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Inter-individual variability and pattern recognition of surface electromyography in front crawl swimming
Jonas Martens1, Daniel Daly1, Kevin Deschamps2
1Department of Kinesiology, KU Leuven, Leuven, Belgium.
Summary
Muscle activation patterns in elite swimmers show high variability, challenging previous research. Coaches should tailor techniques rather than relying on general electromyography (EMG) data for individual athlete improvement.
Area of Science:
- Sports Science
- Biomechanics
- Human Movement Analysis
Background:
- Electromyographic (EMG) variability is understudied in swimming.
- Understanding muscle activation patterns is crucial for optimizing swimming technique.
Purpose of the Study:
- To investigate inter-individual variability in muscle activation during front crawl swimming.
- To identify distinct sub-patterns within muscle activation.
Main Methods:
- Wireless surface EMG recorded rectus abdominis (RA) and deltoideus medialis (DM) activity in 15 male swimmers.
- Amplitude of median EMG trials across six cycles was analyzed for variability.
- K-means cluster analysis identified muscle activation sub-patterns.
Main Results:
- Significant inter-individual variability was observed in muscle activation patterns.
- Distinct sub-patterns were identified through cluster analysis (2, 3, and 4 clusters).
- Variability was higher than expected compared to other cyclic movements.
Conclusions:
- Elite swimmers exhibit higher inter-individual variability in EMG than previously reported.
- Coaches should exercise caution with generalized EMG data for individual technique enhancement.
- Personalized coaching approaches are recommended over standardized EMG references.
Keywords:
Cluster analysisCrawl swimmingStatistical parametric mappingVariabilityWireless electromyography
