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Research Article
Intelligent Fall Detection for Elders
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.
Published Online: May-June 2024
Pages: 80-82
Cite this article
↗ https://www.doi.org/10.59256/ijire.20240503009References
[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.
[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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