Authors : Annette Theresa Mathew; Taniya Shirley Stalin; Krishna Sudheer Kumar; Abhinav Santhosh; Ashwin Juby

Volume/Issue : Volume 9 - 2024, Issue 4 - April

Google Scholar : https://tinyurl.com/2p5z77f4

Scribd : https://tinyurl.com/ecekdt59

DOI : https://doi.org/10.38124/ijisrt/IJISRT24APR2666

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The elderly population represents a significant and rapidly expanding demographic, with a majority experiencing frequent daily accidents, notably falls. Falls rank as the second leading cause of accidental injury deaths globally. To address this issue, we propose a video classification system designed specifically for fall detection. Our fall detection framework comprises two key steps: firstly, the detection of human posture within video frames, followed by fall classification using Convolutional Neural Networks (CNNs). Additionally, we introduce a novel approach for boundary detection, utilizing object detection techniques beyond a predefined line of surveillance captured by a single camera. Through this integrated methodology, we aim to enhance fall detection and boundary breach detection capabilities, thereby contributing to the advancement of elderly care and safety. (Abstract).

Keywords : CNN; Fall Detection; Boundary Detection; Video Classification; Background Subtraction; Elders.

References :

1. Vaishya R, Vaish A. Falls in Older Adults are Serious. Indian J Orthop. 2020 Jan 24;54(1):69-74. doi: 10.1007/s43465-019-00037-x. PMID: 32257019; PMCID: PMC7093636.J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, 1892, pp.68–73.
2. Kellogg International Work Group on the Prevention of Falls by the Elderly. The prevention of falls in later life. Danish Medical Bulletin 1987; 34(4):1-24.
3. Institute of Medicine (US) Division of Health Promotion and Disease Prevention; Berg RL, Cassells JS, editors. The Second Fifty Years: Promoting Health and Preventing Disability. Washington (DC): National Academies Press (US); 1992. 15, Falls in Older Persons: Risk Factors and Prevention.
4. Fife, D., Barancik, J. I., and Chatterjee, M. S. Northeastern Ohio trauma study. II. Injury rates by age, sex and cause. American Journal of Public Health 1984; 74(5):473-478. 
5. Price JD, Hermans DG, Grimley Evans J. Subjective barriers to prevent wandering of cognitively impaired people. Cochrane Database Syst Rev. 2000;2001(4):CD001932. doi: 10.1002/14651858.CD001932. PMID: 11034735; PMCID: PMC8406984. K. Elissa, “Title of paper if known,” unpublished.
6. Kumar CTS, Shaji KS, and Varghese MNM (Eds.). Dementia in India, 2020, Cochin Chapter. Published online 2020. 1–96. Y. Yorozu, M. Hirano, K. Oka, and Y. Tagawa, “Electron spectroscopy studies on magneto-optical media and plastic substrate interface,” IEEE Transl. J. Magn. Japan, vol. 2, pp. 740–741, August 1987 [Digests 9th Annual Conf. Magnetics Japan, p. 301, 1982].
7. Hope T, Tilling KM, Gedling K, et al. The structure of wandering in dementia. Int J Geriatr Psychiatry, 1994; 9 149–155.
8. Garg, Shubham & Saxena, Aman & Gupta, Richa. (2022). Yoga pose classification: a CNN and MediaPipe inspired deep learning approach for real-world application. Journal of Ambient Intelligence and Humanized Computing. 14. 10.1007/s12652-022-03910-0.
9. Subramaniam S, Faisal AI and Deen MJ (2022) Wearable Sensor Systems for Fall Risk Assessment: A Review. Front. Digit. Health 4:921506. doi: 10.3389/fdgth.2022.921506
10. Karar ME, Shehata HI, Reyad O. A Survey of IoT-based fall detection for aiding elderly care: sensors, methods, challenges and future trends. Appl Sci. (2022) 12:3276. doi: 10.3390/app12073276.
11. R. Hasib, K. N. Khan, M. Yu and M. S. Khan, "Vision-based Human Posture Classification and Fall Detection using Convolutional Neural Network," 2021 International Conference on Artificial Intelligence (ICAI), Islamabad, Pakistan, 2021, pp. 74-79, doi: 10.1109/ICAI52203.2021.9445263
12. S. Mobsite, N. Alaoui and M. Boulmalf, "A framework for elders fall detection using deep learning," 2020 6th IEEE Congress on Information Science and Technology (CiSt), Agadir - Essaouira, Morocco, 2020, pp. 69-74, doi: 10.1109/CiSt49399.2021.9357184
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