Low-back disorders (LBDs) are the most common and costly musculoskeletal problem. Muscle co-activation, a mechanism that stabilises the spine, is adopted by the central nervous system to provide added protection and avoid LBDs. However, during high-risk lifting tasks, the compressive load on the spine grows owing to increased co-activation. The aim of this study was to develop a method for the sample-by-sample monitoring of the co-activation of more than two muscles, and to compare this method with agonist–antagonist methods. We propose a time-varying multi-muscle co-activation function that considers electromyographic (EMG) signals as input. EMG data of 10 healthy subjects were recorded while they manually lifted loads at three progressively heavier conditions. The repeated measures ANOVA revealed a significant effect of lifting condition on our co-activation index. Heavier conditions resulted in higher muscle co-activation values. Significant correlations were found between the time-varying multi-muscle co-activation index and other agonist–antagonist methods. Practitioner Summary: We have developed a method to quantify muscle co-activation during the execution of a lifting task. To do this we used surface electromyography. Our algorithm provides a measure of time-varying co-activation between more than two muscles.
A new muscle co-activation index for biomechanical load evaluation in work activities / A., Ranavolo; Mari, Silvia; C., Conte; Serrao, Mariano; A., Silvetti; S., Iavicoli; F., Draicchio. - In: ERGONOMICS. - ISSN 0014-0139. - 58:6(2015), pp. 966-979. [10.1080/00140139.2014.991764]
A new muscle co-activation index for biomechanical load evaluation in work activities
MARI, SILVIA;SERRAO, Mariano;
2015
Abstract
Low-back disorders (LBDs) are the most common and costly musculoskeletal problem. Muscle co-activation, a mechanism that stabilises the spine, is adopted by the central nervous system to provide added protection and avoid LBDs. However, during high-risk lifting tasks, the compressive load on the spine grows owing to increased co-activation. The aim of this study was to develop a method for the sample-by-sample monitoring of the co-activation of more than two muscles, and to compare this method with agonist–antagonist methods. We propose a time-varying multi-muscle co-activation function that considers electromyographic (EMG) signals as input. EMG data of 10 healthy subjects were recorded while they manually lifted loads at three progressively heavier conditions. The repeated measures ANOVA revealed a significant effect of lifting condition on our co-activation index. Heavier conditions resulted in higher muscle co-activation values. Significant correlations were found between the time-varying multi-muscle co-activation index and other agonist–antagonist methods. Practitioner Summary: We have developed a method to quantify muscle co-activation during the execution of a lifting task. To do this we used surface electromyography. Our algorithm provides a measure of time-varying co-activation between more than two muscles.File | Dimensione | Formato | |
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