Journal Information
Share
Share
Download PDF
More article options
Visits
...
Original Research
DOI: 10.1016/j.bjpt.2020.05.003
Full text access
Available online 3 June 2020
Difference in the running biomechanics between preschoolers and adults
Visits
...
Rachel X.Y. Weia, Zoe Y.S. Chanb, Janet H.W. Zhangb, Gary L. Shumc, Chao-Ying Chenb,
Corresponding author
Chao-Ying.Chen@polyu.edu.hk

Corresponding author at: ST531, 5/F, Block S, Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China.
, Roy T.H. Cheungb,d
a Department of Orthopaedics & Traumatology, The Chinese University of Hong Kong, Sha Tin, Hong Kong, China
b Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China
c School of Sport, Health and Wellbeing, Plymouth Marjon University, Derriford, Plymouth, United Kingdom
d School of Health Sciences, Western Sydney University, Campbelltown Campus, Australia
Highlights

  • Toddlers demonstrated similar vertical loading rates and footstrike pattern when compared to adults.

  • Toddlers demonstrated a greater cadence and shorter stride length than adults.

  • Adults need not to modify the running biomechanics according to the posture in toddlers.

Article information
Abstract
Full Text
Bibliography
Download PDF
Statistics
Figures (1)
Tables (2)
Table 1. Demographics of the subjects.
Table 2. Comparison of running biomechanics between preschoolers and adults.
Show moreShow less
Abstract
Background

High vertical loading rate is associated with a variety of running-related musculoskeletal injuries. There is evidence supporting that non-rearfoot footstrike pattern, greater cadence, and shorter stride length may reduce the vertical loading rate. These features appear to be common among preschoolers, who seem to experience lower running injury incidence, leading to a debate whether adults should accordingly modify their running form.

Objective

This study sought to compare the running biomechanics between preschoolers and adults.

Methods

Ten preschoolers (4.2±1.6 years) and ten adults (35.1±9.5 years) were recruited and ran overground with their usual shoes at a self-selected speed. Vertical average and vertical instantaneous loading rate were calculated based on the kinetic data. Footstrike pattern and spatiotemporal parameters were collected using a motion capture system.

Results

There was no difference in normalized vertical average loading rate (p=0.48), vertical instantaneous loading rate (p=0.48), running speed (p=0.85), and footstrike pattern (p=0.29) between the two groups. Preschoolers demonstrated greater cadence (p<0.001) and shorter normalized stride length (p=0.01).

Conclusion

By comparing the kinetic and kinematic parameters between children and adults, our findings do not support the notion that adults should modify their running biomechanics according to the running characteristics in preschoolers for a lower injury risk.

Keywords:
Children
Vertical loading rate
Footstrike pattern
Cadence
Spatiotemporal parameters
Full Text
Introduction

Distance running is an increasingly globally popular sport as reflected by the increasing number of marathon finishers and major running events around the world.1 In spite of potential cardiovascular and mental health benefits related to distance running,2 the incidence of running-related musculoskeletal injury is extremely high. Up to 79% of regular runners may incur an overuse injury in a given year.3,4 Thus, prevention of running-related musculoskeletal injuries has received a lot of attention over the past decades.

A series of retrospective studies have related high vertical impact loading, which is usually expressed as vertical average loading rate (VALR) and vertical instantaneous loading rate (VILR), with a series of running-related ailments, such as patellofemoral pain, tibial stress fracture, and plantar fasciitis.5–7 Recent prospective studies also suggest that high VALR and VILR may be associated with the development of running injuries.8,9 Therefore, different strategies have been proposed to lower the vertical loading rates, including footstrike pattern modification10 and cadence adjustment.11

Specifically, runners exhibiting non-rearfoot strike, i.e. midfoot or forefoot strike, have been shown to experience lower VALR and VILR than rearfoot strikers.12,13 Such reduction in the impact loading can be explained by a lower effective mass during non-rearfoot strike.14 As for spatial parameters, runners with greater cadence and shorter stride length have been reported to place the heel closer to the center of mass at initial contact, which results in a reduction in the braking impulse15 and vertical loading rates.16 Therefore, shortened stride length accompanied with increased cadence for a given velocity also contribute to the reduction of running injuries.11

Anecdotally, many runners believe that adults should mimic the running pattern of children,17 who are supposed to exhibit the most natural running gait18 without being influenced by any external device e.g., shoes.19 Such belief in running biomechanics modification is mainly based on the assumption that children usually land with more non-rearfoot strikes, run with shorter stride length and higher cadence, when compared with adults.19

Limited knowledge exists, however, with regard to the difference in running characteristics between children and adults. To our best knowledge, the majority of previous studies explored differences in walking biomechanics between the two groups.20–22 However, there is a lack of evidence showing the differences in the running biomechanics between children and adults.

Considering running kinetics,23 spatiotemporal parameters,24 and joint kinematics22 become mature and more adult-like at approximately 7–8 years old, the present study compared the running biomechanics between preschoolers (i.e. age <7) and adults. We hypothesized that preschoolers would present lower body weight normalized VALR and VILR than adults. We also expected that preschoolers would exhibit more non-rearfoot strikes, greater cadence, and shorter normalized stride length than adults.

MethodsSubjects

Sample size estimate was calculated using the effect size extracted from a study comparing walking gait differences between school-aged children (5–13 years) and young adults (18–27 years).24 Normalized speed of children aged 5.7 years and young adults aged 19.6 years was extracted for calculating Cohens’ d. A sample size of 9 subjects in each group was required for the present study, based on an effect size of 1.25, type I error of 5% and type II error of 20% (power: 80%).

Ten preschoolers (four males and six females) who were able to run independently and ten adult regular runners (six males and four females) were recruited in this study (Table 1). Subjects were excluded if they had any known developmental, neurological, or musculoskeletal conditions that may have affected their gait. The experimental procedures were reviewed and approved by Departmental Research Committee, Department of Rehabilitation Sciences, the Hong Kong Polytechnic University and all adult subjects and the parents of the preschoolers provided written consents prior to the test.

Table 1.

Demographics of the subjects.

  Adults  Preschoolers  p 
Gender  6 males 4 females  4 males 6 females  0.37 
Age (year)  35.10±9.45  4.16±1.63  <0.001* 
Body weight (kg)  59.79±10.20  15.31±3.24  <0.001* 
Body height (m)  1.70±0.11  1.00±0.11  <0.001* 
Test speed (BH/s)  1.88±0.15  2.03±0.49  0.85 

BH=body height; data are expressed as mean±standard deviation (SD).

*

Indicates p<0.05.

Experimental procedures

We firmly affixed four reflective markers onto specific body landmarks, i.e., bilateral 2nd metatarsal heads and calcaneus according to a previously established model.25 Footstrike angle (FSA) during standing was defined as the angle between the anteroposterior axis of the lab coordinate system and the line connecting markers at the calcaneus and metatarsal. FSA during running was the result of subtracting the original FSA from the angle of the foot at each footstrike. Each subject was then asked to run overground along a 20-m runway with his/her usual shoes at a self-selected speed for 10 successful trials, which were defined as a clean strike onto the force plate (Optima, AMTI, Watertown, MA, USA). To avoid fatigue, subjects were allowed to have 3-min rest between each trial.26 Kinematic data were collected using a 10-camera motion capturing system (Vicon, Oxford Metrics, Oxford, UK) at 120Hz. Marker trajectories were filtered with a fourth order Butterworth low-pass filter at 12Hz.27 The initial contact was determined when the vertical ground reaction force exceeded 10N.28

The VALR and VILR were computed based on the method described in previous studies.28,29 In brief, VALR and VILR were the average and maximum slopes of the line between 20% and 80% of the vertical impact peak curve. If the vertical impact peak was indiscernible, the value at 13% of the total stance was used as a surrogate for time to the vertical impact peak.30 Both VALR and VILR were normalized to body weight. We examined footstrike pattern by measuring the FSA. FSA was calculated as the offset angle between the ground surface and the line virtually connecting the reflective markers located at the heel and metatarsal. The footstrike pattern was determined according to a validated method,25 such that a FSA lower than −1.6° indicated a forefoot strike (FFS); FSA higher than 8° indicated a rearfoot strike (RFS); and FSA between −1.6° and 8° indicated a midfoot strike (MFS). Cadence and stride length were calculated based on the time series data of the heel marker trajectory.27,31 Cadence was expressed as number of steps per minute and stride length was defined by the distance traveled by the heel marker between two consecutive foot contact with the ground. In view of the difference in the anthropometry between preschoolers and adults, stride length and running speed were normalized by body height, consistent with a previous study.32

Statistical analysis

Sex, demographic data, and test running speed were compared between the two groups using Chi-square test and Mann–Whitney U test. Data normality of all selected biomechanical parameters was evaluated by Shapiro–Wilk test. In view of the small sample of the present study, Mann–Whitney U tests were used to compare normalized VALR, normalized VILR, FSA, cadence, and normalized stride length. Chi-square test was used to compare the footstrike pattern between the two groups. All statistical analyses were performed using SPSS 23.0 with priori alpha at 0.05.

Results

Based on the Shapiro–Wilk test, the adult VILR data distribution was determined to be non-parametric (p=0.02). There was no significant difference in the normalized running speed between the two groups (p=0.85). The VALR, VILR, FSA and footstrike pattern, cadence, and stride length in preschoolers and adults are presented in Table 2 and Fig. 1. There was no significant difference in VALR (p=0.48) and VILR (p=0.48) between preschoolers and adults. Preschoolers and adults also demonstrated no differences in the FSA (p=0.85) and footstrike pattern (p=0.29). In terms of spatiotemporal parameters, preschoolers exhibited greater cadence (p<0.001) and shorter normalized stride length (p=0.01) than adults.

Table 2.

Comparison of running biomechanics between preschoolers and adults.

  Adults (mean±SD)  Preschoolers (mean±SD)  Mean difference (95% CI)  p 
Kinetics
VALR (BW/s)  52.84±10.73  56.63±11.70  3.79 (−6.76, 14.34)  0.48 
VILR (BW/s)  59.39±11.79  63.12±12.88  3.72 (−7.88, 15.33)  0.48 
FSA (degree)  9.37±11.75  9.10±4.80  −0.27 (−9.02, 8.48)  0.85 
Footstrike pattern
Rearfoot strike    0.29 
Midfoot strike     
Forefoot strike     
Cadence (step/min)  169.33±11.41  222.65±14.24  53.32 (41.15, 65.48)  <0.001* 
Normalized stride length (BH)  1.33±0.14  1.13±0.24  −0.20 (−0.39, −0.01)  0.01* 

95% CI=95% confidence interval of the difference; VALR=vertical average loading rate; VILR=vertical instantaneous loading rate; BW=body weight; FSA=footstrike angle; BH=body height.

*

Indicates p<0.05.

Figure 1.

Violin plots, indicating medians (black dotted lines), quartiles (gray solid lines) and data distribution, to compare running biomechanics between preschoolers and adults.

(0.17MB).
Discussion

This study examined the difference in running biomechanics between preschoolers and adults. There were no significant differences in the vertical loading rates and footstrike pattern between the two age groups. However, preschoolers demonstrated a statistically greater cadence and shorter stride length than adults.

In the present study, preschoolers presented similar VALR and VILR with adults. Originally, we expected that preschoolers might experience lower vertical loading rate than adults, as preschoolers may have less influence from footwear habituation.18,19 A previous study suggested that children who had never worn shoes experienced lower vertical loading rates during running.14 In the present study, however, most of the parents of our preschoolers reported that their children started to wear shoes on a daily basis since the acquisition of walking skill. In view of the normal developmental milestone of independent walking at approximately 12 months,33 and the mean age of our preschoolers i.e., 4.2 years, footwear habit for 3 years may be sufficient to alter the natural running pattern.34 Because of the association between vertical loading rate and running injury,8,9 we originally hypothesized that a lower vertical loading rate would be present in preschoolers, when compared with adults. A prospective study found that 38.5% of adolescent runners sustained at least one injury over a running season.35 This injury rate is actually similar to the risk in adult runners reported by previous studies (i.e. 19–79%).4,36 The comparable vertical loading rates between preschoolers and adults may reflect similar injury risk between groups.

Similar to the findings on vertical loading rates, preschoolers demonstrated similar FSA and footstrike pattern when compared with adults. This finding is likely explained by the interaction of footstrike pattern and footwear. Modern footwear usually includes thick and cushioned midsole, rigid heel counter, and protective arch support.37 Although footstrike pattern can be affected by other factors, such as running speed,38 these shoe features have shown to possibly lead to a RFS pattern 14,39. This finding is consistent with a previous study investigating footstrike pattern in a group of preschool children.40 In that particular study, shod running experience encouraged RFS landing in children who were aged 3–6 years and the authors suggested that there may be a footstrike pattern transition from non-RFS to RFS due to the use of shoes.40

Shod running has been reported to result in a reduction of cadence and an increase of stride length in preadolescent children.41 In the present study, preschoolers exhibited greater cadence and shorter stride length than adults, in spite of similar vertical loading rate and footstrike pattern. This finding is consistent with the findings reported in a previous study.42 A plausible explanation is that the spatiotemporal parameters may be less influenced by footwear when compared with footstrike pattern.43

Children, during growth, experience musculoskeletal changes and central nervous maturation.44 It has been suggested that some body growth factors e.g., body mass and body stiffness, affect cadence during running gait development.45 Cadence is almost coincident with the natural frequency of human locomotion during lower-speed running, and the natural frequency is determined by both body mass (m) and body stiffness (k) with relation f=(√(k/m))/2π.18 For children from 2 to 12 years old, the natural frequency of locomotion decreases with age and it is mainly attributed to the reduction in the ratio between body stiffness and body mass.18,46,47 The reduction in the ratio between k/m results in a reduction in both natural frequency of the body rebound and cadence. Cadence appears to be mature at the age of 12 years, as the ratio between k/m becomes constant due to the parallel increase in both k and m with age in the following years.18

The greater cadence may imply shorter stride length in preschoolers given the linear and quadratic stride length–cadence relationship.48 Additionally, lower ankle power generation in preschoolers may also partly explain the shorter stride length compared with adult. Running gait seems to require greater operating effort from the ankle than knee extensors.49 However, preschoolers use their proximal muscles, i.e. hip muscles, more than distal muscles, i.e. ankle plantar flexors, for power generation because of the immaturity of neuromuscular control.44 As ankle power is associated with stride length,50 developing children, especially at a younger age, may therefore present shorter stride length compared with adults.

The two age groups in our study presented comparable loading rates, despite the preschoolers demonstrated higher cadence and shorter stride length, which are commonly considered as low-risk factors during running. Taken together these findings and the potential reasons that children demonstrated different spatiotemporal running gait from adults, simply imitating preschooler-like pattern to run may not be efficacious in decreasing musculoskeletal running injuries.

It is very important to note several limitations in this study. Firstly, the present experiment adopted a cross-sectional design and the causal relationship cannot be determined. Therefore, the footwear effect on the locomotion development remains speculative and future prospective studies are warranted. Secondly, we did not control the testing shoes in the present study as we failed to find a running shoe model for both preschoolers and adults available in the market. Thirdly, we did not collect individual joint kinematics, thus leaving comprehensive analysis of difference in running postures between preschoolers and adults largely unknown. Fourthly, the sample in this study is not enough for subgroup analysis based the ages ranging from 3 to 6 years to further investigate the impact of time length of shoe wearing and running experience. Finally, the present study was conducted in a laboratory environment, which may not fully reflect the actual gait biomechanics in a natural environment. With the recent advancement of sensor technology, measurement of running biomechanics outdoors using wearable body-worn sensors is now possible.51 Future investigations of gait biomechanics in a natural environment are therefore highly warranted.

Conclusions

Preschoolers in our study demonstrated greater cadence and shorter stride length compared with adults. However, these spatiotemporal performances did not contribute to more frequent non-RFS pattern nor decrease vertical loading rates during initial contact, which were found to be associated with decreased musculoskeletal injuries in running from literature. Therefore, our findings do not support the notion that adults should modify their running biomechanics to resemble preschoolers’ running form for a lower injury risk.

Conflicts of interest

The authors declare no conflicts of interest.

Acknowledgements

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

References
[1]
J. Scheerder, K. Breedveld, J. Borgers.
Running Across Europe: The Rise and Size of One of the Largest Sport Markets.
Springer, (2015),
[2]
D.C. Lee, R.R. Pate, C.J. Lavie, et al.
Leisure-time running reduces all-cause and cardiovascular mortality risk.
J Am Coll Cardiol, 64 (2014), pp. 472-481
[3]
V. Lun, W.H. Meeuwisse, P. Stergiou, et al.
Relation between running injury and static lower limb alignment in recreational runners.
Br J Sports Med, 38 (2004), pp. 576-580
[4]
R.N. van Gent, D. Siem, M. van Middelkoop, et al.
Incidence and determinants of lower extremity running injuries in long distance runners: a systematic review.
Br J Sports Med, 41 (2007), pp. 469-480
[5]
R.T. Cheung, I.S. Davis.
Landing pattern modification to improve patellofemoral pain in runners: a case series.
J Orthop Sports Phys Ther, 41 (2011), pp. 914-919
[6]
M.B. Pohl, J. Hamill, I.S. Davis.
Biomechanical and anatomic factors associated with a history of plantar fasciitis in female runners.
Clin J Sport Med, 19 (2009), pp. 372-376
[7]
C.E. Milner, R. Ferber, C.D. Pollard, et al.
Biomechanical factors associated with tibial stress fracture in female runners.
Med Sci Sports Exerc, 38 (2006), pp. 323-328
[8]
I.S. Davis, B.J. Bowser, D.R. Mullineaux.
Greater vertical impact loading in female runners with medically diagnosed injuries: a prospective investigation.
Br J Sports Med, 50 (2016), pp. 887-892
[9]
Z.Y.S. Chan, J.H. Zhang, I.P.H. Au, et al.
Gait retraining for the reduction of injury occurrence in novice distance runners: 1-year follow-up of a randomized controlled trial.
Am J Sports Med, 46 (2018), pp. 388-395
[10]
R.T.H. Cheung, W.W. An, I.P.H. Au, et al.
Measurement agreement between a newly developed sensing insole and traditional laboratory-based method for footstrike pattern detection in runners.
PLoS One, 12 (2017), pp. e0175724
[11]
A.G. Schubert, J. Kempf, B.C. Heiderscheit.
Influence of stride frequency and length on running mechanics: a systematic review.
Sports Health, 6 (2014), pp. 210-217
[12]
R.T. Cheung, M.J. Rainbow.
Landing pattern and vertical loading rates during first attempt of barefoot running in habitual shod runners.
Hum Mov Sci, 34 (2014), pp. 120-127
[13]
P.R. Cavanagh, M.A. Lafortune.
Ground reaction forces in distance running.
J Biomech, 13 (1980), pp. 397-406
[14]
D.E. Lieberman, M. Venkadesan, W.A. Werbel, et al.
Foot strike patterns and collision forces in habitually barefoot versus shod runners.
Nature, 463 (2010), pp. 531-535
[15]
J.A. Mercer, P. Devita, T.R. Derrick, et al.
Individual effects of stride length and frequency on shock attenuation during running.
Med Sci Sports Exerc, 35 (2003), pp. 307-313
[16]
B.C. Heiderscheit, E.S. Chumanov, M.P. Michalski, et al.
Effects of step rate manipulation on joint mechanics during running.
Med Sci Sports Exerc, 43 (2011), pp. 296-302
[17]
B.R. Wilk, A. Garis.
Natural running: should we learn to run by watching our children?.
AMAA J, 24 (2011), pp. 5-7
[18]
B. Schepens, P.A. Willems, G.A. Cavagna.
The mechanics of running in children.
J Physiol, 509 (1998), pp. 927-940
[19]
I. Davis.
What can we learn from watching children run?.
AMAA J, 24 (2011), pp. 7-9
[20]
S.C. Dusing, D.E. Thorpe.
A normative sample of temporal and spatial gait parameters in children using the GAITRite® electronic walkway.
Gait Posture, 25 (2007), pp. 135-139
[21]
T. Cupp, D. Oeffinger, C. Tylkowski, et al.
Age-related kinetic changes in normal pediatrics.
J Pediatr Orthop, 19 (1999), pp. 475-478
[22]
K.J. Ganley, C.M. Powers.
Gait kinematics and kinetics of 7-year-old children: a comparison to adults using age-specific anthropometric data.
Gait Posture, 21 (2005), pp. 141-145
[23]
O. Tirosh, G. Orland, A. Eliakim, et al.
Tibial impact accelerations in gait of primary school children: The effect of age and speed.
Gait Posture, 57 (2017), pp. 265-269
[24]
N. Lythgo, C. Wilson, M. Galea.
Basic gait and symmetry measures for primary school-aged children and young adults whilst walking barefoot and with shoes.
Gait Posture, 30 (2009), pp. 502-506
[25]
A.R. Altman, I.S. Davis.
A kinematic method for footstrike pattern detection in barefoot and shod runners.
Gait Posture, 35 (2012), pp. 298-300
[26]
A.D. Nordin, J.S. Dufek, J.A. Mercer.
Three-dimensional impact kinetics with foot-strike manipulations during running.
J Sport Health Sci, 6 (2017), pp. 489-497
[27]
R.E. Fellin, W.C. Rose, T.D. Royer, et al.
Comparison of methods for kinematic identification of footstrike and toe-off during overground and treadmill running.
J Sci Med Sport, 13 (2010), pp. 646-650
[28]
H.P. Crowell, I.S. Davis.
Gait retraining to reduce lower extremity loading in runners.
Clin Biomech (Bristol, Avon), 26 (2011), pp. 78-83
[29]
R. Willy, M. Pohl, I. Davis.
Calculation of vertical load rates in the absence of vertical impact peaks.
American Society of Biomechanics Meeting,
[30]
W. An, M.J. Rainbow, R.T. Cheung.
Effects of surface inclination on the vertical loading rates and landing pattern during the first attempt of barefoot running in habitual shod runners.
Biomed Res Int, 2015 (2015), pp. 240153
[31]
F. Alton, L. Baldey, S. Caplan, et al.
A kinematic comparison of overground and treadmill walking.
Clin Biomech (Bristol, Avon), 13 (1998), pp. 434-440
[32]
R. Schwesig, S. Leuchte, D. Fischer, et al.
Inertial sensor based reference gait data for healthy subjects.
Gait Posture, 33 (2011), pp. 673-678
[33]
A.P. Gontijo, M.C. Mancini, P.L. Silva, et al.
Changes in lower limb co-contraction and stiffness by toddlers with Down syndrome and toddlers with typical development during the acquisition of independent gait.
Hum Mov Sci, 27 (2008), pp. 610-621
[34]
H.M. Rice, S.T. Jamison, I.S. Davis.
Footwear matters: influence of footwear and foot strike on load rates during running.
Med Sci Sports Exerc, 48 (2016), pp. 2462-2468
[35]
M.J. Rauh, T.D. Koepsell, F.P. Rivara, et al.
Epidemiology of musculoskeletal injuries among high school cross-country runners.
Am J Epidemiol, 163 (2005), pp. 151-159
[36]
A.D. Lopes, L.C. Hespanhol Junior, S.S. Yeung, et al.
What are the main running-related musculoskeletal injuries? A systematic review.
Sports Med, 42 (2012), pp. 891-905
[37]
J.F. Esculier, B. Dubois, C.E. Dionne, et al.
A consensus definition and rating scale for minimalist shoes.
J Foot Ankle Res, 8 (2015), pp. 42
[38]
R.T. Cheung, R.Y. Wong, T.K. Chung, et al.
Relationship between foot strike pattern, running speed, and footwear condition in recreational distance runners.
Sports Biomech, 16 (2017), pp. 238-247
[39]
I.S. Davis.
The re-emergence of the minimal running shoe.
J Orthop Sports Phys Ther, 44 (2014), pp. 775-784
[40]
P.A. Latorre-Roman, J.A. Parraga-Montilla, I. Guardia-Monteagudo, et al.
Foot strike pattern in preschool children during running: sex and shod-unshod differences.
Eur J Sport Sci, 18 (2018), pp. 407-414
[41]
K. Hollander, D. Riebe, S. Campe, et al.
Effects of footwear on treadmill running biomechanics in preadolescent children.
Gait Posture, 40 (2014), pp. 381-385
[42]
J. Whitall, N. Getchell.
From walking to running: applying a dynamical systems approach to the development of locomotor skills.
Child Dev, 66 (1995), pp. 1541-1553
[43]
M.A. Legramandi, B. Schepens, G.A. Cavagna.
Running humans attain optimal elastic bounce in their teens.
Sci Rep, 3 (2013), pp. 1310
[44]
D. Sutherland.
The development of mature gait.
Gait Posture, 6 (1997), pp. 163-170
[45]
B. Schepens, P.A. Willems, G.A. Cavagna, et al.
Mechanical power and efficiency in running children.
Pflugers Arch, 442 (2001), pp. 107-116
[46]
World Health Organization.
WHO Child Growth Standards: Length/height-for-age, Weight-for-age, Weight-for-length, Weight-for-height and Body Mass Index-for-age: Methods and Development.
(2006),
[47]
S. Haddad, C. Restieri, K. Krishnan.
Characterization of age-related changes in body weight and organ weights from birth to adolescence in humans.
J Toxicol Environ Health A, 64 (2001), pp. 453-464
[48]
T. Egerton, M. Danoudis, F. Huxham, et al.
Central gait control mechanisms and the stride length–cadence relationship.
Gait Posture, 34 (2011), pp. 178-182
[49]
J.P. Kulmala, M.T. Korhonen, L. Ruggiero, et al.
Walking and running require greater effort from the ankle than the knee extensor muscles.
Med Sci Sports Exerc, 48 (2016), pp. 2181-2189
[50]
A. Uematsu, T. Hortobágyi, K. Tsuchiya, et al.
Lower extremity power training improves healthy old adults’ gait biomechanics.
Gait Posture, 62 (2018), pp. 303-310
[51]
M. Giandolini, S. Pavailler, P. Samozino, et al.
Foot strike pattern and impact continuous measurements during a trail running race: proof of concept in a world-class athlete.
Footwear Sci, 7 (2015), pp. 127-137
Copyright © 2020. Associação Brasileira de Pesquisa e Pós-Graduação em Fisioterapia
Idiomas
Brazilian Journal of Physical Therapy

Subscribe to our newsletter

Article options
Tools
en pt
Cookies policy Política de cookies
To improve our services and products, we use "cookies" (own or third parties authorized) to show advertising related to client preferences through the analyses of navigation customer behavior. Continuing navigation will be considered as acceptance of this use. You can change the settings or obtain more information by clicking here. Utilizamos cookies próprios e de terceiros para melhorar nossos serviços e mostrar publicidade relacionada às suas preferências, analisando seus hábitos de navegação. Se continuar a navegar, consideramos que aceita o seu uso. Você pode alterar a configuração ou obter mais informações aqui.