Abstract：
This study investigates the muscle modules involved in the increase of walking speed in radiographical and asymptomatic knee osteoarthritis (KOA) patients using tensor decomposition. The human body possesses redundancy, which is the property to achieve desired movements with more degrees of freedom than necessary. The muscle module hypothesis is a proposed solution to this redundancy. While previous studies have examined the pathological muscle activity modulations in musculoskeletal diseases such as KOA, they have focused on single muscles rather than muscle modules. Moreover, most studies have only examined the gait of KOA patients at a single speed, leaving the way in which gait speed affects gait parameters in KOA patients unclear. Assessing this influence is crucial for determining appropriate gait speed and understanding why preferred gait speed decreases in KOA patients. In this study, we apply tensor decomposition to muscle activity data to extract muscle modules in KOA patients and elderly controls during walking at different speeds. We found a muscle module comprising hip adductors and back muscles that activate bimodally in a gait cycle, specific to KOA patients when they increase their walking speed. These findings may provide valuable insights for rehabilitation for KOA patients.
摘要：
本研究使用张量分解研究了影像学和无症状性膝骨关节炎（KOA）患者步行速度增加所涉及的肌肉模块。人体具有冗余，这是实现具有比必要的更多自由度的期望运动的属性。肌肉模块假设是对这种冗余的建议解决方案。虽然以前的研究已经检查了肌肉骨骼疾病如KOA的病理性肌肉活动调制，他们专注于单一肌肉而不是肌肉模块。此外，大多数研究只在单一速度下检查了KOA患者的步态，尚不清楚步态速度影响KOA患者步态参数的方式。评估这种影响对于确定合适的步态速度和理解为什么KOA患者的首选步态速度降低至关重要。在这项研究中,我们将张量分解应用于肌肉活动数据，以提取KOA患者和老年对照组在不同速度行走过程中的肌肉模块。我们发现了一个肌肉模块，包括臀部内收肌和背部肌肉，在步态周期中双峰激活，特定于KOA患者，当他们增加他们的步行速度。这些发现可能为KOA患者的康复提供有价值的见解。
