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中文
Yunfeng Wu

Associate professor

Supervisor of Master's Candidates


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Date of Employment:2009-12-14

School/Department:信息学院

Education Level:博士研究生毕业

Business Address:厦门大学翔安校区西部片区6号楼(睿信楼)202室

Gender:Male

Contact Information:yunfengwu@xmu.edu.cn

Degree:Doctor of Engineering (D.Eng.)

Status:在职

Alma Mater:北京邮电大学

Discipline:生物医学工程
信号与信息处理

Academic Honor:

2013   Outstanding talents in the new century

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Statistical analysis of gait maturation in children using nonparametric probability density function modeling

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DOI number:10.3390/e15030753

Journal:Entropy

Abstract:Analysis of gait dynamics in children may help understand the development of neuromuscular control and maturation of locomotor function. This paper applied the nonparametric Parzen-window estimation method to establish the probability density function (PDF) models for the stride interval time series of 50 children (25 boys and 25 girls). Four statistical parameters, in terms of averaged stride interval (ASI), variation of stride interval (VSI), PDF skewness (SK), and PDF kurtosis (KU), were computed with the Parzen-window PDFs to study the maturation of stride interval in children. By analyzing the results of the children in three age groups (aged 3-5 years, 6-8 years, and 10-14 years), we summarize the key findings of the present study as follows. (1) The gait cycle duration, in terms of ASI, increases until 14 years of age. On the other hand, the gait variability, in terms of VSI, decreases rapidly until 8 years of age, and then continues to decrease at a slower rate. (2) The SK values of both the histograms and Parzen-window PDFs for all of the three age groups are positive, which indicates an imbalance in the stride interval distribution within an age group. However, such an imbalance would be meliorated when the children grow up. (3) The KU values of both the histograms and Parzen-window PDFs decrease with the body growth in children, which suggests that the musculoskeletal growth enables the children to modulate a gait cadence with ease. (4) The SK and KU results also demonstrate the superiority of the Parzen-window PDF estimation method to the Gaussian distribution modeling, for the study of gait maturation in children.

Co-author:Suxian Cai,Shanshan Yang,Zhangting Zhong,Fang Zheng,Jia He

First Author:Ning Xiang

Indexed by:Article

Correspondence Author:Yunfeng Wu*

Volume:15

Issue:3

Page Number:753-766

Translation or Not:no

Date of Publication:2013-02-25

Included Journals:SCI

Links to published journals:https://doi.org/10.3390/e15030753