Gait Influence Diagrams in Parkinson's Disease
Por:
Ren, Peng, Karahan, Esin, Chen, Chao, Luo, Ruixue, Geng, Yayuan, Bosch Bayard, Jorge Francisco, Bringas, Maria L., Yao, Dezhong, Kendrick, Keith M., Valdes-Sosa, Pedro A.
Publicada:
1 ago 2017
Resumen:
Previous studies have shown that gait patterns differ between
Parkinson's disease (PD) patients and controls. However, almost all
these studies focused only on univariate time series of a single
variable. This approach cannot reveal detailed information of foot
loading dynamics and the cooperative relationships of different
anatomical plantar foot areas when the subjects walk. By contrast, we
propose a novel multivariate method for analyzing gait patterns of the
PD patients: Gait Influence Diagrams (GIDs). These are constructed by
analyzing theWiener-Akaike-Granger-Schweder influences between vertical
ground reaction force signals at different plantar areas of both feet.
In this paper, we use the particular case of WAGS influence measures
known as ``extended Granger causality analysis''. GIDs are directed
graphs, with arrows indicating those influences that are significantly
different between PD patients and healthy subjects. We confirm prior
clinical observations that Parkinsonian gait differs significantly from
the healthy one in the anterior-posterior movement direction. A new
finding is that there are also pathological changes in the
lateral-medial direction. Importantly, gait asymmetry for the PD
patients is clearly evident in GIDs, even in earlier stages of the
disease. These results suggest that GID might be of use in future PD
gait pattern studies.
Filiaciones:
Ren, Peng:
Univ Elect Sci & Technol China, Key Lab NeuroInformat, Minist Educ, Ctr Informat Biomed, Chengdu 610054, Sichuan, Peoples R China
Karahan, Esin:
Univ Elect Sci & Technol China, Key Lab NeuroInformat, Minist Educ, Ctr Informat Biomed, Chengdu 610054, Sichuan, Peoples R China
Chen, Chao:
Univ Elect Sci & Technol China, Key Lab NeuroInformat, Minist Educ, Ctr Informat Biomed, Chengdu 610054, Sichuan, Peoples R China
Luo, Ruixue:
Univ Elect Sci & Technol China, Key Lab NeuroInformat, Minist Educ, Ctr Informat Biomed, Chengdu 610054, Sichuan, Peoples R China
Geng, Yayuan:
Univ Elect Sci & Technol China, Key Lab NeuroInformat, Minist Educ, Ctr Informat Biomed, Chengdu 610054, Sichuan, Peoples R China
Bosch Bayard, Jorge Francisco:
Univ Nacl Autonoma Mexico, Inst Neurobiol, Queretaro 76230, Mexico
Bringas, Maria L.:
Univ Elect Sci & Technol China, Key Lab NeuroInformat, Minist Educ, Ctr Informat Biomed, Chengdu 610054, Sichuan, Peoples R China
Yao, Dezhong:
Univ Elect Sci & Technol China, Key Lab NeuroInformat, Minist Educ, Ctr Informat Biomed, Chengdu 610054, Sichuan, Peoples R China
Kendrick, Keith M.:
Univ Elect Sci & Technol China, Key Lab NeuroInformat, Minist Educ, Ctr Informat Biomed, Chengdu 610054, Sichuan, Peoples R China
Valdes-Sosa, Pedro A.:
Univ Elect Sci & Technol China, Key Lab NeuroInformat, Minist Educ, Ctr Informat Biomed, Chengdu 610054, Sichuan, Peoples R China
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