Paper Info
Title
Quantifying Chaotic Behavior In Treadmill Walking
Abstract
The authors describe an example of application of nonlinear time series analysis directed at identifying the presence of deterministic chaos in human motion data by means of the largest Lyapunov exponent (LLE). The research aimed at determination of the influence of gait speed on the LLE value with a view to verification of the belief that slower walking leads to increased stability characterized by smaller LLE value. Analyses were focused on the time series representing hip flexion/extension angle, knee flexion/extension angle and dorsiflexion/plantarflexion dimension of the ankle. Gait sequences were recorded in the Human Motion Laboratory (HML) of the Polish-Japanese Academy of Information Technology in Bytom by means of the Vicon system. Application of the AC5000M treadmill allowed recordings in three variants: at the preferred walking speed (PWS) of each subject, at 80% of the PWS and at 120% of the PWS. According to the recommendations from the literature the LLE value was estimated twice for every time series: as the short-term LLE1 for the first stride and as the long-term LLE4-10 over a fixed interval between the fourth and the tenth stride. In the latter case it was confirmed that the LLE value increases with walking speed for both limbs.
Year
DOI
Venue
2015
10.1007/978-3-319-15705-4_31
INTELLIGENT INFORMATION AND DATABASE SYSTEMS, PT II
Keywords
Field
DocType
Nonlinear time series analysis, Phase space reconstruction, Deterministic chaos, Human motion analysis
Gait,STRIDE,Computer science,Artificial intelligence,Treadmill,Physical medicine and rehabilitation,Nonlinear time series analysis,Chaotic,Lyapunov exponent,Ankle,Machine learning,Preferred walking speed
Conference
Volume
ISSN
Citations 
9012
0302-9743
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Henryk Josinski14811.48
Agnieszka Michalczuk2204.78
Adam Świtoński3349.12
Romualda Mucha400.68
Konrad W. Wojciechowski522932.71