The DOI matches its Crossref record; 111 of the 111 references it cites were found in a registry or an index.
Research of Fall Detection and Fall Prevention Technologies: A Systematic Review
Open accessAbstract
Falls are abnormal activity events that occur infrequently; however, they are serious health problems among elderly individuals. With the advancements of technologies, falls have been widely studied by scientific researchers to minimize serious consequences and negative impacts. Fall detection and fall prevention are two strategies to tackle fall issues with a variety of sensing techniques and classifier models. Currently, many reviews on fall-related technologies have been presented and analyzed; however, most of them give surveys on the subfield of fall-related systems, while others are not extensive and comprehensive reviews. In fact, the latest researches have a new trend of fusion-based methods to improve the performance of the fall-related systems based on a combination of different sensors or classifier models. Adaptive threshold and radio frequency-based systems are also researched and proposed recently, which are seldom mentioned in other reviews. Therefore, a global taxonomy for current fall-related studies from four aspects, including current literature reviews, fall detection, and prevention systems based on different sensor apparatus and analytic algorithm, low power techniques, and sensor placements for fall-related systems are conducted in this paper. Several research challenges and issues in the fall-related field are also discussed and analyzed. The objective of this review paper is to conclude and provide a good position of current fall-related studies to inspire researchers in this field.
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Cites
Relatives of the Impaired Elderly: Correlates of Feelings of Burden
Zarit, S. H., Reever, K. E., & Bach-Peterson, J. (1980) · The Gerontologist · doi:10.1093/geront/20.6.649 · Cited by 5,810
Quantitative Gait Markers and Incident Fall Risk in Older Adults
Verghese, J., Holtzer, R., Lipton, R. B., & Wang, C. (2009) · The Journals of Gerontology Series A: Biological Sciences and Medical Sciences · doi:10.1093/gerona/glp033 · Cited by 948
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
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
Accurate, Fast Fall Detection Using Gyroscopes and Accelerometer-Derived Posture Information
Li, Q., Stankovic, J. A., Hanson, M. A., Barth, A. T., Lach, J., & Zhou, G. (2009) · 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks · doi:10.1109/bsn.2009.46 · Cited by 584
A threshold-based fall-detection algorithm using a bi-axial gyroscope sensor
Bourke, A. K., & Lyons, G. M. (2008) · Medical Engineering & Physics · doi:10.1016/j.medengphy.2006.12.001 · Cited by 509
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
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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
- Ren, L., & Peng, Y.
- Venue
- IEEE Access
- Published
- 2019
- Volume
- 7
- Pages
- 77702-77722
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2950883524
- Cited by
- 266
- References
- 111
- FWCI
- 5.04
- Type
- journal article
- Language
- en
- Open access
- gold
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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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