A Closed-Loop Method to Identify EMG-Torque Dynamics in Human Balance Control.

Area of Science:

• Biomechanics
• Neuroscience
• Human Motor Control

Background:

• Human balance control involves complex interactions between neural activation and joint mechanics.
• Ankle torque modulation is crucial for maintaining upright posture.
• Existing methods struggle to independently quantify the contributions of neural drive and intrinsic joint properties to ankle torque.

Purpose of the Study:

• To develop and validate a novel closed-loop identification method for decomposing human ankle torque.
• To differentiate the contributions of central neural activation, stretch reflex, and intrinsic joint stiffness to ankle torque during balance control.
• To provide a robust method requiring only EMG measurements and minimal parameters.

Main Methods:

• A multiple-input, single-output, closed-loop identification technique was employed.
• Separate transfer functions were modeled for EMG-torque relationships representing central and stretch reflex mechanisms.
• Ankle intrinsic torque was estimated from the residuals of the model.
• The method was applied to perturbed standing data from healthy subjects using only EMG measurements.

Main Results:

• The novel method successfully decomposed ankle torque into its constituent components.
• Central and stretch reflex torques accounted for 80-93% of the total ankle torque variation.
• Intrinsic ankle joint stiffness explained the majority of the remaining torque.

Conclusions:

• The developed method effectively separates neural and mechanical contributions to human ankle torque.
• Neural activation (central and stretch reflex) is the primary driver of ankle torque in balance control.
• This technique offers a robust and parameter-efficient approach for analyzing human balance mechanisms.