Running Gait Complexity During an Overground, Mass-Participation Five-Kilometre Run
Human locomotion contains innate variability which may provide health insights. Detrended fluctuation analysis (DFA) has been used to quantify the temporal structure of variability for treadmill running, although it has been less commonly applied to uncontrolled overground running. This study aimed...
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MDPI AG
2024-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/22/7252 |
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| author | Ben Jones Ben Heller Linda van Gelder Andrew Barnes Joanna Reeves Jon Wheat |
| author_facet | Ben Jones Ben Heller Linda van Gelder Andrew Barnes Joanna Reeves Jon Wheat |
| author_sort | Ben Jones |
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| description | Human locomotion contains innate variability which may provide health insights. Detrended fluctuation analysis (DFA) has been used to quantify the temporal structure of variability for treadmill running, although it has been less commonly applied to uncontrolled overground running. This study aimed to determine how running gait complexity changes in response to gradient and elapsed exercise duration during uncontrolled overground running. Sixty-eight participants completed an overground, mass-participation five-kilometre run (a parkrun). Stride times were recorded using an inertial measurement unit mounted on the distal shank. Data were divided into four consecutive intervals (uphill lap 1, downhill lap 1, uphill lap 2, downhill lap 2). The magnitude (SD) and structure (DFA) of stride time variability were compared across elapsed exercise duration and gradient using a repeated-measures ANOVA. Participants maintained consistent stride times throughout the run. Stride time DFA-α displayed a moderate decrease (<i>d</i> = |0.39| ± 0.13) during downhill running compared to uphill running. DFA-α did not change in response to elapsed exercise duration, although a greater stride time SD was found during the first section of lap 1 (<i>d</i> = |0.30| ± 0.12). These findings suggest that inter- and intra-run changes in gait complexity should be interpreted in the context of course elevation profiles before conclusions on human health are drawn. |
| format | Article |
| id | doaj-art-58df647c5d374136964ca80ae373c2dd |
| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj-art-58df647c5d374136964ca80ae373c2dd2025-08-20T01:53:57ZengMDPI AGSensors1424-82202024-11-012422725210.3390/s24227252Running Gait Complexity During an Overground, Mass-Participation Five-Kilometre RunBen Jones0Ben Heller1Linda van Gelder2Andrew Barnes3Joanna Reeves4Jon Wheat5Sport and Physical Activity Research Centre, Sheffield Hallam University, Olympic Legacy Park, 2 Old Hall Rd, Sheffield S9 3TY, UKSport and Physical Activity Research Centre, Sheffield Hallam University, Olympic Legacy Park, 2 Old Hall Rd, Sheffield S9 3TY, UKSport and Physical Activity Research Centre, Sheffield Hallam University, Olympic Legacy Park, 2 Old Hall Rd, Sheffield S9 3TY, UKSport and Physical Activity Research Centre, Sheffield Hallam University, Olympic Legacy Park, 2 Old Hall Rd, Sheffield S9 3TY, UKPublic Health and Sport Sciences Department, University of Exeter Medical School, St Luke’s Campus, 79 Heavitree Rd, Exeter EX2 4TH, UKSport and Physical Activity Research Centre, Sheffield Hallam University, Olympic Legacy Park, 2 Old Hall Rd, Sheffield S9 3TY, UKHuman locomotion contains innate variability which may provide health insights. Detrended fluctuation analysis (DFA) has been used to quantify the temporal structure of variability for treadmill running, although it has been less commonly applied to uncontrolled overground running. This study aimed to determine how running gait complexity changes in response to gradient and elapsed exercise duration during uncontrolled overground running. Sixty-eight participants completed an overground, mass-participation five-kilometre run (a parkrun). Stride times were recorded using an inertial measurement unit mounted on the distal shank. Data were divided into four consecutive intervals (uphill lap 1, downhill lap 1, uphill lap 2, downhill lap 2). The magnitude (SD) and structure (DFA) of stride time variability were compared across elapsed exercise duration and gradient using a repeated-measures ANOVA. Participants maintained consistent stride times throughout the run. Stride time DFA-α displayed a moderate decrease (<i>d</i> = |0.39| ± 0.13) during downhill running compared to uphill running. DFA-α did not change in response to elapsed exercise duration, although a greater stride time SD was found during the first section of lap 1 (<i>d</i> = |0.30| ± 0.12). These findings suggest that inter- and intra-run changes in gait complexity should be interpreted in the context of course elevation profiles before conclusions on human health are drawn.https://www.mdpi.com/1424-8220/24/22/7252overground runninggait variabilitygait complexitydetrended fluctuation analysis (DFA)inertial measurement unit (IMU)gradient |
| spellingShingle | Ben Jones Ben Heller Linda van Gelder Andrew Barnes Joanna Reeves Jon Wheat Running Gait Complexity During an Overground, Mass-Participation Five-Kilometre Run Sensors overground running gait variability gait complexity detrended fluctuation analysis (DFA) inertial measurement unit (IMU) gradient |
| title | Running Gait Complexity During an Overground, Mass-Participation Five-Kilometre Run |
| title_full | Running Gait Complexity During an Overground, Mass-Participation Five-Kilometre Run |
| title_fullStr | Running Gait Complexity During an Overground, Mass-Participation Five-Kilometre Run |
| title_full_unstemmed | Running Gait Complexity During an Overground, Mass-Participation Five-Kilometre Run |
| title_short | Running Gait Complexity During an Overground, Mass-Participation Five-Kilometre Run |
| title_sort | running gait complexity during an overground mass participation five kilometre run |
| topic | overground running gait variability gait complexity detrended fluctuation analysis (DFA) inertial measurement unit (IMU) gradient |
| url | https://www.mdpi.com/1424-8220/24/22/7252 |
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