Walking Analysis System

This project performs detailed analysis of walking patterns using various metrics derived from joint angles and step counts.

Overview

This project utilizes Python to analyze walking data, focusing on metrics such as joint angles, step counts, and symmetry. It leverages visualization techniques to provide insights into walking patterns and detect any abnormalities.

Requirement

• Operating System: macOS
• OpenCV: For video processing and analysis.
• Matplotlib: For data visualization.
• NumPy: For numerical calculations.
• Pandas: For data manipulation and analysis.
• SciPy: For advanced statistical and signal processing tasks.

Features

• 3D Visualization: Visualize joint movements in a 3D space.
• Angular Heat Map of Joints: Generate heat maps to display joint angles over time.
• Joint Angle Analysis: Analyze specific joint angles (e.g., hip, knee) during the walking cycle.
• Symmetry Analysis: Assess the symmetry of walking patterns.
• Step Count: Calculate the number of steps taken.
• Walking Cycle Analysis: Analyze the phases of the walking cycle.

File Descriptions

• 3D_visualisation.py: Script for visualizing joint movements in 3D.
• Angular_heat_map_of_joints.py: Script for generating angular heat maps.
• graph.py: Utility functions for plotting graphs and charts.
• hip_joint_angle.py: Analysis of hip joint angles.
• knee_angle_analysis.py: Analysis of knee joint angles.
• main.py: Main script to run the analysis.
• number_of_steps.py: Script for counting the number of steps.
• symmetry.py: Analysis of walking symmetry.
• walking_cycle.py: Analysis of the walking cycle phases.

Videos

Knee Angles Animation

[Watch the full video](https://raw.githubusercontent.com/s0ma0000/gait-analysis/main/dataset/knee_angles_animation2.mp4)

Author

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🐶 Contribution

Contributions are welcome! Please open an issue or submit a pull request.