scholarly journals A public dataset of running biomechanics and the effects of running speed on lower extremity kinematics and kinetics

2017 ◽  
Author(s):  
Reginaldo K Fukuchi ◽  
Claudiane A Fukuchi ◽  
Marcos Duarte
Keyword(s):  
Muscle Strength ◽  
Lower Extremity ◽  
Three Dimensional ◽  
Running Economy ◽  
Running Speed ◽  
Gait Biomechanics ◽  
Running Injuries ◽  
Foot Strike ◽  
Running Biomechanics ◽  
Kinematics And Kinetics

Background. The goals of this study were (1) to present the set of data evaluating running biomechanics (kinematics and kinetics), including data on running habits, demographics, and levels of muscle strength and flexibility made available at Figshare (DOI: 10.6084/m9.figshare.4543435); and (2) to examine the effect of running speed on selected gait-biomechanics variables related to both running injuries and running economy. Methods. The lower-extremity kinematics and kinetics data of 28 regular runners were collected using a three-dimensional (3D) motion-capture system and an instrumented treadmill while the subjects ran at 2.5 m/s, 3.5 m/s, and 4.5 m/s wearing standard neutral shoes. Results. A dataset comprising raw and processed kinematics and kinetics signals pertaining to this experiment is available in various file formats. In addition, a file of metadata, including demographics, running characteristics, foot-strike patterns, and muscle strength and flexibility measurements is provided. Overall, there was an effect of running speed on most of the gait-biomechanics variables selected for this study. However, the foot-strike patterns were not affected by running speed. Discussion. Several applications of this dataset can be anticipated, including testing new methods of data reduction and variable selection; for educational purposes; and answering specific research questions. This last application was exemplified in the study’s second objective.

scholarly journals A public dataset of running biomechanics and the effects of running speed on lower extremity kinematics and kinetics

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3298 ◽  
Author(s):  
Reginaldo K. Fukuchi ◽  
Claudiane A. Fukuchi ◽  
Marcos Duarte
Keyword(s):  
Muscle Strength ◽  
Lower Extremity ◽  
Three Dimensional ◽  
Running Economy ◽  
Running Speed ◽  
Gait Biomechanics ◽  
Running Injuries ◽  
Foot Strike ◽  
Running Biomechanics ◽  
Kinematics And Kinetics

Background The goals of this study were (1) to present the set of data evaluating running biomechanics (kinematics and kinetics), including data on running habits, demographics, and levels of muscle strength and flexibility made available at Figshare (DOI: 10.6084/m9.figshare.4543435); and (2) to examine the effect of running speed on selected gait-biomechanics variables related to both running injuries and running economy. Methods The lower-extremity kinematics and kinetics data of 28 regular runners were collected using a three-dimensional (3D) motion-capture system and an instrumented treadmill while the subjects ran at 2.5 m/s, 3.5 m/s, and 4.5 m/s wearing standard neutral shoes. Results A dataset comprising raw and processed kinematics and kinetics signals pertaining to this experiment is available in various file formats. In addition, a file of metadata, including demographics, running characteristics, foot-strike patterns, and muscle strength and flexibility measurements is provided. Overall, there was an effect of running speed on most of the gait-biomechanics variables selected for this study. However, the foot-strike patterns were not affected by running speed. Discussion Several applications of this dataset can be anticipated, including testing new methods of data reduction and variable selection; for educational purposes; and answering specific research questions. This last application was exemplified in the study’s second objective.

scholarly journals A public dataset of running biomechanics and the effects of running speed on lower extremity kinematics and kinetics

2017 ◽  
Author(s):  
Reginaldo K Fukuchi ◽  
Claudiane A Fukuchi ◽  
Marcos Duarte
Keyword(s):  
Muscle Strength ◽  
Lower Extremity ◽  
Three Dimensional ◽  
Running Economy ◽  
Running Speed ◽  
Gait Biomechanics ◽  
Running Injuries ◽  
Foot Strike ◽  
Running Biomechanics ◽  
Kinematics And Kinetics

Background. The goals of this study were (1) to present the set of data evaluating running biomechanics (kinematics and kinetics), including data on running habits, demographics, and levels of muscle strength and flexibility made available at Figshare (DOI: 10.6084/m9.figshare.4543435); and (2) to examine the effect of running speed on selected gait-biomechanics variables related to both running injuries and running economy. Methods. The lower-extremity kinematics and kinetics data of 28 regular runners were collected using a three-dimensional (3D) motion-capture system and an instrumented treadmill while the subjects ran at 2.5 m/s, 3.5 m/s, and 4.5 m/s wearing standard neutral shoes. Results. A dataset comprising raw and processed kinematics and kinetics signals pertaining to this experiment is available in various file formats. In addition, a file of metadata, including demographics, running characteristics, foot-strike patterns, and muscle strength and flexibility measurements is provided. Overall, there was an effect of running speed on most of the gait-biomechanics variables selected for this study. However, the foot-strike patterns were not affected by running speed. Discussion. Several applications of this dataset can be anticipated, including testing new methods of data reduction and variable selection; for educational purposes; and answering specific research questions. This last application was exemplified in the study’s second objective.

scholarly journals Runners Employ Different Strategies to Cope With Increased Speeds Based on Their Initial Strike Patterns

2021 ◽  
Vol 12 ◽  
Author(s):  
Antonis Ekizos ◽  
Alessandro Santuz ◽  
Adamantios Arampatzis
Keyword(s):  
Energy Consumption ◽  
Running Economy ◽  
Metabolic Energy ◽  
Running Speed ◽  
Foot Strike ◽  
Low Speeds

In this paper we examined how runners with different initial foot strike pattern (FSP) develop their pattern over increasing speeds. The foot strike index (FSI) of 47 runners [66% initially rearfoot strikers (RFS)] was measured in six speeds (2.5–5.0 ms−1), with the hypotheses that the FSI would increase (i.e., move toward the fore of the foot) in RFS strikers, but remain similar in mid- or forefoot strikers (MFS) runners. The majority of runners (77%) maintained their original FSP by increasing speed. However, we detected a significant (16.8%) decrease in the FSI in the MFS group as a function of running speed, showing changes in the running strategy, despite the absence of a shift from one FSP to another. Further, while both groups showed a decrease in contact times, we found a group by speed interaction (p < 0.001) and specifically that this decrease was lower in the MFS group with increasing running speeds. This could have implications in the metabolic energy consumption for MFS-runners, typically measured at low speeds for the assessment of running economy.

Lower Extremity Biomechanical Demands During Saut de Chat Leaps

2016 ◽  
Vol 31 (4) ◽  
pp. 211-217 ◽  
Author(s):  
Danielle N Jarvis ◽  
Kornelia Kulig
Keyword(s):  
Lower Extremity ◽  
Sagittal Plane ◽  
Reaction Force ◽  
Three Dimensional ◽  
Vertical Force ◽  
Dance Training ◽  
Chronic Injuries ◽  
Analysis System ◽  
Kinetics Of ◽  
Kinematics And Kinetics

In dance, high demands are placed on the lower extremity joints during jumping tasks. The purpose of this study was to compare biomechanical demands placed on the lower extremity joints during the takeoff and landing phases of saut de chat leaps. METHODS: Thirty healthy, experienced dancers with 20.8±4.9 yrs of dance training performed 5 saut de chat leaps. A three-dimensional motion analysis system and force plates were used to collect kinematic and kinetic data. Ground reaction force (GRF) peaks and impulse and sagittal plane kinematics and kinetics of the hip, knee, ankle, and metatarsophalangeal (MTP) joints were calculated for the takeoff and landing phases of each leap. RESULTS: Saut de chat takeoffs demonstrated greater braking GRF impulse (p<0.001), while landings demonstrated greater peak vertical GRF (p<0.001). During takeoff, greater kinetic demands were placed on the MTP (p<0.001) and ankle (p<0.001) joints, while during landing greater kinetic demands were placed on the hip (p=0.037) joint. CONCLUSIONS: Both the takeoff and landing phases of saut de chat leaps place significant demands on a dancer’s body. Takeoff involves greater demands on the more distal joints and requires more braking forces, while the landing phase involves greater demands on the more proximal joints of the lower extremity and requires the dancer to absorb more vertical force. These demands, combined with extensive repetition of movements during training, may contribute to the high number of chronic injuries seen in dance.

scholarly journals A public dataset of overground and treadmill walking kinematics and kinetics in healthy individuals

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4640 ◽  
Author(s):  
Claudiane A. Fukuchi ◽  
Reginaldo K. Fukuchi ◽  
Marcos Duarte
Keyword(s):  
Three Dimensional ◽  
Treadmill Walking ◽  
Gait Patterns ◽  
Gait Biomechanics ◽  
File Formats ◽  
Metadata File ◽  
Public Dataset ◽  
External Forces ◽  
Clinical Gait Analysis ◽  
Kinematics And Kinetics

In a typical clinical gait analysis, the gait patterns of pathological individuals are commonly compared with the typically faster, comfortable pace of healthy subjects. However, due to potential bias related to gait speed, this comparison may not be valid. Publicly available gait datasets have failed to address this issue. Therefore, the goal of this study was to present a publicly available dataset of 42 healthy volunteers (24 young adults and 18 older adults) who walked both overground and on a treadmill at a range of gait speeds. Their lower-extremity and pelvis kinematics were measured using a three-dimensional (3D) motion-capture system. The external forces during both overground and treadmill walking were collected using force plates and an instrumented treadmill, respectively. The results include both raw and processed kinematic and kinetic data in different file formats: c3d and ASCII files. In addition, a metadata file is provided that contain demographic and anthropometric data and data related to each file in the dataset. All data are available at Figshare (DOI: 10.6084/m9.figshare.5722711). We foresee several applications of this public dataset, including to examine the influences of speed, age, and environment (overground vs. treadmill) on gait biomechanics, to meet educational needs, and, with the inclusion of additional participants, to use as a normative dataset.

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