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Quality in Sport

Application of Functional Data Analysis in Complex Human Movement Analysis
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Application of Functional Data Analysis in Complex Human Movement Analysis

Authors

  • Baifa Zhang School of Sports, Southwest University, Chongqing 400715, China https://orcid.org/0000-0002-6746-0066
  • Zhi-Cheng Lin School of Sports, Southwest University, Chongqing 400715, China

DOI:

https://doi.org/10.12775/QS.2025.40.60004

Keywords

Functional Data Analysis, Movement Analysis, Time series data

Abstract

Functional data analysis, pioneered by Ramsay, the president of the statistical society of Canada, is a novel statistical method widely applied in the field of human movement analysis. This study clarifies the relevant concepts and basic processes of functional data analysis, outlines the computational framework of functional principal component analysis, and focuses on exploring its applications in sports science, clinical rehabilitation, and motor development. Compared to traditional cross-sectional statistics, Functional data nalysis demonstrates unique advantages in human movement analysis research and is expected to become a reliable technical means for exploring the laws of human mechanical movement in the future.

References

BAUMGART C, HOPPE M W, FREIWALD J, 2017. Phase-Specific Ground Reaction Force Analyses of Bilateral and Unilateral Jumps in Patients With ACL Reconstruction [J]. Orthopaedic Journal of Sports Medicine, 5(6): 9.

COFFEY N, HARRISON A J, DONOGHUE O A, et al., 2011. Common functional principal components analysis: A new approach to analyzing human movement data [J]. Human Movement Science, 30(6): 1144-1166.

CRAVEN P, WAHBA G, 1979. SMOOTHING NOISY DATA WITH SPLINE FUNCTIONS - ESTIMATING THE CORRECT DEGREE OF SMOOTHING BY THE METHOD OF GENERALIZED CROSS-VALIDATION [J]. Numerische Mathematik, 31(4): 377-403.

DALLA BERNARDINA G R, DOS SANTOS M D M, RESENDE R A, et al., 2021. Asymmetric velocity profiles in Paralympic powerlifters performing at different exercise intensities are detected by functional data analysis [J]. Journal of Biomechanics, 123(5.

DANNENMAIER J, KALTENBACH C, KOLLE T, et al., 2020. Application of functional data analysis to explore movements: walking, running and jumping - A systematic review [J]. Gait & posture, 77(182-189.

DARIUSH B, 2003. Human motion analysis for biomechanics and biomedicine [J]. Machine Vision and Applications, 14(4): 202-205.

DAUXOIS J, POUSSE A, ROMAIN Y, 1982. Asymptotic theory for the principal component analysis of a vector random function: some applications to statistical inference [J]. Journal of Multivariate Analysis, 12(1): 136-154.

DONA G, PREATONI E, COBELLI C, et al., 2009. Application of functional principal component analysis in race walking: An emerging methodology [J]. Sports Biomechanics, 8(4): 284-301.

DONOGHUE O A, HARRISON A J, COFFEY N, et al., 2008. Functional data analysis of running kinematics in chronic Achilles tendon injury [J]. Medicine and science in sports and exercise, 40(7): 1323-1335.

DUHAMEL A, DEVOS P, BOURRIEZ J L, et al., 2006. Functional data analysis for gait curves study in Parkinson's disease [C] //Studies in Health Technology and Informatics.Univ Hamburg, Maastricht, NETHERLANDS:H. UNIV, I. EUROPEAN FEDERAT MED:569-+.

EILERS P H C, MARX B D, 1996. Flexible smoothing with B-splines and penalties [J]. Statistical Science, 11(2): 89-102.

HARRISON A J, RYAN W, HAYES K, 2007. Functional data analysis of joint coordination in the development of vertical jump performance [J]. Sports Biomechanics, 6(2): 199-214.

HEBERT-LOSIER K, PINI A, VANTINI S, et al., 2015. One-leg hop kinematics 20 years following anterior cruciate ligament rupture: Data revisited using functional data analysis [J]. Clinical Biomechanics, 30(10): 1153-1161.

KIPP K, REDDEN J, SABICK M B, et al., 2012. WEIGHTLIFTING PERFORMANCE IS RELATED TO KINEMATIC AND KINETIC PATTERNS OF THE HIP AND KNEE JOINTS [J]. Journal Of Strength And Conditioning Research, 26(7): 1838-1844.

KNEIP A, RAMSAY J O, 2008. Combining Registration and Fitting for Functional Models [J]. Journal of the American Statistical Association, 103(483): 1155-1165.

LANDRY S C, MCKEAN K A, HUBLEY-KOZEY C L, et al., 2007. Neuromuscular and lower limb biomechanical differences exist between male and female elite adolescent soccer players during an unanticipated run and crosscut maneuver [J]. American Journal of Sports Medicine, 35(11): 1901-1911.

LEROY A, MARC A, DUPAS O, et al., 2018. Functional Data Analysis in Sport Science: Example of Swimmers' Progression Curves Clustering [J]. Applied Sciences-Basel, 8(10): 18.

LIEBL D, WILLWACHER S, HAMILL J, et al., 2014. Ankle plantarflexion strength in rearfoot and forefoot runners: A novel clusteranalytic approach [J]. Human Movement Science, 35(104-120.

RAMSAY J, HOOKER G, GRAVES S, 2009. Functional Data Analysis with R and MATLAB [M]. Springer New York.

RAMSAY J O, 1982. WHEN THE DATA ARE FUNCTIONS [J]. Psychometrika, 47(4): 379-396.

RAMSAY J O, WANG X, FLANAGAN R, 1995. A FUNCTIONAL DATA-ANALYSIS OF THE PINCH FORCE OF HUMAN FINGERS [J]. Applied Statistics-Journal of the Royal Statistical Society Series C, 44(1): 17-30.

RICHTER C, O׳CONNOR N E, MARSHALL B, et al., 2014. Comparison of discrete-point vs. dimensionality-reduction techniques for describing performance-related aspects of maximal vertical jumping [J]. Journal of Biomechanics, 47(12): 3012-3017.

RYAN W, HARRISON A, HAYES K, 2006. Functional data analysis of knee joint kinematics in the vertical jump [J]. Sports Biomechanics, 5(1): 121-138.

SOARES J D, CARPES F P, GERALDO G D, et al., 2021. Functional data analysis reveals asymmetrical crank torque during cycling performed at different exercise intensities [J]. Journal of Biomechanics, 122(5.

SON S J, KIM H, SEELEY M K, et al., 2017a. Efficacy of Sensory Transcutaneous Electrical Nerve Stimulation on Perceived Pain and Gait Patterns in Individuals With Experimental Knee Pain [J]. Archives Of Physical Medicine And Rehabilitation, 98(1): 25-35.

SON S J, KIM H, SEELEY M K, et al., 2017b. Movement Strategies among Groups of Chronic Ankle Instability, Coper, and Control [J]. Medicine and science in sports and exercise, 49(8): 1649-1661.

STEPHENS J M, CHAPMAN D W, TATE K, et al., 2020. A drop landing screening approach to monitor an individual using functional data analysis: An ACL injury case study [J]. Journal Of Science And Medicine In Sport, 23(3): 241-245.

TUDDENHAM R D, SNYDER M M, 1954. Physical growth of California boys and girls from birth to eighteen years [J]. Publications in child development. University of California, Berkeley, 1(2): 183-364.

ULLAH S, FINCH C F, 2013. Applications of functional data analysis: A systematic review [J]. BMC Medical Research Methodology, 43(13): 1-12.

WARMENHOVEN J, COBLEY S, DRAPER C, et al., 2017. Assessment of propulsive pin force and oar angle time-series using functional data analysis in on-water rowing [J]. Scandinavian Journal Of Medicine & Science In Sports, 27(12): 1688-1696.

WARMENHOVEN J, SMITH R, DRAPER C, et al., 2018a. Force coordination strategies in on-water single sculling: Are asymmetries related to better rowing performance? [J]. Scandinavian Journal Of Medicine & Science In Sports, 28(4): 1379-1388.

WARMENHOVEN J, HARRISON A, ROBINSON M A, et al., 2018b. A force profile analysis comparison between functional data analysis, statistical parametric mapping and statistical non-parametric mapping in on-water single sculling [J]. Journal Of Science And Medicine In Sport, 21(10): 1100-1105.

WARMENHOVEN J, COBLEY S, DRAPER C, et al., 2018c. How gender and boat-side affect shape characteristics of force-angle profiles in single sculling: Insights from functional data analysis [J]. Journal Of Science And Medicine In Sport, 21(5): 533-537.

WARMENHOVEN J, COBLEY S, DRAPER C, et al., 2019a. Bivariate functional principal components analysis: considerations for use with multivariate movement signatures in sports biomechanics [J]. Sports Biomechanics, 18(1): 10-27.

WARMENHOVEN J, COBLEY S, DRAPER C, et al., 2019b. Considerations for the use of functional principal components analysis in sports biomechanics: examples from on-water rowing [J]. Sports Biomechanics, 18(3): 317-341.

WARMENHOVEN J, BARGARY N, LIEBL D, et al., 2021. PCA of waveforms and functional PCA: A primer for biomechanics [J]. Journal of Biomechanics, 116(6.

WILLWACHER S, GOETZE I, FISCHER K M, et al., 2016. The free moment in running and its relation to joint loading and injury risk [J]. 8(1): 1-11.

WRIGLEY A T, ALBERT W J, DELUZIO K J, et al., 2005. Differentiating lifting technique between those who develop low back pain and those who do not [J]. Clinical Biomechanics, 20(3): 254-263.

ZIN M A M, RAMBELY A S, ARIFF N M, et al., 2020. Smoothing and Differentiation of Kinematic Data Using Functional Data Analysis Approach: An Application of Automatic and Subjective Methods [J]. Applied Sciences-Basel, 10(7): 18

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Published

2025-04-30

How to Cite

1.
ZHANG, Baifa and LIN, Zhi-Cheng. Application of Functional Data Analysis in Complex Human Movement Analysis. Quality in Sport. Online. 30 April 2025. Vol. 40, p. 60004. [Accessed 8 July 2025]. DOI 10.12775/QS.2025.40.60004.
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Issue

Vol. 40 (2025)

Section

Health Sciences

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Copyright (c) 2025 Baifa Zhang, Zhi-Cheng Lin

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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

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