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Refining nonlinear parameters for evaluating gait stability in subjects with various musculoskeletal disorders: A
Kristóf Bányi1, Zsófia Pálya1, Mária Takács2
1Budapest University of Technology and Economics, Faculty of Mechanical Engineering, Műegyetem rkp. 3, Budapest, 1111, Hungary.
Objective:
Gait stability is vital in musculoskeletal health, directly influencing quality of life. Nonlinear metrics such as entropy and fractal dimension enhance understanding of gait stability beyond traditional measures, thus improving diagnostic and physical therapy assessments. The present study aimed to determine which input variable values influence approximate entropy (ApEn), sample entropy (SampEn), and Higuchi's fractal dimension (HFD) parameters effective in evaluating the stability of various individuals.
Methods:
Eighty-one participants (ages 14-84, body mass 43-124 kg, heights 149-189 cm) performed self-paced walking trials on an instrumented treadmill; ten were healthy and 71 had spinal or lower limb orthopaedic issues. The recorded ground reaction force data enabled the calculation of centre of pressure (CoP) coordinates during the recorded time interval. The parameters were tuned for nonlinear analysis by iterating the inputs and identifying stable regions in their respective graphs.
Results:
For the entropy metrics, the embedding dimension and the time delay variables were determined via Average Mutual Information and False Nearest Neighbour methods, with tolerance radii tuned in a range of 2%-100% of the data series' standard deviation (SD). Optimal ApEn values calculated from the CoP coordinates were obtained at a radius of 20% of the SD in the anteroposterior and 15% of the SD in the mediolateral direction, while optimal values for SampEn were 20% and 10%, respectively. The HFD tuning factor, examined between 4-200, yielded plateaued fractal dimension values after 60 in the anteroposterior and 120 in the mediolateral directions.
Conclusion:
These improvements in gait differentiation highlight that optimising nonlinear metric parameters is crucial to producing robust, clinically interpretable indicators of gait stability.
