Vol. 4 No. 2 (2024): Journal of Machine Learning in Pharmaceutical Research
Articles

IoT-enabled Smart Assistive Technologies for Disabilities Rehabilitation: Designing IoT-based assistive technologies to support disabilities rehabilitation, empowering individuals with disabilities to regain functional independence and improve quality of

PDF
  • Dr. Victor Nguyen
Dr. Victor Nguyen
Associate Professor of Biomedical Engineering, Hanoi University of Science and Technology, Vietnam
Cover

Published 12-09-2024

Keywords

  • IoT,
  • functional independence
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Dr. Victor Nguyen, “IoT-enabled Smart Assistive Technologies for Disabilities Rehabilitation: Designing IoT-based assistive technologies to support disabilities rehabilitation, empowering individuals with disabilities to regain functional independence and improve quality of ”, Journal of Machine Learning in Pharmaceutical Research, vol. 4, no. 2, pp. 51–58, Sep. 2024, Accessed: Sep. 18, 2024. [Online]. Available: https://pharmapub.org/index.php/jmlpr/article/view/25

Abstract

This paper presents an in-depth exploration of IoT-enabled smart assistive technologies for disabilities rehabilitation. The rapid advancement of the Internet of Things (IoT) has opened up innovative possibilities in healthcare, particularly in the field of disabilities rehabilitation. By leveraging IoT, assistive technologies can be designed to provide personalized and adaptive support to individuals with disabilities, enabling them to regain functional independence and improve their quality of life. This paper discusses the design principles, technological components, and applications of IoT-based assistive technologies. It also examines the benefits, challenges, and future directions of these technologies in disabilities rehabilitation.

PDF

Downloads

Download data is not yet available.

References

  1. Saeed, A., Zahoor, A., Husnain, A., & Gondal, R. M. (2024). Enhancing E-commerce furniture shopping with AR and AI-driven 3D modeling. International Journal of Science and Research Archive, 12(2), 040-046.
  2. Shahane, Vishal. "A Comprehensive Decision Framework for Modern IT Infrastructure: Integrating Virtualization, Containerization, and Serverless Computing to Optimize Resource Utilization and Performance." Australian Journal of Machine Learning Research & Applications 3.1 (2023): 53-75.
  3. Biswas, Anjanava, and Wrick Talukdar. "Guardrails for trust, safety, and ethical development and deployment of Large Language Models (LLM)." Journal of Science & Technology 4.6 (2023): 55-82.
  4. N. Pushadapu, “Machine Learning Models for Identifying Patterns in Radiology Imaging: AI-Driven Techniques and Real-World Applications”, Journal of Bioinformatics and Artificial Intelligence, vol. 4, no. 1, pp. 152–203, Apr. 2024
  5. Talukdar, Wrick, and Anjanava Biswas. "Improving Large Language Model (LLM) fidelity through context-aware grounding: A systematic approach to reliability and veracity." arXiv preprint arXiv:2408.04023 (2024).
  6. Chen, Jan-Jo, Ali Husnain, and Wei-Wei Cheng. "Exploring the Trade-Off Between Performance and Cost in Facial Recognition: Deep Learning Versus Traditional Computer Vision." Proceedings of SAI Intelligent Systems Conference. Cham: Springer Nature Switzerland, 2023.
  7. Alomari, Ghaith, et al. “AI-Driven Integrated Hardware and Software Solution for EEG-Based Detection of Depression and Anxiety.” International Journal for Multidisciplinary Research, vol. 6, no. 3, May 2024, pp. 1–24.
  8. Choi, J. E., Qiao, Y., Kryczek, I., Yu, J., Gurkan, J., Bao, Y., ... & Chinnaiyan, A. M. (2024). PIKfyve, expressed by CD11c-positive cells, controls tumor immunity. Nature Communications, 15(1), 5487.
  9. Borker, P., Bao, Y., Qiao, Y., Chinnaiyan, A., Choi, J. E., Zhang, Y., ... & Zou, W. (2024). Targeting the lipid kinase PIKfyve upregulates surface expression of MHC class I to augment cancer immunotherapy. Cancer Research, 84(6_Supplement), 7479-7479.
  10. Gondal, Mahnoor Naseer, and Safee Ullah Chaudhary. "Navigating multi-scale cancer systems biology towards model-driven clinical oncology and its applications in personalized therapeutics." Frontiers in Oncology 11 (2021): 712505.
  11. Saeed, Ayesha, et al. "A Comparative Study of Cat Swarm Algorithm for Graph Coloring Problem: Convergence Analysis and Performance Evaluation." International Journal of Innovative Research in Computer Science & Technology 12.4 (2024): 1-9.
  12. Pelluru, Karthik. "Prospects and Challenges of Big Data Analytics in Medical Science." Journal of Innovative Technologies 3.1 (2020): 1-18.
  13. Tatineni, Sumanth. "Addressing Privacy and Security Concerns Associated with the Increased Use of IOT Technologies in the US Healthcare Industry." Technix International Journal for Engineering Research (TIJER) 10.10 (2023): 523-534.