Effect of various upper limb multibody models on soft tissue artefact correction: A case study.

Area of Science:

• Biomechanics
• Human Movement Analysis
• Orthopedics

Background:

• Soft tissue artifacts (STA) compromise joint kinematics accuracy using cutaneous markers, particularly for the scapula.
• Both segmental optimization and multibody kinematics optimization (MKO) are used to enhance kinematic estimates.
• MKO requires specific joint constraints, and its effectiveness for scapular kinematics is not well-established.

Purpose of the Study:

• To determine the optimal models for accurately estimating scapular kinematics.
• To compare segmental optimization and MKO algorithms for scapular motion analysis.
• To evaluate the impact of different scapulothoracic joint models within MKO.

Main Methods:

• Compared segmental optimization and 24-chain MKO models against intracortical pin-derived scapular kinematics in one participant.
• Utilized root mean square error (RMSE) on Cardan angles to quantify kinematic accuracy.
• Investigated four variations of the scapulothoracic joint model within MKO.

Main Results:

• Segmental optimization provided accurate scapula kinematics (RMSE: 1.1°–3.3°), even at high arm elevation.
• MKO models showed no significant difference compared to segmental optimization, except for a free scapulothoracic joint model (RMSE: 1.9°–9.6°).
• Overall MKO performance ranged from 0.9° to 4.1° RMSE across different models.

Conclusions:

• Segmental optimization is an accurate method for estimating scapula kinematics.
• MKO did not offer superior accuracy compared to segmental optimization for correcting soft tissue artifacts in scapular motion.
• The choice of scapulothoracic joint constraints significantly impacts MKO accuracy.