Is the Limit-Cycle-Attractor an (almost) Invariable Characteristic in Human Walking?

Background: Common methods of gait analyses measure step length/width, gait velocity and gait variability to name just a few. Those parameters tend to be changing with fitness and skill of the subjects. But, do stable subject characteristic parameters in walking exist? Does the Limit-Cycle-Attractor qualify as such a parameter?.

Research Question: The attractor method is a new approach focusing on the dynamics of human motion. It classifies the fundamental walking pattern by calculating the Limit-Cycle-Attractor and its variability from acceleration data of the feet. Our hypothesis is that the fundamental walking pattern in healthy controls and in people with Multiple Sclerosis (pwMS) is stable, but can be altered through acute interventions or rehabilitation.

Methods: For this purpose, two investigations were conducted involving 113 subjects. The short-term stability was tested pre and post a 15 min passive/active MOTOmed (ergometer) session as well as up to 20 min afterwards. The long-term stability was tested over five weeks of rehabilitation once a week in pwMS. The main parameter of interest describes the velocity normalized average difference between two attractors (δM), which is an indicator for the change in movement pattern.

Results: The Friedman's two-way ANOVA by ranks did not reveal any significant difference in δM. However, the conventional walking tests (6 min.10 m) improved significantly (p < 0.05) during rehabilitation. Contrary to our original hypothesis, the fundamental walking pattern was highly stable against controlled motor-assisted movement initiation via MOTOmed and rehabilitation treatment. Movement characteristics appeared to be independent of the improved fitness as indicated by the enhanced walking speed and distance.

Significance: The individual Limit-Cycle-Attractor is extremely robust and might indeed qualify as an (almost) invariable characteristic in human walking. This opens up the possibility to encode the individual walking characteristics. Conditions as Parkinson, Multiple Sclerosis etc., might display disease specific distinctions via the Limit-Cycle-Attractor.