The Analysis And Research Of The Gait Signal Based On The Detended Cross-Correlation Analysis And Multifractal Detrended Cross-Correlation Analysis

In modern society, the research of the gait analysis technology promotes the development ofother disciplines forward. Based on the different gait characteristics between different individuals, itcan achieve non-contact identification. In addition, in the medical research, doctors can diagnosethe diseases based on the correlation between two gait signals. The common diseases in modernsociety are the nervous and musculoskeletal system disease. These diseases may affect the ability ofwalk, and then generate abnormal gait. So making some analysis and research for the gait signal isvery helpful to detect the disease, to obtain the diagnosis result and to propose treatment options.And it plays active roles for the medical developing.Firstly, the thesis introduced a Detrended Cross-Correlation Analysis method. After processingthe gait signal with the least-squares linear fit and trend eliminating, it was proved that thecross-correlation existed between two non-stationary time series, and this cross-correlation waslong-standing and stably. It was also concluded that the cross-correlation between two gait signalgradually weakened with the growth of age and the changes in health status through comparing thecross-correlation index of gait signal of the young, old and Parkinson's.Secondly, the thesis introduced another method for researching gait signal. That is MultifractalDetrended Cross-Correlation Analysis. Using this method, it was proved that the gait signals havemultifractality through different viewpoints sand parameters. From the curve of Hurst index, thefunction of multifractal spectra and the curve of the Renyi index, it could get the the conclusion thatthe multifractal strength of old person's gait signal is strongest following by the Parkinson's gaitsignal, and the young persons'gait signal is the weakest.