Joint behaviour during arm swing changes with gait speed and predicts spatiotemporal variability and dynamic stability in healthy young adults

• Published in: Gait & posture Vol. 103; pp. 50 - 56
• Main Authors: Bailey, Christopher A., Graham, Ryan B., Nantel, Julie
• Format: Journal Article
• Language: English
• Published: England Elsevier B.V 01.06.2023
• Subjects: Arm; Arm swing; Biomechanical Phenomena; Dynamic stability; Female; Gait; Humans; Motor variability; Upper Extremity; Upper limb; Walking; Walking Speed; Young Adult; Motor variability; Upper limb; Gait; Arm swing; Dynamic stability
• ISSN: 0966-6362; 1879-2219
• DOI: 10.1016/j.gaitpost.2023.04.016

Arm swing is linked to gait stability. How this is accomplished is unclear as most investigations artificially manipulate arm swing amplitude and examine average patterns. Biomechanical evaluation of stride-to-stride upper limb behaviour across a range of gait speeds, where the arm swings as preferred, could clarify this link. How do stride-to-stride arm swing behaviours change with gait speed and relate to stride-to-stride gait fluctuations? Young adults (n = 45, 25 females) completed treadmill gait at preferred, slow (70% of preferred), and fast speed (130% of preferred) while full-body kinematics were acquired with optoelectronic motion capture. Arm swing behaviour was quantified by shoulder, elbow, and wrist joint angle amplitude (range of motion [ROM]) and motor variability (e.g. mean standard deviation [meanSD], local divergence exponent [λmax]). Stride-to-stride gait fluctuation was quantified by spatiotemporal variability (e.g. stride time CV) and dynamic stability (i.e. trunk local dynamic stability [trunk λmax], centre-of-mass smoothness [COM HR]). Repeated measures ANOVAs tested for speed effects and step-wise linear regressions identified arm swing-based predictors of stride-to-stride gait fluctuation. Speed decreased spatiotemporal variability and increased trunk λmax and COM HR in the anteroposterior and vertical axes. Adjustments in gait fluctuations occurred with increased upper limb ROM, particularly for elbow flexion, and increased meanSD and λmax of shoulder, elbow, and wrist angles. Models of upper limb measures predicted 49.9–55.5% of spatiotemporal variability and 17.7–46.4% of dynamic stability. For dynamic stability, wrist angle features were the best and most common independent predictors. Findings highlight that all upper limb joints, and not solely the shoulder, underlie changes in arm swing amplitude, and that arm swing strategies pair with the trunk and contrast with centre-of-mass and stride strategies. Findings suggest that young adults search for flexible arm swing motor strategies to help optimize stride consistency and gait smoothness. •Elbow flexion contributed most to changes in arm swing amplitude.•Upper limb joint variability and dynamic instability increased at faster gait speed.•Upper limb joint behaviour predicted 50–56% of spatiotemporal variability.•Upper limb joint behaviour predicted 18–46% of dynamic stability.•Young adults may search for flexible arm swing strategies to optimize their stride.