Literature DB >> 17892096

Functional data analysis of joint coordination in the development of vertical jump performance.

A J Harrison1, W Ryan, K Hayes.   

Abstract

Mastery of complex motor skills requires effective development of inter-segment coordination patterns. These coordination patterns can be described and quantified using various methods, including descriptive angle-angle diagrams, conjugate cross-correlations, vector coding, normalized root mean squared error techniques and, as in this study, functional data analysis procedures. Lower limb kinematic data were obtained for 49 children performing the vertical jump. Participants were assigned to developmental stages using the criteria of Gallahue and Ozmun . Inter-segment joint coordination data consisting of pairs of joint angle-time data were smoothed using B-splines and the resulting bivariate functions were analysed using functional principal component analysis and stepwise discriminant analysis. The results of the analysis showed that the knee-hip joint coordination pattern was most effective at discriminating between developmental stages. The results provide support for the application of functional data analysis techniques in the analysis of joint coordination or time series type data.

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Year:  2007        PMID: 17892096     DOI: 10.1080/14763140701323042

Source DB:  PubMed          Journal:  Sports Biomech        ISSN: 1476-3141            Impact factor:   2.832


  8 in total

1.  A Proposed Framework to Describe Movement Variability within Sporting Tasks: A Scoping Review.

Authors:  Jake Cowin; Sophia Nimphius; James Fell; Peter Culhane; Matthew Schmidt
Journal:  Sports Med Open       Date:  2022-06-27

2.  Effects of acute wearable resistance loading on overground running lower body kinematics.

Authors:  Karl M Trounson; Aglaja Busch; Neil French Collier; Sam Robertson
Journal:  PLoS One       Date:  2020-12-28       Impact factor: 3.240

3.  Biomechanical Characteristics of Vertical Jumping of Preschool Children in China Based on Motion Capture and Simulation Modeling.

Authors:  Panchao Zhao; Zhongqiu Ji; Ruixiang Wen; Jiahui Li; Xiao Liang; Guiping Jiang
Journal:  Sensors (Basel)       Date:  2021-12-15       Impact factor: 3.576

4.  Determining jumping performance from a single body-worn accelerometer using machine learning.

Authors:  Mark G E White; Neil E Bezodis; Jonathon Neville; Huw Summers; Paul Rees
Journal:  PLoS One       Date:  2022-02-10       Impact factor: 3.240

Review 5.  Applications of functional data analysis: A systematic review.

Authors:  Shahid Ullah; Caroline F Finch
Journal:  BMC Med Res Methodol       Date:  2013-03-19       Impact factor: 4.615

6.  Functional principal component analysis as a new methodology for the analysis of the impact of two rehabilitation protocols in functional recovery after stroke.

Authors:  M Luz Sánchez-Sánchez; Juan-Manuel Belda-Lois; Silvia Mena-del Horno; Enrique Viosca-Herrero; Beatriz Gisbert-Morant; Celedonia Igual-Camacho; Ignacio Bermejo-Bosch
Journal:  J Neuroeng Rehabil       Date:  2014-09-10       Impact factor: 4.262

7.  Cellists' sound quality is shaped by their primary postural behavior.

Authors:  Jocelyn Rozé; Mitsuko Aramaki; Richard Kronland-Martinet; Sølvi Ystad
Journal:  Sci Rep       Date:  2020-08-17       Impact factor: 4.379

8.  Children's Single-Leg Landing Movement Capability Analysis According to the Type of Sport Practiced.

Authors:  Isaac Estevan; Gonzalo Monfort-Torres; Roman Farana; David Zahradnik; Daniel Jandacka; Xavier García-Massó
Journal:  Int J Environ Res Public Health       Date:  2020-09-03       Impact factor: 3.390

  8 in total

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