Current Volume 9
NeuroFlex: AI-Driven Real-Time Exercise Monitoring and Adaptive Workout Planning Using MediaPipe and Computer Vision
Abstract
The rapid development of digital health technologies has created new opportunities for smart and accessible fitness solutions. This paper presents the design and implementation of an AI-driven real-time exercise monitoring and adaptive workout planning system using computer vision and pose estimation. The proposed system integrates a Flask backend with Me-diaPipe Pose and OpenCV to analyze human body landmarks using a standard webcam. It detects exercises such as squats, lunges, arm raises, and knee lifts, while counting repetitions in real time through joint angle computation and movement state transitions. In addition to repetition tracking, the system evaluates user performance using a lightweight accuracy estimation model based on movement consistency. An AI recommendation module pro-vides contextual coaching, including posture correction, motiva-tional feedback, and fatigue detection. The system also estimates calories burned using weight-adjusted exercise constants. Unlike traditional fitness applications that rely on manual input or wearable devices, the proposed solution requires only a webcam and browser, making it a low-cost and accessible alter-native. Experimental evaluation demonstrates reliable repetition detection and responsive feedback in controlled environments. This work highlights the potential of computer vision-based fitness coaching as an intelligent, interactive, and user-friendly approach for modern wellness applications.
Keywords
Artificial Intelligence, Computer Vision, Pose Estimation, Real-Time Exercise Monitoring, Fitness Technology, Human Activity Recognition, Adaptive Workout Planning, Me-diaPipe Pose
Citations
IRE Journals:
Aaron Agasthya Sanki, Shaik Nasreen, Chepuri Vignesh, Ch Lavanya, Shaik Meeravali "NeuroFlex: AI-Driven Real-Time Exercise Monitoring and Adaptive Workout Planning Using MediaPipe and Computer Vision" Iconic Research And Engineering Journals Volume 9 Issue 10 2026 Page 3472-3473 https://doi.org/10.64388/IREV9I10-1716920
IEEE:
Aaron Agasthya Sanki, Shaik Nasreen, Chepuri Vignesh, Ch Lavanya, Shaik Meeravali
"NeuroFlex: AI-Driven Real-Time Exercise Monitoring and Adaptive Workout Planning Using MediaPipe and Computer Vision" Iconic Research And Engineering Journals, 9(10) https://doi.org/10.64388/IREV9I10-1716920
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
Important Links
For Authors
Volume 8:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 7:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 6:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 5:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 4:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 3:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12