ArticleScientific reports2021
Implications of sample size and acquired number of steps to investigate running biomechanics.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
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- Associations between body composition, physical activity, and life satisfaction in perimenopausal women aged 40-50 years: a cross-sectional study.Przeglad menopauzalny = Menopause review · 2026Article
- Radiographic Imaging to improve frontal plane weight bearing symmetry and its impact on gait in transtibial bone anchored prosthesis users.Scientific reports · 2026Article
- The Use of Machine Learning to Estimate Ground Reaction Forces During Running: A Scoping Review of the Current Practices.Sensors (Basel, Switzerland) · 2026Article
- Development of a Novel Low-Cost Knee Brace to Quantify Human Knee Function During Dynamic Tasks: A Feasibility Study from the North-West Province.Sensors (Basel, Switzerland) · 2026Article
- Divergent Responses to Training Load in Professional Australian Football: Are Insights Obtained from Generic and Running-based Assessments Complementary or Redundant?Sports medicine - open · 2025Article
- James-Stein Estimator Improves Accuracy and Sample Efficiency in Human Kinematic and Metabolic Data.Annals of biomedical engineering · 2025Article
- Field-Based Gait Retraining to Reduce Impact Loading Using Tibial Accelerometers in High-Impact Recreational Runners: A Feasibility Study.Sensors (Basel, Switzerland) · 2025Article
- Postural stability measures as diagnostic tools for chronic ankle instability: a comprehensive assessment.BMC sports science, medicine & rehabilitation · 2025Article
- Pelvic compression garments alter running biomechanics, perceived support, and fear of symptoms in postpartum women with pelvic floor dysfunction: preliminary observations from an exploratory, randomised, repeated-measures crossover design.Frontiers in sports and active living · 2025Article
- Two types of insoles design to influence running biomechanics in opposite directions and individual responses.Frontiers in bioengineering and biotechnology · 2025Article
- Classifying Impact Loading Using Axial Peak Tibial Acceleration and Impact-Related Biomechanical Differences During Treadmill Running.Scandinavian journal of medicine & science in sports · 2025Article
- Article
- Variable-stiffness prosthesis improves biomechanics of walking across speeds compared to a passive device.Scientific reports · 2024Article
- Prediction of instantaneous perceived effort during outdoor running using accelerometry and machine learning.European journal of applied physiology · 2024Article
- Comparison of muscle activity of the lower limbs while running on different treadmill models.Frontiers in human neuroscience · 2024Article
- The Impact of Excessive Body Weight and Foot Pronation on Running Kinetics: A Cross-Sectional Study.Sports medicine - open · 2023Article
- OpenCap: Human movement dynamics from smartphone videos.PLoS computational biology · 2023Article
- Sensitiveness of Variables Extracted from a Fitness Smartwatch to Detect Changes in Vertical Impact Loading during Outdoors Running.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
2 authors.
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Abstract
Low reproducibility and non-optimal sample sizes are current concerns in scientific research, especially within human movement studies. Therefore, this study aimed to examine the implications of different sample sizes and number of steps on data variability and statistical outcomes from kinematic and kinetics running biomechanical variables. Forty-four participants ran overground using their preferred technique (normal) and minimizing the contact sound volume (silent). Running speed, peak vertical, braking forces, and vertical average loading rate were extracted from > 40 steps/runner. Data stability was computed using a sequential estimation technique. Statistical outcomes (p values and effect sizes) from the comparison normal vs silent running were extracted from 100,000 random samples, using various combinations of sample size (from 10 to 40 runners) and number of steps (from 5 to 40 steps). The results showed that only 35% of the study sample could reach average stability using up to 10 steps across all biomechanical variables. The loading rate was consistently significantly lower during silent running compared to normal running, with large effect sizes across all combinations. However, variables presenting small or medium effect sizes (running speed and peak braking force), required > 20 runners to reach significant differences. Therefore, varying sample sizes and number of steps are shown to influence the normal vs silent running statistical outcomes in a variable-dependent manner. Based on our results, we recommend that studies involving analysis of traditional running biomechanical variables use a minimum of 25 participants and 25 steps from each participant to provide appropriate data stability and statistical power.
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