 56
- Issue
- 12
- Pages
- 2858-2867
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W2169138660
- Cited by
- 375
- References
- 25
- FWCI
- 13.93
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zigel, Y., Litvak, D., & Gannot*, I. (2009). A Method for Automatic Fall Detection of Elderly People Using Floor Vibrations and Sound—Proof of Concept on Human Mimicking Doll Falls. IEEE Transactions on Biomedical Engineering. https://doi.org/10.1109/tbme.2009.2030171
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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