Bayat Sayeh, Mihailidis Alex
Institute of Biomedical Engineering University of Toronto Toronto Ontario Canada.
KITE Research Institute, Toronto Rehabilitation Institute Toronto Ontario Canada.
Alzheimers Dement (Amst). 2021 May 13;13(1):e12187. doi: 10.1002/dad2.12187. eCollection 2021.
People with dementia (PWD) often become disoriented, which increases their risk of getting lost. This article explores the extent to which we can predict future whereabouts of PWD by learning from their past mobility patterns using Global Positioning System (GPS) tracking devices.
Seven older adults with dementia and eight healthy older adults completed 8 weeks of GPS data collection. We computed the probability that an appropriate algorithm can correctly predict the participant's future destinations using spatial and temporal patterns in each participant's GPS trajectories.
Relying on both spatial and temporal patterns, our results suggest that a 4-week record of mobility patterns displays 95% potential predictability across the dementia group, which is significantly higher than 92% potential predictability among the controls, t(13) = -3.39, < .01, d = -1.75. That is, we can hope to be able to predict destinations of PWD about 95% of the time and destinations of controls about 92% of the time.
Our findings on predictability of mobility patterns among PWD offer new perspectives on predictive mobility models that can be used to locate missing persons with dementia.
患有痴呆症的人（PWD）常常会迷失方向，这增加了他们走失的风险。本文探讨了通过使用全球定位系统（GPS）跟踪设备从他们过去的移动模式中学习，我们能够在多大程度上预测PWD未来的行踪。
七名患有痴呆症的老年人和八名健康的老年人完成了为期8周的GPS数据收集。我们使用每个参与者GPS轨迹中的空间和时间模式，计算了一种合适的算法能够正确预测参与者未来目的地的概率。
依靠空间和时间模式，我们的结果表明，痴呆症组中4周的移动模式记录显示出95%的潜在可预测性，这显著高于对照组中的92%的潜在可预测性，t(13) = -3.39，p <.01，d = -1.75。也就是说，我们有望能够在大约95%的时间里预测PWD的目的地，在大约92%的时间里预测对照组的目的地。
我们关于PWD移动模式可预测性的研究结果为可用于定位走失痴呆症患者的预测性移动模型提供了新的视角。
