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Workout Monitoring Robot: A Robotic Approach for Real-Time Workout Monitoring and Guidance

Shreyas Walke1 , Yash Wadekar2 , Aditya Ladawa3 , Pratik Khopade4 , Shraddha V. Pandit5

  1. Dept. of Artificial Intelligence and Data Science, PES’s Modern College of Engineering, India.
  2. Dept. of Artificial Intelligence and Data Science, PES’s Modern College of Engineering, India.
  3. Dept. of Artificial Intelligence and Data Science, PES’s Modern College of Engineering, India.
  4. Dept. of Artificial Intelligence and Data Science, PES’s Modern College of Engineering, India.
  5. Dept. of Artificial Intelligence and Data Science, PES’s Modern College of Engineering, India.

Section:Research Paper, Product Type: Journal Paper
Volume-12 , Issue-8 , Page no. 1-9, Aug-2024

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v12i8.19

Online published on Aug 31, 2024

Copyright © Shreyas Walke, Yash Wadekar, Aditya Ladawa, Pratik Khopade, Shraddha V. Pandit . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Shreyas Walke, Yash Wadekar, Aditya Ladawa, Pratik Khopade, Shraddha V. Pandit, “Workout Monitoring Robot: A Robotic Approach for Real-Time Workout Monitoring and Guidance,” International Journal of Computer Sciences and Engineering, Vol.12, Issue.8, pp.1-9, 2024.

MLA Style Citation: Shreyas Walke, Yash Wadekar, Aditya Ladawa, Pratik Khopade, Shraddha V. Pandit "Workout Monitoring Robot: A Robotic Approach for Real-Time Workout Monitoring and Guidance." International Journal of Computer Sciences and Engineering 12.8 (2024): 1-9.

APA Style Citation: Shreyas Walke, Yash Wadekar, Aditya Ladawa, Pratik Khopade, Shraddha V. Pandit, (2024). Workout Monitoring Robot: A Robotic Approach for Real-Time Workout Monitoring and Guidance. International Journal of Computer Sciences and Engineering, 12(8), 1-9.

BibTex Style Citation:
@article{Walke_2024,
author = {Shreyas Walke, Yash Wadekar, Aditya Ladawa, Pratik Khopade, Shraddha V. Pandit},
title = {Workout Monitoring Robot: A Robotic Approach for Real-Time Workout Monitoring and Guidance},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {8 2024},
volume = {12},
Issue = {8},
month = {8},
year = {2024},
issn = {2347-2693},
pages = {1-9},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5712},
doi = {https://doi.org/10.26438/ijcse/v12i8.19}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v12i8.19}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5712
TI - Workout Monitoring Robot: A Robotic Approach for Real-Time Workout Monitoring and Guidance
T2 - International Journal of Computer Sciences and Engineering
AU - Shreyas Walke, Yash Wadekar, Aditya Ladawa, Pratik Khopade, Shraddha V. Pandit
PY - 2024
DA - 2024/08/31
PB - IJCSE, Indore, INDIA
SP - 1-9
IS - 8
VL - 12
SN - 2347-2693
ER -

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Abstract

In this research paper, we present the development and implementation of a cutting-edge Workout Monitoring Robot designed to monitor and guide user’s exercises with its capability of pose estimation and correction and natural language interactions that revolutionize the way individuals engage in exercise routines. Whereas the current research that part-take in similar activities have had much difficulty in flexibility and ease of interaction. This study focuses on enhancing the effectiveness and safety of physical fitness activities by imposing advanced technologies including human pose estimation, autonomous robot navigation and a sophisticated human-computer interface driven by NLP. This research attempts to open the door to a new era of smart and responsive workout assistance, ultimately improving health and well-being.

Key-Words / Index Term

Human Pose Estimation, Remote Photoplethysmography, Autonomous Robot Navigation, Natural Language Robot Programming

References

[1] V. Štajer, I.M. Milovanovic, N. Todorovic, M. Ranisavljev, S. Pišot, P. Drid, “Let’s (Tik) Talk About Fitness Trends,” Frontiers in Public Health, Vol.10, pp.899-949, 2022. DOI: 10.3389/fpubh.2022.899949.
[2] V.S.P. Bhamidipati, I. Saxena, D. Saisanthiya, M. Retnadhas, “Robust Intelligent Posture Estimation for an AI Gym Trainer using Mediapipe and OpenCV,” 2023 International Conference on Networking and Communications (ICNWC), Chennai, India, pp.1-7, 2023. DOI: 10.1109/ICNWC57852.2023.10127264.
[3] G. Taware, R. Kharat, P. Dhende, P. Jondhalekar, R. Agrawal, “AI-Based Workout Assistant and Fitness Guide,” 2022 6th International Conference on Computing, Communication, Control, and Automation (ICCUBEA), Pune, India, pp.1-4, 2022. DOI: 10.1109/ICCUBEA54992.2022.10010733.
[4] S. Kardam, S. Maggu, “AI Personal Trainer using OpenCV and Python,” International Journal of Advanced Research in Engineering and Science, Vol.9, Issue.12, 2021.
[5] J. Fasola, M.J. Mataric, “Robot exercise instructor: A socially assistive robot system to monitor and encourage physical exercise for the elderly,” 19th International Symposium on Robot and Human Interactive Communication, Viareggio, Italy, pp.416-421, 2010. DOI: 10.1109/ROMAN.2010.5598658
[6] K. Enoksson, B. Zhou, "Sound following robot," KTH Royal Institute of Technology, Stockholm, Sweden, June 2017.
[7] Jitesh, "AI Robot - Human Following Robot using TensorFlow Lite on Raspberry Pi," 2021.
[8] F. Haugg, M. Elgendi, C. Menon, “GRGB rPPG: An Efficient Low-Complexity Remote Photoplethysmography-Based Algorithm for Heart Rate Estimation,” Bioengineering, Vol.10, No.2, pp.243, 2023. DOI: 10.3390/bioengineering10020243.
[9] J. Greenblatt, "AI-Powered Smart Mirror," April 2020.
[10] G. Dsouza, D. Maurya, A. Patel, “Smart gym trainer using Human pose estimation,” 2020 IEEE International Conference for Innovation in Technology (INOCON), Bangalore, India, pp.1-4, 2020. DOI: 10.1109/INOCON50539.2020.9298212.
[11] L. Xu, S. Jin, W. Liu, C. Qian, W. Ouyang, P. Luo, X. Wang, “ZoomNAS: Searching for Whole-Body Human Pose Estimation in the Wild,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.45, No.4, pp.5296-5313, 2023. DOI: 10.1109/TPAMI.2022.3197352.
[12] C. Zheng, W. Wu, T. Yang, S. Zhu, C. Chen, R. Liu, J. Shen, N. Kehtarnavaz, M. Shah, “Deep Learning-Based Human Pose Estimation: A Survey,” 2020.
[13] S. Chen, R. Yang, “Pose Trainer: Correcting Exercise Posture using Pose Estimation,” 2018.
[14] P. Zell, B. Wandt, B. Rosenhahn, “Joint 3D human motion capture and physical analysis from monocular videos,” in Proc. IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp.17–26, 2017.
[15] A. Flores, B. Hall, L. Carter, M. Lanum, R. Narahari, G. Goodman, “Verum Fitness: An AI Powered Mobile Fitness Safety and Improvement Application,” 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), Washington, DC, USA, pp.980-984, 2021. DOI: 10.1109/ICTAI52525.2021.00156.
[16] N. Faujdar, S. Saraswat, S. Sharma, “Human Pose Estimation using Artificial Intelligence with Virtual Gym Tracker,” 2023 6th International Conference on Information Systems and Computer Networks (ISCON), Mathura, India, pp.1-5, 2023. DOI: 10.1109/ISCON57294.2023.10112064.
[17] H.V.R. Podduturi, C. Varla, K.R. Gopaldinne, N. Bhukya, R.K. Reddy Nallagondu, G.S. Bapiraju, “Smart Trainer using OpenCV,” 2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA), Uttarakhand, India, pp.477-480, 2023. DOI: 10.1109/ICIDCA56705.2023.10099780.
[18] T.T. Tran, J.W. Choi, C. Van Dang, G. SuPark, J.Y. Baek, J.W. Kim, “Recommender System with Artificial Intelligence for Fitness Assistance System,” 2018 15th International Conference on Ubiquitous Robots (UR), Honolulu, HI, USA, pp.489-492, 2018. DOI: 10.1109/URAI.2018.8441895.
[19] R. Bi, D. Gao, X. Zeng, Q. Zhu, “LAZIER: A Virtual Fitness Coach Based on AI Technology,” 2022 IEEE 5th International Conference on Information Systems and Computer Aided Education (ICISCAE), Dalian, China, pp.207-212, 2022. DOI: 10.1109/ICISCAE55891.2022.9927664.
[20] X. Li, M. Zhang, J. Gu, Z. Zhang, “Fitness Action Counting Based on MediaPipe,” 2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), Beijing, China, pp.1-7, 2022. DOI: 10.1109/CISPBMEI56279.2022.9980337.
[21] R. Achkar, R. Geagea, H. Mehio, W. Kmeish, “SmartCoach personal gym trainer: An Adaptive Modified Backpropagation approach,” 2016 IEEE International Multidisciplinary Conference on Engineering Technology (IMCET), Beirut, Lebanon, pp.218-223, 2016. DOI: 10.1109/IMCET.2016.7777455.
[22] K.B. Lee, R.A. Grice, “The Design and Development of User Interfaces for Voice Application in Mobile Devices,” 2006 IEEE International Professional Communication Conference, Saratoga Springs, NY, USA, pp.308-320, 2006. DOI: 10.1109/IPCC.2006.320364.
[23] A. Chaudhry, M. Batra, P. Gupta, S. Lamba, S. Gupta, “Arduino Based Voice Controlled Robot,” 2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS), Greater Noida, India, pp.415-417, 2019. DOI: 10.1109/ICCCIS48478.2019.8974532.
[24] S. Chakraborty, N. De, D. Marak, M. Borah, S. Paul, V. Majhi, “Voice Controlled Robotic Car Using Mobile Application,” 2021 6th International Conference on Signal Processing, Computing and Control (ISPCC), Solan, India, pp.1-5, 2021. DOI: 10.1109/ISPCC53510.2021.9609396.
[25] F. Salih, M.S.A. Omer, “Raspberry pi as a Video Server,” 2018 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE), Khartoum, Sudan, pp.1-4, 2018. DOI: 10.1109/ICCCEEE.2018.8515817.
[26] M. Arshad Khan, M. Kenney, J. Painter, D. Kamale, R. BatistaNavarro, A. Ghalamzan-E, “Natural Language Robot Programming: NLP integrated with autonomous robotic grasping,” arXiv e-prints, 2023. DOI: 10.48550/arXiv.2304.02993.
[27] Anand John, Divyakant Meva, "A Comparative Study of Various Object Detection Algorithms and Performance Analysis", International Journal of Computer Sciences and Engineering, Vol.8, Issue.10, pp.158-163, 2020.
[28] N. Raviteja, M. Lavanya, S. Sangeetha, "An Overview on Object Detection and Recognition", International Journal of Computer Sciences and Engineering, Vol.8, Issue.2, pp.42-45, 2020.