Collimore Ashley N, Pohlig Ryan T, Awad Louis N
Department of Physical Therapy, Sargent College of Health and Rehabilitation Sciences, Boston University, Boston, MA 02215, USA.
Biostatistics Core Facility, University of Delaware, Newark, DE 19713, USA.
Sensors (Basel). 2024 Nov 21;24(23):7442. doi: 10.3390/s24237442.
The dynamic motor control index is an emerging biomarker of age-related neuromuscular impairment. To date, it has been computed by quantifying the co-activity of eleven lower limb muscles. Because clinics that routinely employ electromyography typically collect from fewer muscles, a reduced muscle sensor set may improve the clinical usability of this metric of motor control. This study aimed to test if commonly used eight- and five-muscle electromyography (EMG) sensor sets produce similar dynamic motor control indices as the previously examined eleven-muscle sensor set and similarly differentiate across age subgroups. EMG data were collected during treadmill walking from 36 adults separated into young (N = 18, <35 yrs.), young-old (N = 13, 65-74 yrs.), and old-old (N = 5, ≥75 yrs.) subgroups. Dynamic motor control indices generated using the sensor set with eleven muscles correlated with the eight-muscle set (R = 0.70) but not the five-muscle set (R = 0.30). Regression models using the eleven-muscle (χ(4) = 10.62, = 0.031, Nagelkerke R = 0.297) and eight-muscle (χ(4) = 9.418, = 0.051, Nagelkerke R = 0.267) sets were significant and approaching significance, respectively, whereas the model for the five-muscle set was not significant ( = 0.663, Nagelkerke R = 0.073). In both the eleven-muscle (Wald χ = 5.16, = 0.023, OR = 1.26) and eight-muscle models (Wald χ = 4.20, = 0.04, OR = 1.19), a higher index significantly predicted being in the young group compared to the old-old group. Age-related differences in the neuromuscular control of walking can be detected using dynamic motor control indices generated using eleven- and eight-muscle sensor sets, increasing clinical usability of the dynamic motor control index.
动态运动控制指数是一种新兴的与年龄相关的神经肌肉损伤生物标志物。迄今为止，它是通过量化11块下肢肌肉的共同活动来计算的。由于常规使用肌电图的诊所通常从较少的肌肉进行采集，减少肌肉传感器组可能会提高这种运动控制指标在临床上的可用性。本研究旨在测试常用的8肌肉和5肌肉肌电图（EMG）传感器组是否能产生与之前检测的11肌肉传感器组相似的动态运动控制指数，以及是否能在不同年龄亚组中进行类似的区分。在跑步机行走过程中，收集了36名成年人的EMG数据，这些成年人被分为年轻组（N = 18，<35岁）、年轻老年组（N = 13，65 - 74岁）和老年组（N = 5，≥75岁）亚组。使用11块肌肉的传感器组生成的动态运动控制指数与8肌肉组相关（R = 0.70），但与5肌肉组不相关（R = 0.30）。使用11肌肉组（χ(4) = 10.62，P = 0.031，Nagelkerke R = 0.297）和8肌肉组（χ(4) = 9.418，P = 0.051，Nagelkerke R = 0.267）的回归模型分别具有显著性和接近显著性，而5肌肉组的模型不具有显著性（P = 0.663，Nagelkerke R = 0.073）。在11肌肉组（Wald χ = 5.16，P = 0.023，OR = 1.26）和8肌肉组模型（Wald χ = 4.20，P = 0.04，OR = 1.19）中，与老年组相比，较高的指数显著预测属于年轻组。使用11肌肉和8肌肉传感器组生成的动态运动控制指数可以检测出与年龄相关的行走神经肌肉控制差异，提高了动态运动控制指数在临床上的可用性。
