Evolution in Real-Time Automated systems for Personalized Exercise Guidance and Monitoring

Authors

DOI:

https://doi.org/10.26438/ijcse/v12i3.3036

Keywords:

Autonomous Robot Navigation, Human Pose Estimation, Mediapipe, Computer Vision

Abstract

This comprehensive review delves into the dynamic realm of AI-driven fitness assistance and robotic navigation, exploring the evolving challenges and advancements in human pose estimation, fitness assessment, and user engagement during workout sessions. The surveyed studies employ diverse methodologies, spanning from real-time exercise pose identification using OpenCV and MediaPipe to innovative applications like sound localization and deep learning. The paper also explores the integration of robotics in fitness assistance, showcasing systems for social support and personalized workout recommendations. Furthermore, it investigates advancements in robotic navigation, employing both complex and simplified approaches to seamlessly integrate into workout scenarios. This integration aims to provide in-depth workout analysis and accurate guidance to users while autonomously navigating the environment. The convergence of computer vision, machine learning, image processing, and the Internet of Things emerges as a pivotal approach, offering a holistic solution for immersive fitness experiences in both home and gym settings.

References

[1] Štajer, Valdemar, Milovanovi?, Ivana, Todorovi?, Nikola, Ranisavljev, Marijana, Pišot, Saša, and Drid, Patrik. "Let`s (Tik) Talk About Fitness Trends." Frontiers in Public Health, Vol. 10, pp. 899949, 2022.

[2] V. S. P. Bhamidipati, I. Saxena, D. Saisanthiya, and M. Retnadhas, "Robust Intelligent Posture Estimation for an AI Gym Trainer using Mediapipe and OpenCV," in Proceedings of the 2023 International Conference on Networking and Communications (ICNWC), Chennai, India, pp. 1-7, 2023.

[3] G. Taware, R. Kharat, P. Dhende, P. Jondhalekar, and R. Agrawal, "AI-Based Workout Assistant and Fitness Guide," in Proceedings of the 2022 6th International Conference On Computing, Communication, Control And Automation (ICCUBEA), Pune, India, pp. 1-4, 2022.

[4] S. Kardam and S. Maggu, "AI Personal Trainer using OpenCV and Python," International Journal of Computer Science, Vol. 9, Issue 12, pp. 2425-2427, 2021.

[5] J. Fasola and M. J. Mataric, "Robot exercise instructor: A socially assistive robot system to monitor and encourage physical exercise for the elderly," in Proceedings of the 19th International Symposium in Robot and Human Interactive Communication, Viareggio, Italy, pp. 416-421, 2010.

[6] K. Enoksson and B. Zhou, "Sound following robot," KTH Royal Institute of Technology, Stockholm, Sweden, 2017.

[7] Jitesh, "AI Robot - Human Following Robot using TensorFlow Lite on Raspberry Pi," 2021.

[8] F. Haugg, M. Elgendi, and C. Menon, "GRGB rPPG: An Efficient Low-Complexity Remote Photoplethysmography-Based Algorithm for Heart Rate Estimation," Bioengineering, vol. 10, no. 2, pp. 243, 2023.

[9] G. Dsouza, D. Maurya, and A. Patel, "Smart gym trainer using Human pose estimation," in Proceedings of the 2020 IEEE International Conference for Innovation in Technology (INOCON), Bangalore, India, pp. 1-4, 2020.

[10] L. Xu et al., "ZoomNAS: Searching for Whole-Body Human Pose Estimation in the Wild," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 4, pp. 5296-5313, 2023.

[11] Ce Zheng, Wenhan Wu, Taojiannan Yang, Sijie Zhu, Chen Chen, Ruixu Liu, Ju Shen, Nasser Kehtarnavaz, and Mubarak Shah, "Deep Learning-Based Human Pose Estimation: A Survey," 2020.

[12] Chen, Steven & Yang, Richard, "Pose Trainer: Correcting Exercise Posture using Pose Estimation," 2018.

[13] P. Zell, B. Wandt, and B. Rosenhahn, "Joint 3D human motion capture and physical analysis from monocular videos," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 17–26, 2017.

[14] A. Flores, B. Hall, L. Carter, M. Lanum, R. Narahari, and G. Goodman, "Verum Fitness: An AI Powered Mobile Fitness Safety and Improvement Application," in Proceedings of the 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), Washington, DC, USA, pp. 980-984, 2021.

[15] N. Faujdar, S. Saraswat, and S. Sharma, "Human Pose Estimation using Artificial Intelligence with Virtual Gym Tracker," in Proceedings of the 2023 6th International Conference on Information Systems and Computer Networks (ISCON), Mathura, India, pp. 1-5, 2023.

[16] H. V. R. Podduturi, C. Varla, K. R. Gopaldinne, N. Bhukya, R. K. Reddy Nallagondu, and G. S. Bapiraju, "Smart Trainer using OpenCV," in Proceedings of the 2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA), Uttarakhand, India, pp. 477-480, 2023.

[17] T. T. Tran, J. W. Choi, C. Van Dang, G. SuPark, J. Y. Baek, and J. W. Kim, "Recommender System with Artificial Intelligence for Fitness Assistance System," in Proceedings of the 2018 15th International Conference on Ubiquitous Robots (UR), Honolulu, HI, USA, pp. 489-492, 2018.

[18] R. Bi, D. Gao, X. Zeng, and Q. Zhu, "LAZIER: A Virtual Fitness Coach Based on AI Technology," in Proceedings of the 2022 IEEE 5th International Conference on Information Systems and Computer Aided Education (ICISCAE), Dalian, China, pp. 207-212, 2022.

[19] X. Li, M. Zhang, J. Gu, and Z. Zhang, "Fitness Action Counting Based on MediaPipe," in Proceedings of the 2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), Beijing, China, pp. 1-7, 2022.

[20] R. Achkar, R. Geagea, H. Mehio, and W. Kmeish, "SmartCoach personal gym trainer: An Adaptive Modified Backpropagation approach," in Proceedings of the 2016 IEEE International Multidisciplinary Conference on Engineering Technology (IMCET), Beirut, Lebanon, pp. 218-223, 2016.

[21] K. B. Lee and R. A. Grice, "The Design and Development of User Interfaces for Voice Application in Mobile Devices," in Proceedings of the 2006 IEEE International Professional Communication Conference, Saragota Springs, NY, USA, pp. 308-320, 2006.

[22] A. Chaudhry, M. Batra, P. Gupta, S. Lamba, and S. Gupta, "Arduino Based Voice Controlled Robot," in Proceedings of the 2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS), Greater Noida, India, pp. 415-417, 2019.

[23] S. Chakraborty, N. De, D. Marak, M. Borah, S. Paul, and V. Majhi, "Voice Controlled Robotic Car Using Mobile Application," in Proceedings of the 2021 6th International Conference on Signal Processing, Computing and Control (ISPCC), Solan, India, pp. 1-5, 2021.

[24] F. Salih and M. S. A. Omer, "Raspberry Pi as a Video Server," in Proceedings of the 2018 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE), Khartoum, Sudan, pp. 1-4, 2018.

[25] Muhammad Khan, Max Kenney, Jack Painter, Disha Kamale, Riza Batista-Navarro, and Amir Ghalamzan, "Natural Language Robot Programming: NLP integrated with autonomous robotic grasping," 2023.

[26] C. Wang, et al., "Autonomous mobile robot navigation in uneven and unstructured indoor environments," in Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada, pp. 109-116, 2017.

[27] K. Yokoyama and K. Morioka, "Autonomous Mobile Robot with Simple Navigation System Based on Deep Reinforcement Learning and a Monocular Camera," in Proceedings of the 2020 IEEE/SICE International Symposium on System Integration (SII), Honolulu, HI, USA, pp. 525-530, 2020.

[28] Y. Sun, J. Yang, D. Zhao, and S. Li, "Personal Care Robot Navigation System Based on Multi-sensor Fusion," in Proceedings of the 2021 IEEE International Conference on Intelligence and Safety for Robotics (ISR), Tokoname, Japan, pp. 408-412, 2021.

[29] Goswami, Shankha & Sahoo, Sushil Kumar. "Design of a Robotic Vehicle to Avoid Obstacle Using Arduino Microcontroller and Ultrasonic Sensor". Journal of Advances in Transportation Engineering, 2023.

[30] Cristina Bolaños, Jesús Fernández-Bermejo, Javier Dorado, Henry Agustín, Félix Jesús Villanueva, María José Santofimia. A Comparative Analysis of Pose Estimation Models as Enablers for a Smart-Mirror Physical Rehabilitation System. Procedia Computer Science, Vol. 207, pp. 2536-2545, 2022.

[31] Gupta, N., Gupta, S.K., Pathak, R.K. et al. "Human Activity Recognition in Artificial Intelligence Framework: A Narrative Review." Artificial Intelligence Review, Vol. 55, pp. 4755-4808, 2022.

Downloads

Published

2024-03-31
CITATION
DOI: 10.26438/ijcse/v12i3.3036
Published: 2024-03-31

How to Cite

[1]
S. Walke, Y. Wadekar, A. Ladawa, S. V. Pandit, and P. Khopade, “Evolution in Real-Time Automated systems for Personalized Exercise Guidance and Monitoring”, Int. J. Comp. Sci. Eng., vol. 12, no. 3, pp. 30–36, Mar. 2024.

Issue

Vol. 12 No. 3 (2024): IJCSE March Edition

Section

Review Article

License

Creative Commons License

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

Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.