Biomarkers for rhythmic and discrete dynamic primitives in locomotion

Area of Science:

• Neuroscience
• Biomechanics
• Rehabilitation Science

Background:

• Central nervous system injuries impair motor control, necessitating effective rehabilitation.
• Motor control is theorized to rely on dynamic primitives like submovements and oscillations.
• Therapies targeting these primitives may enhance motor recovery after neurological damage.

Purpose of the Study:

• To introduce two novel biomarkers for evaluating rhythmic and discrete movements in gait.
• To assess the efficacy of these biomarkers in quantifying motor control during various walking conditions.

Main Methods:

• Development of the mean-squared jerk ratio (MSJR) to measure gait rhythmicity.
• Development of the discrete Principal Component Analysis (dPCA) to detect discrete movements.
• Application of biomarkers to kinematic data from healthy individuals under diverse walking conditions (speed variations, terrain changes, sidesteps).

Main Results:

• MSJR decreased with increasing speed, indicating enhanced gait rhythmicity, even with imposed ankle stiffness.
• Rhythmicity, as measured by MSJR, remained robust despite terrain perturbations.
• dPCA effectively identified discrete sidesteps within rhythmic walking patterns.

Conclusions:

• The proposed MSJR and dPCA biomarkers accurately quantify rhythmic and discrete gait movements.
• These biomarkers show potential for improving clinical assessment and guiding rehabilitation strategies for neurological patients.
• Objective measurement of motor control primitives can advance understanding and treatment of gait impairments.