Utilization of Augmented Reality for Human Organ Analysis

Main Article Content

Neha Gupta
Ashish Bansal
Ihtiram Raza Khan
Nilesh Shubhash Vani

Abstract

This research paper investigates the utilization of augmented reality (AR) technology for human organ analysis in medical education. The study aims to develop and evaluate an AR application that provides an immersive and interactive learning experience for medical students. The research follows a quantitative methodology, to develop and test the effectiveness of the AR application in improving learning outcomes. The research examines the impact of the AR application on student engagement, retention of information, and performance on assessments. The results show that the AR application has a significant positive impact on learning outcomes. The use of AR technology improves student engagement, retention of information, and performance on assessments. The application's design and functionality were found to be intuitive and user-friendly, making it accessible for both students and educators. The research highlights the potential of AR technology in medical education and provides insights into its effectiveness in improving learning outcomes. The findings suggest that AR technology can be a valuable tool in medical education, enhancing the way students learn about human anatomy. This research can contribute to the existing literature on the use of AR technology in education, paving the way for future research and innovation in the field. Ultimately, the study shows that the integration of AR technology in medical education can significantly enhance the learning experience for students, providing them with an immersive and interactive approach to learning about human anatomy.

Article Details

How to Cite
Gupta, N. ., Bansal, A. ., Khan, I. R. ., & Vani, N. S. . (2023). Utilization of Augmented Reality for Human Organ Analysis. International Journal on Recent and Innovation Trends in Computing and Communication, 11(8s), 438–444. https://doi.org/10.17762/ijritcc.v11i8s.7224
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Articles

References

The Prasanna, L. C., & D'souza, M. R. (2019). Augmented reality: An innovative educational tool in human anatomy education. Journal of Clinical and Diagnostic Research, 13(4), JM01-JM04.

Fardoun, H. M., & Hammoudi, H. (2017). Augmented reality applications in learning of human anatomy: A literature review. Journal of King Saud University-Computer and Information Sciences, 29(3), 392-402.

Serrano-Laguna, Á., Fernández-Sanz, L., Villalba-Mora, E., & Delgado-Marquez, B. L.(2019). Augmented reality for learning human anatomy: An evaluation of the Human Anatomy Atlas AR app. Journal of Medical Systems, 43(5), 117.

Khor, W. S., & Tan, B. H. (2019). An augmented reality approach for enhancing learning and retention of human anatomy. Studies in Health Technology and Informatics, 264, 902-906.

Abhari, K., Shafigh, F., Aminpour, F., & Ahmadzadeh, H. (2017). Augmented reality in medical education: A systematic review. Journal of Medical Systems, 41(8), 122.

M. Rajkumar, N. Gupta, M. Singhal “Application Of Supervised Machine Learning Techniques for Classification of Brain Stroke”, Journal of Otorhinolaryngology and Head and Neck Surgery, Vol 27, Issue 1 (2023), pp.377-387

M. Dhawan, L. Purohit, N. Gupta “ A Comprehensive Study on the Latest Trends of Cyber Security in the health care domain”, The 6th International Conference on “Emerging Technologies in Computer Engineering: Industrial IoT and Cyber Physical Systems."(ICETCE-2023) (February 08, 2023). Proceedings of the International Conference on Communications in computer and information science.

N. Gupta, V. Dutta” Sentimental analysis using deep learning techniques. International Journa of Scientific and Research Publications, Vol 12 Issue 2 (2022), 550–556. https://doi.org/10.29322/IJSRP.12.02.2022.p12268

Y. Prasad, N. Gupta “Implementation of Machine Learning Based Google Teachable Machine in Early Childhood Education”, International Journal of Early Childhood Special Education (INT-JECSE), Vol 14 Issue 3 (2022), pp.4132–4139.

Viswanathan, D., Kumari, S., & Navaneetham, P. (2023). Soft C-means Multi objective Metaheuristic Dragonfly Optimization for Cluster Head Selection in WSN. International Journal of Intelligent Systems and Applications in Engineering, 11(2s), 88–95. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2513

Azuma, R. T. (1997). A survey of augmented reality. Presence: Teleoperators and Virtual Environments, 6(4), 355-385.

Bizzotto, N., Sandri, A., Regis, D., Tami, I., Magnan, B., Bartolozzi, P. (2017). Augmented reality in orthopaedics: a systematic review. Bone & Joint Research, 6(7), 403-411.

Di Flumeri, G., Aricò, P., Borghini, G., Colosimo, A., Bonelli, S., Golfetti, A., ... & Babiloni, F. (2018). EEG-based mental workload neurometric to evaluate the impact of different traffic and road conditions in real driving settings. Frontiers in Human Neuroscience, 12, 509.

Hsieh, C. H., & Hsu, H. P. (2011). Augmented reality system for real-time medical training and guidance. Journal of Medical Systems, 35(5), 969-979.

Liao, H., Tang, Z., & Chen, C. (2019). Augmented reality and virtual reality in healthcare education: a review. Medical Education, 53(9), 880-893.

Lozano-Quilis, J. A., & Gil-Gómez, H. (2018). Technology advances for telerehabilitation: VR, AR, and robotics. In Rehabilitation Robotics (pp. 35-48). Springer, Cham.

Tang, Z., Zhou, L., Li, Z., & Chen, C. (2016). Virtual reality and mixed reality for virtual learning environments. Computers & Education, 102, 220-230.

Bork, F., Pfarrkirchner, K., Hirtler, L., Kehrer, A., Alizadeh-Naeeni, M., & Augsten, N.(2019). Augmented reality in gastrointestinal endoscopy: a systematic review and future perspectives. Digestive Endoscopy, 31(5), 478-484

Feng, X., Finocchiaro, T., Hafezi, N., Krishnaswamy, P., & Yan, J. (2018). Augmented reality in gastrointestinal endoscopy: challenges and future directions. World Journal of Gastroenterology, 24(26), 2785-2796.

?en, H., Tuna, Y., & Özturan, M. (2020). Augmented reality in otolaryngology: a systematic review. European Archives of Oto-Rhino-Laryngology, 277(10), 2699-2707.