Interpolation of segment Euler angles can provide a robust estimation of segment angular trajectories during...

Area of Science:

• Biomechanics
• Ergonomics
• Human Movement Analysis

Background:

• Video-based motion analysis for estimating joint moments relies on accurate kinematic data.
• Interpolation methods in the sagittal plane can introduce errors in joint angle trajectories during complex movements like asymmetric lifting.

Purpose of the Study:

• To evaluate the accuracy of cubic spline interpolation for estimating segment Euler angles in dynamic asymmetric lifting tasks.
• To compare interpolated joint angle trajectories with continuously measured data.

Main Methods:

• Utilized 5-point cubic spline interpolation to estimate segment Euler angles.
• Compared interpolated values against measured kinematic data across various lifting conditions.
• Performed sensitivity analysis to assess the impact of measurement error.

Main Results:

• Segment Euler angle trajectories showed a Root Mean Square Error (RMSE) below 5 degrees for most segments without measurement error.
• Increased measurement error led to a higher RMSE in estimated trajectories.
• Lifting from higher initial positions resulted in lower RMSE compared to low initial positions.

Conclusions:

• Cubic spline interpolation offers a robust method for estimating segment angular trajectories in asymmetric lifting.
• The accuracy of this method is highly dependent on minimizing measurement errors at interpolation points.