Oregon Center for Aging and Technology, Department of Neurology, Oregon Health & Science University, Portland, OR, USA.
Neurology. 2012 Jun 12;78(24):1946-52. doi: 10.1212/WNL.0b013e318259e1de.
To determine whether unobtrusive long-term in-home assessment of walking speed and its variability can distinguish those with mild cognitive impairment (MCI) from those with intact cognition.
Walking speed was assessed using passive infrared sensors fixed in series on the ceiling of the homes of elderly individuals participating in the Intelligent Systems for Assessing Aging Change (ISAAC) cohort study. Latent trajectory models were used to analyze weekly mean speed and walking speed variability (coefficient of variation [COV]).
ISAAC participants living alone included 54 participants with intact cognition, 31 participants with nonamnestic MCI (naMCI), and 8 participants with amnestic MCI at baseline, with a mean follow-up of 2.6 ± 1.0 years. Trajectory models identified 3 distinct trajectories (fast, moderate, and slow) of mean weekly walking speed. Participants with naMCI were more likely to be in the slow speed group than in the fast (p = 0.01) or moderate (p = 0.04) speed groups. For COV, 4 distinct trajectories were identified: group 1, the highest baseline and increasing COV followed by a sharply declining COV; groups 2 and 3, relatively stable COV; and group 4, the lowest baseline and decreasing COV. Participants with naMCI were more likely to be members of either highest or lowest baseline COV groups (groups 1 or 4), possibly representing the trajectory of walking speed variability for early- and late-stage MCI, respectively.
Walking speed and its daily variability may be an early marker of the development of MCI. These and other real-time measures of function may offer novel ways of detecting transition phases leading to dementia.
确定是否可以通过非侵入性的长期居家步行速度及其变化的评估来区分轻度认知障碍（MCI）患者和认知正常者。
使用固定在老年人家庭天花板上的一系列被动红外传感器来评估步行速度。使用潜在轨迹模型分析每周平均速度和步行速度变化（变异系数[COV]）。
ISAAC 参与者中包括 54 名认知正常的独居者、31 名非遗忘性 MCI（naMCI）参与者和 8 名遗忘性 MCI 参与者，平均随访 2.6±1.0 年。轨迹模型确定了每周平均步行速度的 3 个不同轨迹（快、中、慢）。与快（p=0.01）或中（p=0.04）速度组相比，naMCI 参与者更有可能处于慢速度组。对于 COV，确定了 4 个不同的轨迹：第 1 组，基线最高且 COV 增加，随后 COV 急剧下降；第 2 组和第 3 组，COV 相对稳定；第 4 组，基线最低且 COV 降低。naMCI 参与者更有可能属于基线 COV 最高或最低的组（第 1 组或第 4 组），这可能分别代表早、晚期 MCI 的步行速度变化轨迹。
步行速度及其日常变化可能是 MCI 发展的早期标志物。这些和其他实时功能测量可能为检测导致痴呆的过渡阶段提供新方法。
