Local state space temporal fluctuations: a methodology to reveal changes during a fatiguing repetitive task

Area of Science:

• Biomechanics
• Sport Sciences
• Motor Control

Background:

• Muscular fatigue impacts motor performance, including kinematics and kinetics.
• Quantifying fatigue-related kinematic changes using joint angles is valuable in biomechanics and sports science.
• Existing methods may not fully capture the dynamic adaptation patterns during fatiguing tasks.

Purpose of the Study:

• Introduce a novel approach to extract kinematic changes from 2D phase portraits.
• Investigate fatigue adaptation patterns in repetitive elbow movements.
• Assess the influence of load and repetition rate on temporal kinematic changes.

Main Methods:

• Utilized 2D phase portraits to analyze kinematic changes during repetitive elbow movements.
• Employed the local flow variation concept to track trajectory shifts in the state space.
• Measured temporal kinematic changes and assessed complexity using permutation entropy.

Main Results:

• Higher loads resulted in significantly more complex kinematic changes (p=0.014).
• Repetition rates did not show a significant effect on kinematic complexity (p=0.583).
• The proposed method identified new features for quantifying kinematic complexity from phase portraits.

Conclusions:

• The novel phase portrait method effectively captures temporal kinematic changes due to muscular fatigue.
• This approach allows for qualitative and quantitative assessment of fatigue adaptation.
• Task conditions, specifically load, significantly influence the complexity of kinematic changes during fatiguing tasks.