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Research Article

Intelligent Fall Detection for Elders

Open Access Peer Reviewed Crossref DOI

Authors

  • Vijith P R1
  • Aromal K R2
  • Aswin T M3
  • Nihal Navas K M4

1Assistant Professor, Department of Electronics and Communication Engineering, Universal Engineering College, Vallivattom, Thrissur, Kerala, India. 234Department of Electronics and Communication Engineering, Universal Engineering College Vallivattom, Thrissur, Kerala, India.

Article Information

Published Online
May-June 2024
Pages
80-82
Article Type
Research Article
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References

[1]. WHO-website: https://www.who.int/news-room/fact-sheets/detail/falls
[2]. R. Heilym Ramirez, Sergio A. Velastin, Ignacio Meza, Ernesto Fabregas, Dimitrios Makris and Gonzalo Farias,“Fall detection and
activity recognition using human skeleton features”0.1109/ACCESS.2021.306162 March 3,2021Bener A, Zirie M, Janahi IM, AlHamaq AOAA, Musallam M, Wareham NJ.Prevalence of diagnosed and undiagnosed diabetes mellitus and its risk factorsin a
population-based study of Qatar. Diabetes Research and Clinical Practice. 2009;84(1):99–106.
[3]. Chalavadi Vishnu, Rajeshreddy Datla, Debaditya Roy, Shobhan Babu and C Krishna Mohan,“Human fall detection in surveillance
videos using fall motion vector modelling”.DOI 10.1109/JSEN.2021.3082180, IEEE Sensor, Oct,2021
[4]. Rabia Hasib, Kaleem Nawaz Khan, Miao Yu and Muhammad Salam Khan,“Vison-based human posture classification and fall
detection using convolutional neural networks”.2021 International Conference on Artificial Intelligence (ICAI) — 978-1-6654-
3293-1/202021 IEEE, Apr 5,2021
[5]. Ayush Chandak, Nitin Chaturvedi and Dhiraj, “Machine-learningbased human fall detection using contact and non-contact based
sensors”.Volume 2022, Article ID 9626170.
[6]. A. Murad and J.-Y. Pyun, “Deep recurrent neural networks for human activity recognition,” Sensors, vol. 17, no. 11, p. 2556, Nov.
2017.
[7]. Jia-Wei Lin, Ming-Hung Lu andYuan-Hsiang Lin,“A thermal camera based continuous body temperature measurement system”.
Feb 10,2021
[8]. B. S. Daga, A. A. Ghatol, and V. M. Thakare, “Silhouette based human fall detection using multimodal classif i ers for content based
video retrieval systems,” in Proc. Int. Conf. Intell. Comput., Instrum. Control Technol.(ICICICT), Jul. 2017, pp. 1409–1416.
[9]. P. Bet, P. C. Castro, and M. A. Ponti, “Fall detection and fall risk assessment in older person using wearable sensors: A systematic
review,” Int.J. Med. Informat., vol. 130, Oct. 2019, Art. no. 103946.
[10]. S. C. Agrawal, R. K. Tripathi, and A. S. Jalal, “Human-fall detection from an indoor video surveillance,” in Proc. 8th Int. Conf.
Comput., Commun.Netw. Technol. (ICCCNT), Jul. 2017, pp. 1–5.
[11]. J. Wang, Y. Chen, S. Hao, X. Peng, and L. Hu, “Deep learning for sensorbased activity recognition: A survey,” Pattern Recognit.
Lett., vol. 119,pp. 3–11, Mar. 2019.
[12]. S. Yu, H. Chen, and R. A. Brown, “Hidden markov model-based fall detection with motion sensor orientation calibration: A case
for real-life home monitoring,” IEEE Journal of Biomedical and Health Informatics,vol. 22, no. 6, pp. 1847–1853, 2018.
[13]. Z. Liu, M. Yang, Y. Yuan, and K. Y. Chan, “Fall detection and personnel tracking system using infrared array sensors,” IEEE
Sensors Journal, vol. 20, no. 16, pp. 9558–9566, 2020.
[14]. N. Lu, Y. Wu, L. Feng, and J. Song, “Deep learning for fall detection: Three-dimensional CNN combined with LSTM on video
kinematic data,” IEEE Journal of Biomedical and Health Informatics, vol. 23, no.1, pp. 314–323, 2019.
[15]. J. Maitre, K. Bouchard, and S. Gaboury, “Fall detection with UWB radars and CNN-LSTM architecture,” IEEE Journal of
Biomedical and Health Informatics, pp. 1–1, 2020.
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