Immediate kinematic and muscle activity changes after a single robotic exoskeleton walking session post-stroke

ABSTRACT

Background: Robotic Exoskeletons (EKSO) are novel technology for retraining common gait dysfunction in people post-stroke. EKSO’s capability to influence gait characteristics post-stroke is unknown.

Objectives: To compare temporospatial, kinematic, and muscle activity gait characteristics before and after a single EKSO session and examine kinematic symmetry between involved and uninvolved limbs.

Methods: Participants post-stroke walked under two conditions: pre-EKSO, and immediately post-EKSO. A 10-camera motion capture system synchronized with 6 force plates was used to obtain temporospatial and kinematic gait characteristics from 5 walking trials of 9 meters at a self-selected speed. Surface EMG activity was obtained from bilateral gluteus medius, rectus femoris, medial hamstrings, tibialis anterior, and soleus muscles. Wilcoxon Signed Rank tests were used to analyze differences pre- and post-EKSO. Single EKSO session consisted of 22.3±6.8 minutes total time (walk time=7.2±1.5 minutes) with 250±40 steps.

Results: Six ambulatory (Functional Ambulation Category, range=4-5) adults (3 female; 44.7±14.6 years) with chronic stroke (4.5±1.9 years post-stroke) participated. No significant differences were observed for temporospatial gait characteristics. Muscle activity was significantly less post-EKSO in the involved leg rectus femoris during swing phase (p=0.028). Ankle dorsiflexion range of motion on the involved leg post-EKSO was significantly less during stance phase (p=0.046). Differences between involved and uninvolved joint range of motion symmetry were found pre-EKSO but not post-EKSO in swing phase hip flexion and stance phase knee flexion and knee extension.

Conclusions: EKSO training appears capable of altering gait in people with chronic stroke and a viable intervention to reduce gait dysfunction post-stroke.

KEYWORDS:

• Cerebrovascular disease
• robotics
• electromyography
• gait
• temporospatial
• mobility
• biomechanics

Acknowledgments

The authors wish to thank Anna Lovotti and Alyssa Breslin for their contributions in assisting with data collection. This study was partially funded by the Texas Woman’s University Research Enhancement Program.

Additional information

Funding

This work was supported by the Texas Woman’s University [Texas Woman’s University Research Enhancement Program].