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.

scholarly journals Habitual foot strike pattern does not affect simulated triceps surae muscle metabolic energy consumption during running

2019 ◽  
Vol 222 (23) ◽  
pp. jeb212449
Author(s):  
Wannes Swinnen ◽  
Wouter Hoogkamer ◽  
Friedl De Groote ◽  
Benedicte Vanwanseele
Keyword(s):  
Energy Consumption ◽  
Triceps Surae ◽  
Metabolic Energy ◽  
Triceps Surae Muscle ◽  
Foot Strike

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 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 Habitual foot strike pattern does not affect simulated Triceps Surae muscle metabolic energy consumption during running

2019 ◽  
Author(s):  
Wannes Swinnen ◽  
Wouter Hoogkamer ◽  
Friedl De Groote ◽  
Benedicte Vanwanseele
Keyword(s):  
Energy Consumption ◽  
Triceps Surae ◽  
Metabolic Energy ◽  
Whole Body ◽  
Optimization Approach ◽  
Joint Work ◽  
Energy Models ◽  
Triceps Surae Muscle ◽  
Direct Measurements ◽  
Foot Strike

AbstractFoot strike pattern affects ankle joint work and Triceps Surae muscle-tendon dynamics during running. Whether these changes in muscle-tendon dynamics also affect Triceps Surae muscle energy consumption is still unknown. In addition, as the Triceps Surae muscle accounts for a substantial amount of the whole body metabolic energy consumption, changes in Triceps Surae energy consumption may affect whole body metabolic energy consumption. However, direct measurements of muscle metabolic energy consumption during dynamic movements is hard. Model-based approaches can be used to estimate individual muscle and whole body metabolic energy consumption based on Hill type muscle models. In this study, we use an integrated experimental and dynamic optimization approach to compute muscle states (muscle forces, lengths, velocities, excitations and activations) of 10 habitual mid-/forefoot striking and 9 habitual rearfoot striking runners while running at 10 and 14 km/h. The Achilles tendon stiffness of the musculoskeletal model was adapted to fit experimental ultrasound data of the Gastrocnemius medialis muscle during ground contact. Next, we calculated Triceps Surae muscle and whole body metabolic energy consumption using four different metabolic energy models provided in literature. Neither Triceps Surae metabolic energy consumption (p > 0.35), nor whole body metabolic energy consumption (p > 0.14) was different between foot strike patterns, regardless of the energy model used or running speed tested. Our results provide new evidence that mid-/forefoot and rearfoot strike pattern are metabolically equivalent.

scholarly journals Reducing the metabolic energy of walking and running using an unpowered hip exoskeleton

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Tiancheng Zhou ◽  
Caihua Xiong ◽  
Juanjuan Zhang ◽  
Di Hu ◽  
Wenbin Chen ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Design Method ◽  
Metabolic Cost ◽  
Metabolic Energy ◽  
Spring Stiffness ◽  
Spatiotemporal Parameters ◽  
The Common ◽  
Hip Flexion ◽  
Optimal Stiffness ◽  
Insight Into

Abstract Background Walking and running are the most common means of locomotion in human daily life. People have made advances in developing separate exoskeletons to reduce the metabolic rate of walking or running. However, the combined requirements of overcoming the fundamental biomechanical differences between the two gaits and minimizing the metabolic penalty of the exoskeleton mass make it challenging to develop an exoskeleton that can reduce the metabolic energy during both gaits. Here we show that the metabolic energy of both walking and running can be reduced by regulating the metabolic energy of hip flexion during the common energy consumption period of the two gaits using an unpowered hip exoskeleton. Methods We analyzed the metabolic rates, muscle activities and spatiotemporal parameters of 9 healthy subjects (mean ± s.t.d; 24.9 ± 3.7 years, 66.9 ± 8.7 kg, 1.76 ± 0.05 m) walking on a treadmill at a speed of 1.5 m s−1 and running at a speed of 2.5 m s−1 with different spring stiffnesses. After obtaining the optimal spring stiffness, we recruited the participants to walk and run with the assistance from a spring with optimal stiffness at different speeds to demonstrate the generality of the proposed approach. Results We found that the common optimal exoskeleton spring stiffness for walking and running was 83 Nm Rad−1, corresponding to 7.2% ± 1.2% (mean ± s.e.m, paired t-test p < 0.01) and 6.8% ± 1.0% (p < 0.01) metabolic reductions compared to walking and running without exoskeleton. The metabolic energy within the tested speed range can be reduced with the assistance except for low-speed walking (1.0 m s−1). Participants showed different changes in muscle activities with the assistance of the proposed exoskeleton. Conclusions This paper first demonstrates that the metabolic cost of walking and running can be reduced using an unpowered hip exoskeleton to regulate the metabolic energy of hip flexion. The design method based on analyzing the common energy consumption characteristics between gaits may inspire future exoskeletons that assist multiple gaits. The results of different changes in muscle activities provide new insight into human response to the same assistive principle for different gaits (walking and running).

Gait Training with Wearable Hip-assist Robot Reduce Trunk and Leg Muscle Efforts and Metabolic Energy Consumption in Community Dwelling Elderly Adults: A Randomized Controlled Trial

2019 ◽  
Author(s):  
Hwang-Jae Lee ◽  
Su Hyun Lee ◽  
Won Hyuk Chang ◽  
Keehong Seo ◽  
Jusuk Lee ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Gait Training ◽  
Community Dwelling ◽  
Metabolic Energy ◽  
Control Group ◽  
Elderly Adults ◽  
Age Related ◽  
Spatio Temporal ◽  
Gait Function ◽  
Experimental Group

Abstract Background: Wearable types of gait-assist robots have been developed to provide additional advantages such as being easily transportable, producing a more natural gait pattern, and being simple to control. The purpose of this study was to investigate the effect of intensive gait training with a newly developed wearable hip-assist robot on gait function and cardiopulmonary metabolic energy efficiency in community-dwelling elderly adults. Methods: Total of 27 community-dwelling elderly adults with age-related problems completed in this intervention study (15 experimental group and 12 control group) . The experimental participants received an intensive gait training program with a total of 10 sessions involving five sessions of treadmill and five sessions of over-ground gait training with the wearable hip-assist robot. The control group received gait training without a wearable-hip assist robot. The primary outcomes were gait functions (spatio-temporal parameters and muscle effort). The secondary outcome was cardiopulmonary metabolic energy consumption. Results: Compared to the control group, the experimental group had significantly greater improvements after intervention in spatio-temporal parameters (gait speed, cadence, and stride length) and reduced muscle efforts (trunk and lower extremity) with gait (p < 0.05). In addition, the reduction in oxygen consumption (ml/min/kg) was about 16.31% in the experimental group after intervention. Furthermore, the reduction in the aerobic energy expenditure measurement (Kcal/min) was about 17.36% in the experimental group after intensive gait training with wearable hip-assist robot. All cardiopulmonary metabolic energy consumption parameters in the experimental group were reduced significantly more than in the control group (p < 0.01). Conclusion: The intensive gait training with a wearable hip-assist robot was effective in improving gait function and cardiopulmonary metabolic energy efficiency in community-dwelling elderly adults with age-related problems. Trial registration: NCT02843828, registration date: 07/14/2016 - retrospectively registered

scholarly journals Internal mechanical work and maximum subtalar joint pronation in different gradients

2019 ◽  
Vol 32 ◽  
Author(s):  
Karina Azevedo Lopes ◽  
Mayara Maciel Batista ◽  
Letícia Martins ◽  
André Luiz Kiihn ◽  
Marcos Roberto Queiroga ◽  
...  
Keyword(s):  
Repeated Measures ◽  
Running Economy ◽  
Mechanical Work ◽  
Distance Runners ◽  
Long Distance ◽  
Running Speed ◽  
The Social ◽  
Complex Relationships ◽  
Student’S T ◽  
Student’S T Test

Abstract Introduction: Some authors have described the importance of physiological intensity in the behavior of the biomechanical aspects of running (for example, subtalar pronation), but the complex relationships between these variables are not yet well understood. Objective: This study investigated the influence of positive gradients on internal mechanical work (Wint) and maximum subtalar pronation at a submaximal running speed. Method: Sixteen male, trained long-distance runners (age: 29 ± 7 yr; stature: 1.72 ± 0.07 m; body mass: 72.1 ± 10.6 kg), performed four running economy tests (gradients: +1%, +5%, +10% and +15%, respectively) for four minutes at a same submaximal running speed to quantify the maximum values of subtalar pronation and predict the Wint values. Data were analyzed using descriptive statistics, Student’s T-test, and one-way repeated-measures (ANOVA) along with the Statistical Package for the Social Sciences (SPSS) version 20.0. Results: Wint increased according to the gradient (p < 0.05). However, no significant differences were observed in the maximum values of maximum subtalar pronation corresponding to each gradient. Conclusion: Results show the maximum subtalar pronation during submaximal running depends on the speed rather than intensity of effort.

scholarly journals Will the Foot Strike Pattern Change at Different Running Speeds with or without Wearing Shoes?

2020 ◽  
Vol 17 (17) ◽  
pp. 6044
Author(s):  
Ying-Jen Lai ◽  
Willy Chou ◽  
I-Hua Chu ◽  
Yu-Lin Wang ◽  
Yi-Jing Lin ◽  
...  
Keyword(s):  
High Speed ◽  
Physical Therapist ◽  
Random Order ◽  
Heel Strike ◽  
Running Speed ◽  
Chi Square ◽  
Significance Level ◽  
Limb Injuries ◽  
Foot Strike ◽  
Chi Square Analysis

Runners strike their feet with three different patterns during running: forefoot, midfoot, and rearfoot. This study aimed to investigate whether runners maintain consistent patterns while running speed and foot condition change. The foot strike patterns of runners when running on a treadmill at paces ranging from slow to fast were recorded from twenty healthy male regular runners, with and without shoes, in random order. A high-speed camera was used to observe the strike patterns, which were then categorized by an experienced physical therapist. Linear-log and Pearson chi-square analysis with a significance level of α = 0.05 was performed to examine the correlation between foot strike pattern, running speed, and shoe conditions. The results suggest that runners strike with different patterns when running with and without shoes (χ2 = 99.07, p < 0.01); runners preferred to adopt heel strike regardless of running speeds when running with shoes. While running barefoot, only 23.8% of landing strikes were rearfoot, and the strike pattern distribution did not change significantly with the running speed (χ2 = 2.26, p = 0.89). In summary, the foot strike preference of runners is correlated with the foot condition (barefoot or shod) rather than running speed. For runners who intend to change their strike patterns for any reason, we recommend that they consider adjusting their footwear, which may naturally help with the foot strike adjustment. Future studies should attempt to use advanced techniques to observe further foot biomechanics in order to discover if changing strike pattern is directly correlated with lower limb injuries.

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