Sensorimotor Time Delay Estimation by EMG Signal Processing in People Living with Spinal Cord Injury

Area of Science:

• Biomechanics
• Neuroscience
• Rehabilitation Engineering

Background:

• Neuro mechanical time delays are inherent in sensorimotor control, impacting body stabilization and increasing fall risk.
• Understanding these delays is crucial for individuals with spinal cord injury (SCI) to inform rehabilitation strategies and assistive technology development.
• Estimating muscle activation onset is key to quantifying these time delays in SCI populations.

Purpose of the Study:

• To estimate muscle onset activation in individuals with complete SCI using four distinct signal processing strategies.
• To compare the efficacy of time-domain (filtering, TKEO) and time-frequency domain (cepstral analysis, power spectrum) methods for onset detection.
• To investigate the relationship between muscle activation sequences, estimated time delays, and postural stability in SCI.

Main Methods:

• EMG data from eight upper limb muscles were collected from seven complete SCI participants during seated balance tasks with mechanical perturbation.
• Four strategies were employed: simple filtering, TEO (Temporal Teager-Kaiser Energy Operator), cepstral analysis, and power spectrum analysis.
• Muscle onset activation was estimated using these time and time-frequency domain techniques.

Main Results:

• The TKEO technique demonstrated superior artifact removal (ECG, motion) compared to simple filtering but both failed in several trials.
• Time-frequency methods (cepstral analysis, power spectrum) yielded longer muscle activation onsets, potentially reflecting lower-frequency stabilization movements.
• No significant correlation was found between muscle activation sequence, estimated delay values, and individual stabilization strategies due to motion redundancy.

Conclusions:

• Time-frequency analysis methods are more robust for estimating muscle onset in SCI individuals compared to simple time-domain filtering.
• The estimated time delays provide valuable data for developing sophisticated sensorimotor control models.
• Findings can guide therapists and biomechanics in designing personalized rehabilitation programs and stability-focused assistive technologies for SCI patients.