Paper Info
Title
Neighborhood coarse graining based Lempel-Ziv complexity for analysis on center of pressure
Abstract
Center of pressure (COP) has been long used to investigate standing postural control. However, there is still lack of COP measures which can give information about how well controlled the standing posture is. This paper presents a novel Lempel-Ziv complexity (LZC) measure for COP. The classical Lempel-Ziv complexity is improved with neighborhood coarse graining to fit it for analyzing two-dimensional COP trajectory as a whole. The proposed neighborhood coarse graining based Lempel-Ziv complexity (NGLZC) was evaluated by monitoring changes of standing postural sway complexity induced by visual input. The results reflected that COP NGLZC values in three kinds of visual input conditions showed consistent pattern across subjects, whereas the LZC values of COP medial-lateral component and the anterior-posterior component reflected no meaningful pattern. Furthermore, it was found that a statistically significant effect for the visual input factor on COP NGLZC (ANOVA: P <; 0.001). Hence, the COP NGLZC can be used as a good indicator of standing postural control.
Year
DOI
Venue
2016
10.1109/BioCAS.2016.7833760
2016 IEEE Biomedical Circuits and Systems Conference (BioCAS)
Keywords
Field
DocType
postural sway,center of pressure,complexity
Computer vision,Simulation,Computer science,Balance (ability),Algorithm,Lempel-Ziv complexity,Postural control,Center of pressure (fluid mechanics),Artificial intelligence,Granularity,Trajectory
Conference
ISSN
ISBN
Citations 
2163-4025
978-1-5090-2960-0
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Yao Sun117938.32
Wei Wei248069.55
Zhizeng Luo34911.65
Zhongming Ji400.34