Comprehensive quantitative investigation of arm swing during walking at various speed and surface slope conditions.

Previous studies have shown that inclusion of arm swing in gait rehabilitation leads to more effective walking recovery in patients with walking impairments. However, little is known about the correct arm-swing trajectories to be used in gait rehabilitation given the fact that changes in walking conditions affect arm-swing patterns. In this paper we present a comprehensive look at the effects of a variety of conditions on arm-swing patterns during walking. The results describe the effects of surface slope, walking speed, and physical characteristics on arm-swing patterns in healthy individuals. We propose data-driven mathematical models to describe arm-swing trajectories. Thirty individuals (fifteen females and fifteen males) with a wide range of height (1.58-1.91m) and body mass (49-98kg), participated in our study. Based on their self-selected walking speed, each participant performed walking trials with four speeds on five surface slopes while their whole-body kinematics were recorded. Statistical analysis showed that walking speed, surface slope, and height were the major factors influencing arm swing during locomotion. The results demonstrate that data-driven models can successfully describe arm-swing trajectories for normal gait under varying walking conditions. The findings also provide insight into the behavior of the elbow during walking.