The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Fall detection system using Kinect’s infrared sensor
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Citations
Cites
Fischler, M. A., & Bolles, R. C. (1981) · Communications of the ACM · doi:10.1145/358669.358692 · Cited by 25,893
Risk Factors for Falls in Community-dwelling Older People: A Systematic Review and Meta-analysis
Deandrea, S., Lucenteforte, E., Bravi, F., Foschi, R., La Vecchia, C., & Negri, E. (2010) · Epidemiology · doi:10.1097/ede.0b013e3181e89905 · Cited by 1,455
Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm
Bourke, A. K., O’Brien, J. V., & Lyons, G. M. (2007) · Gait & Posture · doi:10.1016/j.gaitpost.2006.09.012 · Cited by 821
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
University of North Carolina at Chapel Hill
(2015) · The SAGE Encyclopedia of Stem Cell Research · doi:10.4135/9781483347660.n469 · Cited by 502
A Smart and Passive Floor-Vibration Based Fall Detector for Elderly
Alwan, M., Rajendran, P. J., Kell, S., Mack, D., Dalal, S., Wolfe, M., & Felder, R. (2006) · 2006 2nd International Conference on Information & Communication Technologies · doi:10.1109/ictta.2006.1684511 · Cited by 402
A smart sensor to detect the falls of the elderly
Sixsmith, A., & Johnson, N. (2004) · IEEE Pervasive Computing · doi:10.1109/mprv.2004.1316817 · Cited by 399
Adaptive step size random search
Schumer, M., & Steiglitz, K. (1968) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1968.1098903 · Cited by 284
Auvinet, E., Multon, F., Saint-Arnaud, A., Rousseau, J., & Meunier, J. (2011) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2010.2087385 · Cited by 256
The prognosis of falls in elderly people living at home
Donald, I. (1999) · Age and Ageing · doi:10.1093/ageing/28.2.121 · Cited by 216
Cited by
Challenges, issues and trends in fall detection systems
Igual, R., Medrano, C., & Plaza, I. (2013) · BioMedical Engineering OnLine · doi:10.1186/1475-925x-12-66 · Cited by 654
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
Remote patient monitoring: a comprehensive study
Malasinghe, L. P., Ramzan, N., & Dahal, K. (2019) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-017-0598-x · Cited by 534
Systematic review of Kinect applications in elderly care and stroke rehabilitation
Webster, D., & Celik, O. (2014) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-11-108 · Cited by 436
UP-Fall Detection Dataset: A Multimodal Approach
Martínez-Villaseñor, L., Ponce, H., Brieva, J., Moya-Albor, E., Núñez-Martínez, J., & Peñafort-Asturiano, C. (2019) · Sensors · doi:10.3390/s19091988 · Cited by 403
Metadata
- Authors
- Mastorakis, G., & Makris, D.
- Venue
- Journal of Real-Time Image Processing
- Published
- 2012-03-15
- Volume
- 9
- Issue
- 4
- Pages
- 635-646
- ISSN
- 1861-8200 (ISSN-L)
- 1861-8219
- OpenAlex
- W2059584741
- Cited by
- 356
- References
- 24
- FWCI
- 26.88
- Type
- journal article
- Language
- en
- Open access
- closed
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- Mastorakis, G., & Makris, D. (2014). Fall detection system using Kinect’s infrared sensor. Journal of Real-Time Image Processing. https://doi.org/10.1007/s11554-012-0246-9
Data sources
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.
