Ansai Juliana Hotta, de Andrade Larissa Pires, Rossi Paulo Giusti, Nakagawa Theresa Helissa, Vale Francisco Assis Carvalho, Rebelatto José Rubens
Federal University of Mato Grosso do Sul.
Federal University of São Carlos.
Motor Control. 2019 Jan 1;23(1):1-12. doi: 10.1123/mc.2017-0015.
This study compared performances of timed up and go test subtasks between 40 older people with preserved cognition, 40 with mild cognitive impairment, and 38 with mild Alzheimer's disease. The assessment consisted of anamneses and timed up and go test subtasks (sit-to-stand, walking forward, turn, walking back, and turn-to-sit). Data were captured by Qualisys Track Manager software and processed by Visual3D software. The MATLAB program was applied to detect and analyze timed up and go test subtasks. All subtasks differentiated people with Alzheimer's disease and preserved cognition, except the sit-to-stand subtask, which did not distinguish any group. The walking forward subtask differed older people with preserved cognition from mild cognitive impairment, specifically on minimum peak of knee, average value of knee, and hip (pitch axis) during stance phase. The walking back, turn, and turn-to-sit subtasks distinguished subjects with Alzheimer's disease from mild cognitive impairment. The separated analysis of transition and walking subtasks is important in identifying mobility patterns among cognitive profiles.
本研究比较了40名认知功能正常的老年人、40名轻度认知障碍患者和38名轻度阿尔茨海默病患者在计时起立行走测试子任务中的表现。评估包括问诊和计时起立行走测试子任务（从坐到站、向前走、转身、向后走以及转身坐下）。数据由Qualisys Track Manager软件采集，并由Visual3D软件处理。MATLAB程序用于检测和分析计时起立行走测试子任务。除了从坐到站的子任务无法区分任何组外，所有子任务都能区分阿尔茨海默病患者和认知功能正常的人。向前走子任务能区分认知功能正常的老年人和轻度认知障碍患者，特别是在站立阶段的膝关节最小峰值、膝关节平均值和髋关节（俯仰轴）方面。向后走、转身和转身坐下子任务能区分阿尔茨海默病患者和轻度认知障碍患者。对过渡和行走子任务进行单独分析对于识别不同认知状况下的运动模式很重要。
