1 |
E. Casilari, S. A. Jose, and M. C. Jose, UMAFall: A Multisensor dataset for the research on automatic fall detection, Procedia. Comput. Sci. 110 (2017), 32-39.
DOI
|
2 |
G. Kowshik, J. Anudeep, P. V. Krishna, S. K. Vasudevan, and I. Shah, An inventive and innovative system to detect fall of old aged persons - a novel attempt with IoT, sensors and data analytics to prevent the post fall effects, Intern. J. Med. Eng. Inf. 12 (2020), no. 1, 1-18.
DOI
|
3 |
C. Buse and T. Julia, Materialising memories: Exploring the stories of people with dementia through dress, Ageing Soc. 36 (2016), no. 6, 1115-1135.
DOI
|
4 |
N. A. Neubauer and L. Liu, The significance of losing things: Evaluation of antecedent behaviors of dementia-related wandering in community and facility settings, June 17, 2020. Available from: https://www.futuremedicine.com/doi/full/10.2217/nmt-2019-0030 [last accessed May 2021].
|
5 |
D. Anguita, A. Ghio, L. Oneto, X. Parra, and J. L. Reyes-Ortiz, Human activity recognition on smartphones using a multiclass hardware-friendly support vector machine, Intern. workshop on ambient assisted living, Berlin, Heidelberg, 2012.
|
6 |
F. Karim, S. Majumdar, H. Darabi, and S. Harford, Multivariate LSTM-FCNs for time series classification, Neural Netw. 116 (2019), 237-245.
DOI
|
7 |
R. T. Janice, Slip, trip, stumble, fall: An overview of falls in the elderly and how to prevent them, Aug. 2018, Available from: https://lermagazine.com/cover_story/slip-trip-stumble-fall-an-overview-of-falls-in-the-elderly-and-how-to-prevent-them [last accessed May 2021].
|
8 |
F. M. da Silva, M. da Silva Reis, M. H. de Matos, D. N. Barbosa, D. R. Soares, E. T. de Aquino Oliveira, A. M. dos Santos, and J. A. Rodrigues, Golden time: Analysis of the response time of the Mobile Urgency Care Service (Samu), Revista de Epidemiologia e Controle de Infeccao 10 (2020), no. 3, 270-275.
|
9 |
Y. Yang, V. Komisar, N. Shishov, B. Lo, A. M. B. Korall, F. Feldman, and S. N. Robinovitch, The effect of fall biomechanics on risk for hip fracture in older adults: A cohort study of video-captured falls in long-term care, J. Bone Miner. Res. 35 (2020), 1914-1922.
DOI
|
10 |
C. H. Orces and H. Alamgir, Trends in Fall-related injuries Among Older Adults Treated in Emergency Departments in the USA, Inj. Prev. 20 (2014), 421-423.
DOI
|
11 |
World Health Organization (WHO), WHO global report on falls prevention in older age, WHO, Geneva, Switzerland, 2018 Available from: https://extranet.who.int/agefriendlyworld/wp-content/uploads/2014/06/WHO-Global-report-on-falls-prevention-inolder-age.pdf [last accessed May 2021].
|
12 |
Centers for Disease Control and Prevention (CDC), WISQARS™, Web-based injury statistics query and reporting system, Available from: http://www.cdc.gov/injury/wisqars [last accessed July 2020].
|
13 |
Consumer Injury Surveillance System (CISS), Analysis of risk cases for falling accident in older adults, Oct. 2016, Available from: https://www.kca.go.kr/smartconsumer/board/download.do?menukey=7301&fno=10014532&bid=00000146&did=1001991589 [in Korean], [last accessed May 2021].
|
14 |
M. D. Neuman, J. H. Silber, J. S. Magaziner, M. A. Passarella, S. Mehta, and R. M. Werner, Survival and functional outcomes after hip fracture among nursing home residents, JAMA Intern. Med. 174 (2014), 1273-1280.
DOI
|
15 |
Y. Kim, S. M. Baek, and B. C. Bae, Motion capture of the human body using multiple depth sensors, ETRI J. 39 (2017), no. 2, 181-190.
DOI
|
16 |
E. Casilari, R. Luque, and M. J. Moron, Analysis of android device-based solutions for fall detection, Sensors 15 (2015), no. 2, 17827-17894.
DOI
|
17 |
D. Micucci, M. Marco, and N. Paolo, UniMiB SHAR: A dataset for human activity recognition using acceleration data from smartphones, Appl. Sci. 7 (2017), no. 10. https://doi.org/10.3390/app7101101
DOI
|
18 |
S. N. Robinovitch, F. Feldman, Y. Yang, R. Schonnop, P. M. Leung, T. Sarraf, J. Sims-Gould, and M. Loughin, Video capture of the circumstances of falls in elderly people residing in long-term care: An observational study, Lancet 381 (2013), no. 9860, 37-54.
|
19 |
A. D. Ahlam, S. Rubita, and H. M. Nasrul, Transfer Deep Learning Along with Binary Support Vector Machine for Abnormal Behavior Detection, IEEE Access 8 (2020), 61085-61095.
DOI
|
20 |
Z. Xia, P. Li, K. Xiao, X. Meng, L. Han, and C. Yu, Sensor drift compensation based on the improved LSTM and SVM multi-class ensemble learning models, Sensors 19 (2019), no. 18. https://doi.org/10.3390/s19183844
DOI
|
21 |
S. Rajesh and A. Sungheetha, An efficient dimension reduction based fusion of CNN and SVM model for detection of abnormal incident in video surveillance, J. Soft Comp. Paradigm 3 (2021), no. 2, 55-69.
DOI
|
22 |
S. A. Taghanaki, M. R. Ansari, B. Z. Dehkordi, and S. A. Mousavi, Nonlinear feature transformation and genetic feature selection: improving system security and decreasing computational cost, ETRI J. 34 (2012), no. 6, 847-857.
DOI
|
23 |
L. Hazelhoff and H. Jungong, Video-based fall detection in the home using principal component analysis, (ACIVS 2008: Advanced Concepts for Intelligent Vision Systems, Juan-Les-Pins, France), Oct. 2008, pp. 298-309.
|
24 |
A. Sucerquia, D. L. Jose, and F. V. Jesus Francisco, SisFall: A fall and movement dataset, Sensors 17 (2017), no. 1, 198.
DOI
|
25 |
O. Aziz, M. Musngi, E. J. Park, G. Mori, and S. N. Robinovitch, A comparison of accuracy of fall detection algorithms (threshold-based vs. machine learning) using waist-mounted tri-axial accelerometer signals from a comprehensive set of falls and nonfall trials, Med. Biol. Eng. Comput. 55 (2017), no. 1, 45-55.
DOI
|
26 |
F. Gottwalt, C. Elizabeth, and D. Tharam, CorrCorr: A feature selection method for multivariate correlation network anomaly detection techniques, Comput. Secur. 83 (2019), 234-245.
DOI
|
27 |
D. H. Mazumder and R. Veilumuthu, An enhanced feature selection filter for classification of microarray cancer data, ETRI J. 41 (2019), no. 3, 358-370.
DOI
|
28 |
J. Oxley, S. O'Hern, D. Burtt, and B. Rossiter, Fall-related injuries while walking in victoria, Feb. 2016, Available from: https://www.victoriawalks.org.au/Assets/Files/Fall-Related-Injuries-While-Walking-Report.pdf [last accessed May 2021].
|
29 |
A. B. Peterson and R. K. Scott, Deaths from fall-related traumatic brain injury-United States, 2008-2017, MMWR Morb. Mortal. Wkly Rep. 69 (2020), no. 9, 225-230.
|
30 |
A. Stinchcombe, N. Kuran, and S. Powell, Seniors' Falls in Canada: Second report: Key highlights, Chronic Dis. Inj. Canada 34 (2014), no. 2-3, 171-174.
DOI
|
31 |
K. M. DeGoede, J. A. Ashton-Miller, and A. B. Schultz, Fall-related upper body injuries in the older adult: A review of the biomechanical issues, J. Biomech. 36 (2003), no. 7, 1043-1053.
DOI
|