

FIT-QUEST – Personal Fitness App
Abstract
References
. E. Siira, J. Häikiö and E. Annanperä, "Mobile gaming in gyms — Can fitness and games join together?," 2018 IEEE 6th International Conference on Serious Games and Applications for Health (SeGAH), Vienna, Austria, 2018, pp. 1-6, doi: 10.1109/SeGAH.2018.8401350.
. Hannan, Abdul & Shafiq, Muhammad & Hussain, Faisal & Pires, Ivan. (2021). A Portable Smart Fitness Suite for Real-Time Exercise Monitoring and Posture Correction. 21.10.3390/s21196692
. V. S. P. Bhamidipati, I. Saxena, D. Saisanthiya and 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, 2023, pp. 1-7 doi:10.1109/ICNWC57852.2023.10127264
. Bagga, Ereena & Yang, Ang. (2024). Real-Time Posture Monitoring and Risk Assessment for Manual Lifting Tasks Using MediaPipe and LSTM. 10.48550/arXiv.2408.12796.
. Utilizing Google’s Machine Learning Kit in Developing Android Application by chi Nguyen.
. Zhang, X., & Wang, J. (2020). Human Pose Estimation with Deep Learning: A Review.
IEEE Transactions on Circuits and Systems for Video Technology.
. Rahman, M., Roggen, D., & Parate, A. (2019). Counting Repetitions in Exercises Using Wearable Sensors and Machine Learning. ACM UbiComp.
. Shoaib, M., Bosch, S., Incel, O. D., Scholten, H., & Havinga, P. J. (2015). Complex Human Activity Recognition Using Smartphone and Wrist-Worn Motion Sensors. Sensors, 15(5), 11001-11025.
. Chen, K., Lin, M., Chen, H., & Ke, W. (2021). Deep Learning-based Exercise Posture Recognition and Repetition Counting using Mobile Devices. IEEE Access.
. Mathur, A., & Nadeem, T. (2019). Using Computer Vision for Automated Exercise Analysis: A Review. International Conference on Artificial Intelligence and Signal Processing (AISP).
Refbacks
- There are currently no refbacks.