Title:

Push-Up Counter Using YOLOv8 Pose: Fitness Meets AI! 💪🤖

Introduction:

Exploring the potential of pose estimation, I developed an innovative push-up counter using Ultralytics YOLOv8’s pose estimation model. This system leverages AI to track body motion and count push-ups based on real-time angle calculations between keypoints. The result? A smarter, automated way to track your fitness progress!

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Highlights & Achievements

🟢 Pose Tracking with YOLOv8:
Using YOLOv8's pose model, I tracked keypoints such as the shoulder, elbow, and wrist. This enables precise monitoring of the body's position throughout the push-up motion.

🎥 Push-Up Counting Logic:
The system detects a complete push-up by calculating the angle between the keypoints:

• Down Position: Angle < 90°
• Up Position: Angle > 145°
  Each complete repetition increments the counter.

📝 Real-Time Annotations:
Every frame is annotated with the current push-up count and angle values, providing a live visual tracker during the exercise.

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What I Learned

1. Adaptability of YOLOv8:
   The pose estimation model is highly effective for tracking body motions and can be extended to other fitness activities like posture correction or exercise monitoring.

2. Angle-Based Detection:
   Using angles to track dynamic movements is a practical approach for exercise counting, opening possibilities for broader applications.

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Next Steps

🎯 Generalize for Other Exercises:
Extend the system to monitor squats, planks, jumping jacks, and more.

📈 Refine Counting Accuracy:
Fine-tune angle thresholds for better accuracy across various push-up styles and individual body types.

🛠️ Multi-Person Tracking:
Enable the model to handle multiple individuals in a frame for group workout sessions.

Conclusion

This project demonstrates the potential of integrating AI-driven pose estimation with fitness tracking. By leveraging YOLOv8's pose model, we developed a robust push-up counter capable of real-time motion tracking and angle-based detection. The system showcases significant promise not only for exercise monitoring but also for broader applications in health, rehabilitation, and sports analytics.

Future enhancements, such as multi-person tracking and adaptation to diverse exercises, will pave the way for a comprehensive AI fitness assistant. This work highlights how advanced technologies can be harnessed to revolutionize personal fitness and bring smarter solutions to everyday challenges.

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