Visual Gait Analysis Based on UE4

Area of Science:

• Computer Science
• Biomedical Engineering
• Human Motion Analysis

Background:

• Artificial intelligence and virtual reality technologies are increasingly integrated into medical and entertainment fields.
• Accurate human motion analysis is crucial for applications such as gait analysis and rehabilitation.

Purpose of the Study:

• To design and develop a 3D human pose model using the UE4 platform and inertial sensors.
• To enable real-time display and analysis of human body posture and motion data.
• To improve the accuracy of motion data through real-time calibration and error compensation.

Main Methods:

• Utilized the UE4 3D modeling platform with blueprint language and C++ programming.
• Developed a 3D pose model based on inertial sensor data.
• Integrated independent coordinate systems for each body part to analyze angles and displacements.
• Implemented automatic calibration and error correction for inter-related joint data.

Main Results:

• The 3D pose model accurately displays gait, limb angles, and displacements in real-time.
• The system effectively combines motion capture with 3D visualization.
• Motion data errors from inertial sensors were compensated, ensuring model integrity and anatomical correctness.

Conclusions:

• The developed 3D pose model offers accurate, real-time human motion display and data correction.
• This technology shows significant potential for applications in gait analysis and biomechanics.
• The model's ability to self-correct errors enhances the reliability of motion capture data.