title: [Detrended cross-correlation analysis: a new method for gait signal analysis].
abstract: The cross-correlation of gait signal can mirror the health situations of different people. It is important to analyze the long-range cross correlations of the two signals of nonstationarity for medical research. In this paper, we propose a detrended cross-correlation analysis (DCCA) method for analyzing the different gait signal in physiological and pathological conditions. Our work dealt with three kinds of gait signals, including those of normal young people (23 to 29 years of age), those of healthy old people (71 to 77 years of age) and those of the old people (60 to 77 years of age) with Parkinson's disease from the MIT-BIH database. We carried out the DCCA for the three gait signals of nonstationarity. The results showed that the self-similarity of gait signal got more unstable with the age increasing and health status worsening. From the cross-correlation analysis, we found that the cross-correlation degree of gait signal of young people increased gradually, the healthy old people changed slowly and the Parkinson's disease patients showed unstable changes. We can make medical diagnosis and treatment according to the differences among different gait signals.
authors.affiliation: Image Processing and Image Communications Key Lab, Nanjing University of Posts & Telecomm, Nanjing 210003, China.
authors.forename: Pingping
authors.initials: P
authors.lastname: Wang
authors.forename: Jun
authors.initials: J
authors.lastname: Wang
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D003627:Data Interpretation, Statistical; D005684:Gait / Q000502:physiology*; D020233:Gait Disorders, Neurologic / Q000503:physiopathology*; D006801:Humans; D016014:Linear Models; D008875:Middle Aged; D010300:Parkinson Disease / Q000503:physiopathology; D055815:Young Adult