Real-Time Fitness Monitoring with MediaPipe

Authors: Chandra Prayaga, Lakshmi Prayaga, Aaron Wade, Kyle Rank, Gopi Shankar Mallu, Sri Satya Harsha Pola

Abstract:

In today's tech-driven world, where connectivity shapes our daily lives, maintaining physical and emotional health is crucial. Athletic trainers play a vital role in optimizing athletes' performance and preventing injuries. However, a shortage of trainers impacts the quality of care. This study introduces a vision-based exercise monitoring system leveraging Google's MediaPipe library for precise tracking of bicep curl exercises and simultaneous posture monitoring. We propose a three-stage methodology: landmark detection, side detection, and angle computation. Our system calculates angles at the elbow, wrist, neck, and torso to assess exercise form. Experimental results demonstrate the system's effectiveness in distinguishing between good and partial repetitions and evaluating body posture during exercises, providing real-time feedback for precise fitness monitoring.

Keywords: Physical health, athletic trainers, fitness monitoring, technology driven solutions, Google's MediaPipe, landmark detection, angle computation, real-time feedback.

References:

[1] Impellizzeri, F. M., Menaspà, P., Coutts, A. J., Kalkhoven, J., & Menaspà, M. J. (2020). Training load and its role in injury prevention, part I: back to the future. Journal of athletic training, 55(9), 885-892.
[2] Shanley, E., Thigpen, C. A., Chapman, C. G., Thorpe, J., Gilliland, R. G., & Sease, W. F. (2019). Athletic Trainers’ Effect on Population Health: Improving Access to and Quality of Care. Journal of Athletic Training, 54(2), 124–132. https://doi.org/10.4085/1062-6050-219-17.
[3] Post, E. G., Roos, K. G., Rivas, S., Kasamatsu, T. M., & Bennett, J. (2019). Access to Athletic Trainer Services in California Secondary Schools. Journal of Athletic Training, 54(12), 1229–1236. https://doi.org/10.4085/1062-6050-268-19.
[4] FitCoach: Virtual fitness coach empowered by wearable mobile devices | IEEE Conference Publication | IEEE Xplore. (n.d.). Ieeexplore.ieee.org. Retrieved February 16, 2024, from https://ieeexplore.ieee.org/document/8057208
[5] IMU-Based Walking Workouts Recognition | IEEE Conference Publication | IEEE Xplore. (n.d.). Ieeexplore.ieee.org. https://ieeexplore.ieee.org/abstract/document/8767285?casa_token=gR9EyQ8b5a4AAAAA:5ygo3ow3pkaTY3ufvGoxKp6JBaOYjNEaWLay3lUnhtT1JkRtseFl_PIiplwle_j7c_VvSgEh-Q
[6] Wang, N. (2020). ExerciseTrak: Reconstructing Arm Posture for Upper-Body Exercises using a Wrist-Mounted Motion Sensing Device. Ecommons.cornell.edu. https://ecommons.cornell.edu/items/4e429547-2ee5-4f9d-af3f-9355874de6d1
[7] Strömbäck, D., Huang, S., & Radu, V. (2020). MM-Fit. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 4(4), 1–22. https://doi.org/10.1145/3432701
[8] Youssef, F. F., Parque, V., & Gomaa, W. (2023). VCOACH: A Virtual Coaching System Based on Visual Streaming. Procedia Computer Science, 222, 207–216. https://doi.org/10.1016/j.procs.2023.08.158
[9] Lin, Y., Jiao, X., & Zhao, L. (2023). Detection of 3D Human Posture Based on Improved Mediapipe. Journal of Computer and Communications, 11(2), 102–121. https://doi.org/10.4236/jcc.2023.112008
[10] Body Posture Detection & Analysis System using MediaPipe. (2022, March 8). https://learnopencv.com/building-a-body-posture-analysis-system-using-mediapipe/