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

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, inmore » biomechanical applications, the functional data analysis could be a beneficial alternative. Thus 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.« less

Authors:
 [1];  [2]; ORCiD logo [3];  [4];  [2]
  1. Kyung Hee Univ., Gyeonggi (Korea). Dept. of Sports Medicine
  2. Brigham Young Univ., Provo, UT (United States). Dept. of Exercise Sciences
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  4. Brigham Young Univ., Provo, UT (United States). Dept. of Statistics
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1441331
Report Number(s):
LA-UR-18-20243
Journal ID: ISSN 1899-7562
Grant/Contract Number:
AC52-06NA25396
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Journal of Human Kinetics
Additional Journal Information:
Journal Volume: 60; Journal Issue: 1; Journal ID: ISSN 1899-7562
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 97 MATHEMATICS AND COMPUTING; functional data analysis; statistics; joint kinematics

Citation Formats

Park, Jihong, Seeley, Matthew K., Francom, Devin, Reese, C. Shane, and Hopkins, J. Ty. Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach. United States: N. p., 2017. Web. doi:10.1515/hukin-2017-0114.
Park, Jihong, Seeley, Matthew K., Francom, Devin, Reese, C. Shane, & Hopkins, J. Ty. Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach. United States. doi:10.1515/hukin-2017-0114.
Park, Jihong, Seeley, Matthew K., Francom, Devin, Reese, C. Shane, and Hopkins, J. Ty. Thu . "Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach". United States. doi:10.1515/hukin-2017-0114. https://www.osti.gov/servlets/purl/1441331.
@article{osti_1441331,
title = {Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach},
author = {Park, Jihong and Seeley, Matthew K. and Francom, Devin and Reese, C. Shane and Hopkins, J. Ty},
abstractNote = {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. Thus 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.},
doi = {10.1515/hukin-2017-0114},
journal = {Journal of Human Kinetics},
number = 1,
volume = 60,
place = {United States},
year = {Thu Dec 28 00:00:00 EST 2017},
month = {Thu Dec 28 00:00:00 EST 2017}
}

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