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Approaches and principles of fall detection for elderly and patient
Abstract
Fall detection for elderly and patient has been an active research topic due to that the healthcare industry has a big demand for products and technology of fall detection. This paper gives a survey of fall detection for elderly and patient, focusing on identifying approaches and principles of the existing fall detection methods. To properly build the classification tree of the methods of fall detection we first study the characteristics of fall. Then according to what sensors and how sensors are used we first divide the methods of fall detection into three approaches: wearable device, ambience device, and camera-based. Further we divide each approach into two to three classes according to the used principles. For each class of algorithm we analyze their merits and demerits. We also give comments on how we can improve some algorithms.
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Mihailidis, A., Carmichael, B., & Boger, J. (2004) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2004.834386 · Cited by 208
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
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
Human fall detection on embedded platform using depth maps and wireless accelerometer
Kwolek, B., & Kepski, M. (2014) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2014.09.005 · Cited by 650
RT-Fall: A Real-Time and Contactless Fall Detection System with Commodity WiFi Devices
Wang, H., Zhang, D., Wang, Y., Ma, J., Wang, Y., & Li, S. (2017) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2016.2557795 · Cited by 640
Survey on Fall Detection and Fall Prevention Using Wearable and External Sensors
Delahoz, Y., & Labrador, M. (2014) · Sensors · doi:10.3390/s141019806 · Cited by 329
Metadata
- Authors
- Yu, X.
- Venue
- HealthCom 2008 - 10th International Conference on e-health Networking, Applications and Services
- Publisher
- IEEE
- Published
- 2008-07
- Pages
- 42-47
- OpenAlex
- W2072130063
- Cited by
- 328
- References
- 1
- FWCI
- 7.48
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Yu, X. (2008). Approaches and principles of fall detection for elderly and patient. HealthCom 2008 - 10th International Conference on e-health Networking, Applications and Services. https://doi.org/10.1109/health.2008.4600107
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
