Related Experiment Video
Updated: Jul 23, 2025
09:24
A Rapidly Incremented Tethered-Swimming Maximal Protocol for Cardiorespiratory Assessment of Swimmers
Published on: January 28, 2020
8.9K
Using Statistical Parametric Mapping as a statistical method for more detailed insights in swimming: a systematic
Jorge E Morais1,2, Tiago M Barbosa1,2, Tomohiro Gonjo3
1Instituto Politécnico de Bragança, Department of Sports Sciences, Bragança, Portugal.
Frontiers in Physiology
|July 17, 2023
Summary
Statistical Parametric Mapping (SPM) offers detailed insights into swimming performance by analyzing velocity as a continuous variable. This systematic review highlights SPM
Area of Science:
- Sports Science
- Biomechanics
- Data Analysis
Background:
- Swimming performance is intrinsically time-dependent, yet velocity is often analyzed discretely.
- Traditional statistical methods may overlook nuanced performance variations within the swimming stroke cycle.
Approach:
- A systematic review following PRISMA guidelines was conducted.
- Nine articles utilizing Statistical Parametric Mapping (SPM) in swimming contexts were synthesized.
- Studies analyzed kinematics, joint torque, EMG, swimming velocity, and propulsion.
Key Points:
- SPM enables the analysis of swimming velocity as a continuous (1-D) variable, capturing time-dependent performance metrics.
- SPM revealed insights into shoulder kinematics, electromyography (EMG), breaststroke velocity, front-crawl propulsion, and underwater undulatory velocity.
- Specific differences within the stroke cycle were identified using SPM, which are not discernible with traditional 0-D methods.
Conclusions:
- Statistical Parametric Mapping (SPM) provides superior, detailed analysis of swimming performance compared to traditional discrete methods.
- SPM facilitates a deeper understanding of biomechanics and stroke efficiency, enabling targeted training interventions.
- The application of SPM in swimming research offers coaches actionable data for optimizing training drills and addressing specific performance limitations.
Related Concept Videos
01:12Statistical Methods to Analyze Parametric Data: ANOVA
438
Analysis of Variance, or ANOVA, is a powerful statistical technique used to analyze parametric data, primarily in research and experimental studies. It's designed to compare the means of two or more groups, assisting researchers in identifying any significant differences between these group means. There are two main types of ANOVA based on the complexity of the analysis: one-way and two-way.
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
438
01:16Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data
157
Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
157