Motion-Based Ground Reaction Forces and Moments Prediction Method for Interaction With a Moving and/or Non-Horizontal...

Area of Science:

• Biomechanics
• Human Motion Analysis
• Applied Physics

Background:

• Inverse dynamics is crucial for biomechanical analysis but relies on external force data.
• Force platforms are limited in ecological validity; motion-based prediction offers a solution.
• Existing methods struggle with interactions involving moving or non-horizontal structures (MNHS).

Purpose of the Study:

• To evaluate the accuracy of an improved optimization-based method for predicting ground reaction forces and moments (GRF&Ms).
• To adapt GRF&Ms prediction for interactions with moving and/or non-horizontal structures (MNHS).
• To enhance contact detection for MNHS interactions in motion-based GRF&Ms prediction.

Main Methods:

• Developed and modified an optimization-based algorithm for GRF&Ms prediction.
• Implemented improved contact detection for moving and/or non-horizontal structures (MNHS).
• Collected motion capture and GRF&Ms data from 20 subjects performing squats and steps on an instrumented moving structure.

Main Results:

• The modified method demonstrated comparable accuracy to the original method.
• Root-mean-square errors (normalized by body mass) were within an acceptable range for all force and moment components.
• Specific errors: 0.14 N/kg (AP), 0.29 N/kg (ML), 0.61 N/kg (L); 0.06 Nm/kg (Frontal), 0.13 Nm/kg (Sagittal), 0.03 Nm/kg (Transverse).

Conclusions:

• The enhanced motion-based GRF&Ms prediction method is suitable for analyzing human motion on moving and/or non-horizontal structures (MNHS).
• This advancement allows for more ecologically valid biomechanical studies in complex environments.
• The improved contact detection is key to the method's success with MNHS.