Refining nonlinear parameters for evaluating gait stability in subjects with various musculoskeletal disorders: A...

Area of Science:

• Biomechanics and Motor Control
• Nonlinear Dynamics
• Musculoskeletal Health Assessment

Background:

• Gait stability is crucial for musculoskeletal health and quality of life.
• Traditional gait measures have limitations.
• Nonlinear metrics like entropy and fractal dimension offer enhanced insights.

Purpose of the Study:

• To determine optimal input variable values for nonlinear gait stability metrics.
• To investigate parameters influencing approximate entropy (ApEn), sample entropy (SampEn), and Higuchi's fractal dimension (HFD).

Main Methods:

• Eighty-one participants (14-84 years) with diverse musculoskeletal conditions performed treadmill walking.
• Ground reaction force data were used to calculate center of pressure (CoP) coordinates.
• Nonlinear analysis parameters were tuned by iterating inputs to find stable regions.

Main Results:

• Optimal ApEn parameters were identified at 20% (anteroposterior) and 15% (mediolateral) of standard deviation (SD).
• Optimal SampEn parameters were found at 20% (anteroposterior) and 10% (mediolateral) of SD.
• Higuchi's fractal dimension (HFD) plateaued after 60 (anteroposterior) and 120 (mediolateral) tuning factor values.

Conclusions:

• Optimizing nonlinear metric parameters is essential for accurate gait stability assessment.
• This study provides specific parameter recommendations for ApEn, SampEn, and HFD.
• Improved gait differentiation through optimized parameters leads to robust clinical indicators.