Functional data analysis reveals asymmetrical crank torque during cycling performed at different exercise intensities
| Autor: | Jéssica da Silva Soares, Leopoldo Augusto Paolucci, Marcos Roberto Kunzler, Fabiola Bertu Medeiros, André Gustavo Pereira de Andrade, Felipe P. Carpes, Álvaro Sosa Machado, Gislaine de Fátima Geraldo |
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| Rok vydání: | 2021 |
| Předmět: |
Data Analysis
media_common.quotation_subject 0206 medical engineering Biomedical Engineering Biophysics 02 engineering and technology Kinematics Asymmetry 03 medical and health sciences 0302 clinical medicine Control theory Torque Orthopedics and Sports Medicine Power output Muscle Skeletal media_common Mathematics Leg Crank Rehabilitation Functional data analysis 020601 biomedical engineering Bicycling Biomechanical Phenomena Intensity (physics) body regions Cycling 030217 neurology & neurosurgery |
| Zdroj: | Journal of Biomechanics. 122:110478 |
| ISSN: | 0021-9290 |
| DOI: | 10.1016/j.jbiomech.2021.110478 |
| Popis: | Pedaling asymmetry is claimed as a factor of influence on injury and performance. However, the evidence is still controversial. Most previous studies determined peak torque asymmetries, which in our understanding does not consider the pattern of movement like torque profiles. Here we demonstrate that asymmetries in pedaling torque at different exercise intensities can be better described when the torque profiles are considered using functional analysis of variance than when only the peak values are analyzed. We compared peak torques and torque curves recorded while cyclists pedaled at submaximal intensities of 60%, 80%, and 95% of the maximal power output and compared data between the preferred and non-preferred legs. ANOVA showed symmetry or rather no difference in the amount of peak torque between legs, regardless of pedaling intensity. FANOVA, on the other hand, revealed significant asymmetries between legs, regardless of cycling intensity, apparently for different sections of the cycle, however, not for peak torque, either. We conclude that pedaling asymmetry cannot be quantified solely by peak torques and considering the analysis of the entire movement cycle can more accurately reflect the biomechanical movement pattern. Therefore, FANOVA data analysis could be an alternative to identify asymmetries. A novel approach as described here might be useful when combining kinetics assessment with other approaches like EMG and kinematics and help to better understand the role of pedaling asymmetries for performance and injury risks. |
| Databáze: | OpenAIRE |
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