A statistical approach to the use of control entropy identifies differences in constraints of gait in highly trained versus untrained runners
Control entropy (CE) is a complexity analysis suitable fordynamic, non-stationary conditions which allows the inference of the control effort of a dynamical system generating the signal [4]. These characteristics make CE a highly relevant time varying quantity relevant to the dynamic physiological...
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AIMS Press
2011-11-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2012.9.123 |
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| author | Rana D. Parshad Stephen J. McGregor Michael A. Busa Joseph D. Skufca Erik Bollt |
| author_facet | Rana D. Parshad Stephen J. McGregor Michael A. Busa Joseph D. Skufca Erik Bollt |
| author_sort | Rana D. Parshad |
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| description | Control entropy (CE) is a complexity analysis suitable fordynamic, non-stationary conditions which allows the inference of the control effort of a dynamical system generating the signal [4]. These characteristics make CE a highly relevant time varying quantity relevant to the dynamic physiological responses associated with running. Using High Resolution Accelerometry (HRA) signals we evaluate here constraints of running gait, from two different groups of runners, highly trained collegiate and untrained runners.To this end, we further develop the control entropy (CE) statistic to allow for group analysis to examine the non-linearcharacteristics of movement patterns in highly trained runners with those of untrained runners, to gain insight regarding gaits that are optimal for running. Specifically, CE develops response time series of individuals descriptive of the control effort; a group analysis of these shapes developed here uses Karhunen Loeve Analysis (KL) modes of these time series which are compared between groups by application of a Hotelling $T^{2}$ test to these group response shapes. We find that differences in the shape of the CE response exist within groups, between axes for untrained runners (vertical vs anterior-posterior and mediolateral vs anterior-posterior) and trained runners (mediolateral vs anterior-posterior). Also shape differences exist between groups by axes (vertical vs mediolateral). Further, the CE, as a whole, was higher in each axis in trained vs untrained runners. These results indicate that the approach can provide unique insight regarding the differing constraints on running gait in highly trained and untrained runners when running under dynamic conditions. Further, the final point indicates trained runners are less constrained than untrained runners across all running speeds. |
| format | Article |
| id | doaj-art-b504433291b34e399c4bba79ac444388 |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2011-11-01 |
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| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-b504433291b34e399c4bba79ac4443882025-01-24T02:05:22ZengAIMS PressMathematical Biosciences and Engineering1551-00182011-11-019112314510.3934/mbe.2012.9.123A statistical approach to the use of control entropy identifies differences in constraints of gait in highly trained versus untrained runnersRana D. Parshad0Stephen J. McGregor1Michael A. Busa2Joseph D. Skufca3Erik Bollt4Department of Mathematics & Computer Science, Clarkson University, Potsdam, NY 13676Department of Mathematics & Computer Science, Clarkson University, Potsdam, NY 13676Department of Mathematics & Computer Science, Clarkson University, Potsdam, NY 13676Department of Mathematics & Computer Science, Clarkson University, Potsdam, NY 13676Department of Mathematics & Computer Science, Clarkson University, Potsdam, NY 13676Control entropy (CE) is a complexity analysis suitable fordynamic, non-stationary conditions which allows the inference of the control effort of a dynamical system generating the signal [4]. These characteristics make CE a highly relevant time varying quantity relevant to the dynamic physiological responses associated with running. Using High Resolution Accelerometry (HRA) signals we evaluate here constraints of running gait, from two different groups of runners, highly trained collegiate and untrained runners.To this end, we further develop the control entropy (CE) statistic to allow for group analysis to examine the non-linearcharacteristics of movement patterns in highly trained runners with those of untrained runners, to gain insight regarding gaits that are optimal for running. Specifically, CE develops response time series of individuals descriptive of the control effort; a group analysis of these shapes developed here uses Karhunen Loeve Analysis (KL) modes of these time series which are compared between groups by application of a Hotelling $T^{2}$ test to these group response shapes. We find that differences in the shape of the CE response exist within groups, between axes for untrained runners (vertical vs anterior-posterior and mediolateral vs anterior-posterior) and trained runners (mediolateral vs anterior-posterior). Also shape differences exist between groups by axes (vertical vs mediolateral). Further, the CE, as a whole, was higher in each axis in trained vs untrained runners. These results indicate that the approach can provide unique insight regarding the differing constraints on running gait in highly trained and untrained runners when running under dynamic conditions. Further, the final point indicates trained runners are less constrained than untrained runners across all running speeds.https://www.aimspress.com/article/doi/10.3934/mbe.2012.9.123statistical hypothesis testingcontrol entropygait analysis. |
| spellingShingle | Rana D. Parshad Stephen J. McGregor Michael A. Busa Joseph D. Skufca Erik Bollt A statistical approach to the use of control entropy identifies differences in constraints of gait in highly trained versus untrained runners Mathematical Biosciences and Engineering statistical hypothesis testing control entropy gait analysis. |
| title | A statistical approach to the use of control entropy identifies differences in constraints of gait in highly trained versus untrained runners |
| title_full | A statistical approach to the use of control entropy identifies differences in constraints of gait in highly trained versus untrained runners |
| title_fullStr | A statistical approach to the use of control entropy identifies differences in constraints of gait in highly trained versus untrained runners |
| title_full_unstemmed | A statistical approach to the use of control entropy identifies differences in constraints of gait in highly trained versus untrained runners |
| title_short | A statistical approach to the use of control entropy identifies differences in constraints of gait in highly trained versus untrained runners |
| title_sort | statistical approach to the use of control entropy identifies differences in constraints of gait in highly trained versus untrained runners |
| topic | statistical hypothesis testing control entropy gait analysis. |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2012.9.123 |
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