Smart Rehabilitation: Integrating IoT and Deep Learning for Personalized Therapy
Abstract
Rehabilitation therapy is essential for patients recovering from injuries or surgeries, but traditional approaches often lack personalization. This paper presents a smart rehabilitation system that uses IoT devices and deep learning to provide personalized therapy plans. IoT sensors monitor patient movements and progress, while deep learning algorithms analyze the data to adapt therapy exercises in real-time. A clinical trial involving post-stroke patients shows that the system enhances recovery outcomes and patient engagement. The paper also addresses the technical challenges and future prospects of smart rehabilitation technologies.
References
Gonzalez, R., & Martinez, S. (2021). Blockchain for IoT Security and Privacy: A Systematic Review. Sensors, 21(10), 3264. https://doi.org/10.3390/s21103264
Patel, S., & Mehta, P. (2019). IoT in Healthcare: Applications, Challenges, and Future Trends. Health Informatics Journal, 25(2), 651-666. https://doi.org/10.1177/1460458217731250
Kondru, V. L. P. (2016). Exploring the Interplay of Food Habits, Genetics, and Environment: Implications for Dental and General Health. International Journal of AI-Assisted Medicine , 3(3), 1-20.
Kondru, V. L. P. (2016). Smoking, Alcohol Consumption, and Periodontitis: A Comprehensive Review of the Association and Implications for Oral Health. Transactions on Latest Trends in Health Sector, 8(8).
Kondru, V. L. P. (2016). Addressing the Disparities: The Burden of Dental Health in Low-Income Countries vs. Developed Countries and its Impact on Government Resources and Societal Well-being. International Journal of Medical Informatics and AI, 3(3), 1-17.
Kondru, V. L. P. (2015). Comparative Analysis of Healthcare Systems: A Study of India and the United States. Transactions on Latest Trends in Health Sector, 7(7).
Kondru, V. L. P. (2015). Electronic Health Care Records-Boon To Industry. International Journal of Medical Informatics and AI, 2(2), 1-18.
Kondru, V. L. P. (2014). Understanding Fluorosis: Implications for Dental and General Health. Transactions on Latest Trends in Health Sector, 6(6).
Kondru, V. L. P. (2014). Comparative Analysis of Oral Cancer Prevalence: Rural vs. Urban India and India vs. Developed . Journal of Healthcare Data Science and AI , 1(1), 1-20.
Kondru, V. L. P. (2014). Understanding Fluorosis: Implications for Dental and General Health. Transactions on Latest Trends in Health Sector, 6(6).
Kondru, V. L. P. (2014). Disparities in Dental Health Education: A Comparative Study of Rural and Urban Populations in India. International Journal of Medical Informatics and AI, 1(1), 1-17.
Kondru, V. L. P. (2014). A Review of the Association between Smoking, Alcohol Consumption, and Oral Cancer Risk. Journal of Healthcare AI and ML , 1(1), 1-18. https://journalpublication.wrcouncil.org/index.php/JHAM/article/view/6
Singh, A., & Gupta, R. (2020). Predictive Maintenance in Industrial IoT: Applications and Challenges. IEEE Transactions on Industrial Informatics, 16(8), 5344-5353. https://doi.org/10.1109/TII.2019.2963462
Chen, Q., & Zhang, L. (2019). Privacy-Preserving Data Analytics in IoT: Techniques and Applications. IEEE Internet of Things Journal, 6(2), 1504-1518. https://doi.org/10.1109/JIOT.2018.2871717
Nadella, G. S., & Pillai, S. E. V. S. (2024, March). Examining the Indirect Impact of Information and System Quality on the Overall Educators' Use of E-Learning Tools: A PLS-SEM Analysis. In SoutheastCon 2024 (pp. 360-366). IEEE.
Yadav, H. (2023). Enhanced Security, Privacy, and Data Integrity in IoT Through Blockchain Integration. International Journal of Sustainable Development in Computing Science, 5(4), 1-10.
