Garcia-Retortillo Sergi, Abenza Óscar, Vasileva Fidanka, Balagué Natàlia, Hristovski Robert, Wells Andrew, Fanning Jason, Kattula Jeff, Ivanov Plamen Ch
Department of Health and Exercise Science, Wake Forest University, Winston-Salem, NC, 27190, USA.
Complex Systems in Sport, INEFC University of Barcelona, 08038, Barcelona, Spain.
Geroscience. 2025 Apr;47(2):1615-1639. doi: 10.1007/s11357-024-01331-9. Epub 2024 Sep 17.
Assessing inter-muscular coordination in older adults is crucial, as it directly impacts an individual's ability for independent functioning, injury prevention, and active engagement in daily activities. However, the precise mechanisms by which distinct muscle fiber types synchronize their activity across muscles to generate coordinated movements in older adults remain unknown. Our objective is to investigate how distinct muscle groups dynamically synchronize with each other in young and older adults during exercise. Thirty-five young adults and nine older adults performed one bodyweight squat set until exhaustion. Simultaneous surface electromyography (sEMG) recordings were taken from the left and right vastus lateralis, and left and right erector spinae. To quantify inter-muscular coordination, we first obtained ten time series of sEMG band power for each muscle, representing the dynamics of different muscle fiber types. Next, we calculated the bivariate equal-time Pearson's cross-correlation for each pair of sEMG band power time series across all leg and back muscles. The main results show (i) an overall reduction in the degree of inter-muscular coordination, and (ii) increased stratification of the inter-muscular network in older adults compared to young adults. These findings suggest that as individuals age, the global inter-muscular network becomes less flexible and adaptable, hindering its ability to reorganize effectively in response to fatigue or other stimuli. This network approach opens new avenues for developing novel network-based markers to characterize multilevel inter-muscular interactions, which can help target functional deficits and potentially reduce the risk of falls and neuro-muscular injuries in older adults.
评估老年人的肌肉间协调性至关重要,因为它直接影响个体的独立功能、预防损伤以及积极参与日常活动的能力。然而,在老年人中,不同肌肉纤维类型如何跨肌肉同步其活动以产生协调运动的精确机制仍不清楚。我们的目标是研究年轻人和老年人在运动过程中不同肌肉群如何动态地相互同步。35名年轻人和9名老年人进行一组自重深蹲直至力竭。同时从左右外侧股四头肌以及左右竖脊肌进行表面肌电图(sEMG)记录。为了量化肌肉间协调性,我们首先为每块肌肉获取了10个sEMG频段功率的时间序列,代表不同肌肉纤维类型的动态变化。接下来,我们计算了所有腿部和背部肌肉的每对sEMG频段功率时间序列的双变量等时皮尔逊交叉相关性。主要结果表明:(i)肌肉间协调性程度总体降低;(ii)与年轻人相比,老年人肌肉间网络的分层增加。这些发现表明,随着个体年龄增长,整体肌肉间网络变得不那么灵活和适应性差,阻碍了其有效重组以应对疲劳或其他刺激的能力。这种网络方法为开发新的基于网络的标志物以表征多层次肌肉间相互作用开辟了新途径,这有助于针对功能缺陷并可能降低老年人跌倒和神经肌肉损伤的风险。