Citation:

Naga Ramesh Palakurti, 2023. AI-Driven Personal Health Monitoring Devices: Trends and Future Directions, ESP Journal of Engineering & Technology Advancements  3(3): 41-51.

Abstract:

Over the last few years, personal health monitoring wearable devices have emerged as innovative applications of Artificial Intelligence (AI) in the healthcare industry as they help in real time analysis and prediction of health standardized check-ups and health management. To navigate through the current trends, new technologies and developments, the prospects are as follows: The article also gives a logical look at the state of the art of such devices, enumerating the advantages and drawbacks, as well as outlining the main ethical issues. In terms of method, it also discusses different AI approaches, data acquisition procedures, and those integrating systems used in the context of health monitoring. The finding and implication section discusses the findings of the current trend and the possibility of improvement in application and user acceptance. The last section provides a prognosis on what the area of personal health monitoring might look like in the future, as well as the position of AI in the optimisation of patient experience.

References:

[1] The Evolution Of AI In Healthcare, xsolis, https://www.xsolis.com/blog/the-evolution-of-ai-in-healthcare/
[2] Innovating Well-Being: The Future of Personal Health Monitoring Devices, https://blog.emb.global/future-of-personal-health-monitoring-devices/#:~:text=One%20of%20the%20significant%20milestones,sleep%20patterns%20have%20become%20mainstream.
[3] Sarker, I.H. Machine Learning: Algorithms, Real-World Applications and Research Directions. SN COMPUT. SCI. 2, 160 (2021). https://doi.org/10.1007/s42979-021-00592-x
[4] Nittas V, Zecca C, Kamm CP, Kuhle J, Chan A, von Wyl V. Digital health for chronic disease management: An exploratory method to investigating technology adoption potential. PLoS One. 2023 Apr 13;18(4):e0284477. doi: 10.1371/journal.pone.0284477.
[5] The Future of AI in Healthcare: Trends and Innovations, cprime, https://www.cprime.com/resources/blog/the-future-of-ai-in-healthcare-trends-and-innovations/
[6] Olawade, David B., et al. “Enhancing mental health with Artificial Intelligence: Current trends and future prospects.” Journal of medicine, surgery, and public health (2024): 100099.
[7] System architecture of the health monitoring systems, https://www.researchgate.net/figure/System-architecture-of-the-health-monitoring-systems_fig1_338246586
[8] Artificial intelligence (AI) algorithms: a complete overview, tableau, https://www.tableau.com/data-insights/ai/algorithms
[9] AI-driven remote patient monitoring, 2023. https://www.geneca.com/ai-driven-remote-patient-monitoring/
[10] Written by Emma Joseph, The Future Scope of AI in Healthcare, https://www.pixelcrayons.com/blog/digital-transformation/the-future-scope-of-ai-in-healthcare/
[11] Doctor, Akbar. "Manufacturing of medical devices using artificial intelligence-based troubleshooters." Biomedical Signal and Image Processing with Artificial Intelligence. Cham: Springer International Publishing, 2023. 195-206. [Google Scholar]
[12] Empowering Rules Engines: AI and ML Enhancements in BRMS for Agile Business Strategies. (2022). International Journal of Sustainable Development through AI, ML and IoT, 1(2), 1-20. https://ijsdai.com/index.php/IJSDAI/article/view/36
[13] Naga Ramesh Palakurti, 2022. "AI Applications in Food Safety and Quality Control" ESP Journal of Engineering & Technology Advancements 2(3): 48-61.
[14] S. E. V. S. Pillai, A. A. ElSaid and W. -C. Hu, "A Self-Reconfigurable System for Mobile Health Text Misinformation Detection," 2022 IEEE International Conference on Electro Information Technology (eIT), Mankato, MN, USA, 2022, pp. 242-247, doi: 10.1109/eIT53891.2022.9813840.
[15] Ayyalasomayajula, M. M. T., Chintala, S., & Sailaja, A. (2019). A Cost-Effective Analysis of Machine Learning Workloads in Public Clouds: Is AutoML Always Worth Using? International Journal of Computer Science Trends and Technology (IJCST), 7(5), 107–115.
[16] Bhat, V. Gojanur, and R. Hegde. 2015. 4G protocol and architecture for BYOD over Cloud Computing. In Communications and Signal Processing (ICCSP), 2015 International Conference on. 0308-0313. Google Scholar. [Link]
[17] Muthukumaran Vaithianathan, Mahesh Patil, Shunyee Frank Ng, Shiv Udkar, 2023. "Comparative Study of FPGA and GPU for High-Performance Computing and AI" ESP International Journal of Advancements in Computational Technology (ESP-IJACT) Volume 1, Issue 1: 37-46. [PDF]
[18] Kalla, Dinesh, Nathan Smith, Fnu Samaah, and Kiran Polimetla. "Enhancing Early Diagnosis: Machine Learning Applications in Diabetes Prediction." Journal of Artificial Intelligence & Cloud Computing. SRC/JAICC-205. DOI: doi. org/10.47363/JAICC/2022 (1) 191 (2022): 2-7.
[19] Piyush Ranjan, 2022.”Fundamentals Of Digital Transformation In Financial Services: Key Drivers and Strategies”, International Journal of Core Engineering & Management, Volume 7, Issue 3, PP 41-50, [Link]

Keywords:

AI-driven health monitoring, Wearable devices, Predictive analytics, Health Management, Machine Learning.