Open Access
E3S Web of Conf.
Volume 507, 2024
International Conference on Futuristic Trends in Engineering, Science & Technology (ICFTEST-2024)
Article Number 01025
Number of page(s) 11
Published online 29 March 2024
  1. Abou, L., Fliflet, A., Hawari, L., Presti, P., Sosnoff, J. J., Mahajan, H. P., Frechette, M. L., & Rice, L. A. (2022). The sensitivity of the fall detection feature on the Apple Watch among individuals who use wheelchairs. Assistive technology: the official journal of RESNA, 34(5), 619–625. [Google Scholar]
  2. Abou, L., Fliflet, A., Presti, P., Sosnoff, J. J., Mahajan, H. P., Frechette, M. L., & Rice, L. A. (2023). Fall detection from a manual wheelchair. Assistive technology: the official journal of RESNA, 35(6), 523–531. [Google Scholar]
  3. Sadi, M. S., Alotaibi, M., Islam, M. R., Islam, M. S., Alhmiedat, T., & Bassfar, Z. (2022). Finger-Gesture Controlled Wheelchair with Enabling IoT. Sensors (Basel, Switzerland), 22(22), 8716. [Google Scholar]
  4. B. -S. Lin et al., “Fall Detection System With Artificial Intelligence-Based Edge Computing,” in IEEE Access, vol. 10, pp. 4328–4339, 2022, doi: 10.1109/ACCESS.2021.3140164. [Google Scholar]
  5. Sofia Yousuf Sheikh, Muhammad Taha Jilani, A ubiquitous wheelchair fall detection system using low-cost embedded inertial sensors and unsupervised one-class SVM, Journal of Ambient Intelligence and Humanized Computing, No. 1, p. 147-162, 2021 [Google Scholar]
  6. Mastorakis, G., Makris, D. Fall detection system using Kinect’s infrared sensor. J Real-Time Image Proc 9, 635–646 (2014). [Google Scholar]
  7. Ribeiro, O.; Gomes, L.; Vale, Z. IoT-Based Human Fall Detection System. Electronics 2022, 11, 592. [Google Scholar]
  8. Shu, F., Shu, J. An eight-camera fall detection system using human fall pattern recognition via machine learning by a low-cost android box. Sci Rep 11, 2471 (2021). [Google Scholar]
  9. Quoc Thien Huynh and Uyen D. Nguyen and Binh Q. Tran, A Cloud-Based System for In-Home Fall Detection and Activity Assessment, IFMBE Proceedings, Id. Huynh2018ACS, 2018 [Google Scholar]
  10. S. S, S. Sheth, A. Kumar and B. Dwivedy, “An IoT Enabled Smart Wheelchair Solution for Physically Challenged People,” 2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN), Vellore, India, 2023, pp. 1–5, doi: 10.1109/ViTECoN58111.2023.10157231. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.