Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach

Journal Title: Journal of Human Kinetics - Year 2017, Vol 60, Issue 6

Abstract

In human motion studies, discrete points such as peak or average kinematic values are commonly selected to test hypotheses. The purpose of this study was to describe a functional data analysis and describe the advantages of using functional data analyses when compared with a traditional analysis of variance (ANOVA) approach. Nineteen healthy participants (age: 22 ± 2 yrs, body height: 1.7 ± 0.1 m, body mass: 73 ± 16 kg) walked under two different conditions: control and pain+effusion. Pain+effusion was induced by injection of sterile saline into the joint capsule and hypertonic saline into the infrapatellar fat pad. Sagittal-plane ankle, knee, and hip joint kinematics were recorded and compared following injections using 2×2 mixed model ANOVAs and FANOVAs. The results of ANOVAs detected a condition × time interaction for the peak ankle (F1,18 = 8.56, p = 0.01) and hip joint angle (F1,18 = 5.77, p = 0.03), but did not for the knee joint angle (F1,18 = 0.36, p = 0.56). The functional data analysis, however, found several differences at initial contact (ankle and knee joint), in the mid-stance (each joint) and at toe off (ankle). Although a traditional ANOVA is often appropriate for discrete or summary data, in biomechanical applications, the functional data analysis could be a beneficial alternative. When using the functional data analysis approach, a researcher can (1) evaluate the entire data as a function, and (2) detect the location and magnitude of differences within the evaluated function.

Authors and Affiliations

Jihong Park, Matthew K. Seeley, Devin Francom, C. Shane Reese, J. Ty Hopkins

Keywords

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  • EP ID EP239945
  • DOI 10.1515/hukin‐2017‐0114
  • Views 133
  • Downloads 0

How To Cite

Jihong Park, Matthew K. Seeley, Devin Francom, C. Shane Reese, J. Ty Hopkins (2017). Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach. Journal of Human Kinetics, 60(6), 39-49. https://www.europub.co.uk/articles/-A-239945