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Asymmetric velocity profiles in Paralympic powerlifters performing at different exercise intensities are detected by functional data analysis
- Source :
- Journal of Biomechanics. 123:110523
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- Asymmetries compromise performance in powerlifting and Paralympic powerlifting, but its quantification can be complex. Previous studies consider average or peak values to quantify asymmetries, however this approach does not consider the pattern of movement like velocity profiles. Here we demonstrate that conducting a functional analysis of variance (FANOVA) permits to quantify asymmetries in bench press performance by Paralympic powerlifting at different submaximal intensities. Kinematic data were collected from 10 Paralympic powerlifting athletes performing in bench press at submaximal intensities (50% and 90% of the one-repetition maximum). Linear velocity was quantified considering mean values and the entire waveform. Mean values were compared by analysis of variance (ANOVA) and the waveforms were compared by FANOVA. FANOVA identified asymmetry profiles that ANOVA did not recognize at the highest intensity, which is the closest to a competition. This way, FANOVA can bring advantages to the analysis of competitive performance. FANOVA data analysis identifies asymmetries at higher intensity of effort considering the whole pattern of movement. Therefore, we consider that the FANOVA's approach may benefit the biomechanical assessment of the Paralympic powerlifting.
- Subjects :
- Data Analysis
Weight Lifting
Movement
0206 medical engineering
Rehabilitation
Biomedical Engineering
Biophysics
Functional data analysis
02 engineering and technology
Kinematics
020601 biomedical engineering
Bench press
Biomechanical Phenomena
Exercise Therapy
Intensity (physics)
03 medical and health sciences
0302 clinical medicine
Statistics
Muscle strength
Humans
Orthopedics and Sports Medicine
030217 neurology & neurosurgery
Biomechanical assessment
Mathematics
Subjects
Details
- ISSN :
- 00219290
- Volume :
- 123
- Database :
- OpenAIRE
- Journal :
- Journal of Biomechanics
- Accession number :
- edsair.doi.dedup.....91977ac8f51e1b2bf75b345c9cef5faf