Moreira Juliana, Cunha Bruno, Félix José, Santos Rubim, Sousa Andreia S P
CIR, E2S, Polytechnic of Porto, Rua Dr. António Bernardino de Almeida, 4249-015 Porto, Portugal.
Research Center in Physical Activity, Health and Leisure, Faculty of Sports, University of Porto, 4200-450 Porto, Portugal.
Biosensors (Basel). 2025 Sep 19;15(9):621. doi: 10.3390/bios15090621.
The Timed Up and Go (TUG) test is used to assess mobility in older adults, but its reliance on completion time limits its insight into detailed movement patterns that could serve as early indicators of functional decline. This study aimed to identify lower limb and trunk kinematic biomarkers during the TUG test that distinguish between older adults with and without functional disability, emphasizing the potential for wearable sensor applications. Sixty adults aged 60+ participated in this cross-sectional study. Three-dimensional lower limb and trunk range of motion (ROM), velocity, center of mass (CoM) displacement, and velocity were analyzed using an optoelectronic system across TUG subphases: sit-to-walk, walk-forward, turn, walk-back, and turn-to-sit. Principal component analysis identified eleven principal components (PCs), explaining 84.33% of the total variance. PCs included sagittal hip and knee motion and CoM velocity during turn-to-sit and walking (PC1); tri-dimensional trunk velocity during turning, walk-back, and sit-to-walk transitions (PC2, PC4, PC6); sagittal knee and hip velocity in sit-to-walk (PC3); and frontal and transverse plane knee ROM and velocity during turning (PC5). Significant differences between functional disability groups were found for PC1 and PC4. These findings provide benchmark data for developing and validating wearable biosensors aimed at monitoring kinematic biomarkers.
定时起立行走（TUG）测试用于评估老年人的活动能力，但其对完成时间的依赖限制了对详细运动模式的洞察，而这些运动模式可能是功能衰退的早期指标。本研究旨在识别TUG测试期间区分有功能残疾和无功能残疾老年人的下肢和躯干运动学生物标志物，强调可穿戴传感器应用的潜力。60名60岁及以上的成年人参与了这项横断面研究。使用光电系统分析了TUG测试各子阶段（从坐到走、向前走、转弯、向后走、再转回到坐）的三维下肢和躯干运动范围（ROM）、速度、质心（CoM）位移和速度。主成分分析确定了11个主成分（PC），解释了总方差的84.33%。这些主成分包括转回到坐和行走过程中的矢状面髋部和膝部运动以及质心速度（PC1）；转弯、向后走和从坐到走转换过程中的三维躯干速度（PC2、PC4、PC6）；从坐到走过程中的矢状面膝部和髋部速度（PC3）；以及转弯过程中额状面和横断面的膝部ROM和速度（PC5）。在PC1和PC4方面发现了功能残疾组之间的显著差异。这些发现为开发和验证旨在监测运动学生物标志物的可穿戴生物传感器提供了基准数据。
