Passive Monitoring of Walking Cadence as a Novel Tool for Aging and Cognitive Health Assessment

项目摘要 尽管付出了巨大的努力，阿尔茨海默病(AD)的治疗临床试验已经 很大程度上失败了，可能是因为干预措施启动得太晚了 神经退行性变已经开始且不可逆转的过程。及早发现人 因此，阿尔茨海默病的高危人群对帮助制定预防措施尤为重要 和治疗方案。我们假设运动功能的细微变化可能有助于 作为认知障碍早期迹象的潜在生物标记物。跟踪中的更改 Cadence将能够评估潜在的运动/认知平行轨迹 下降，并可能被证明是认知能力下降的一个指标。这项研究将利用 大量收集体力活动和认知评估数据，并派生出新颖的 来自商用可穿戴设备的数字表型(目标1)。到时候我们会的 评估这些新测量与认知功能下降的相关性，以及 开发先进的机器学习模型，以识别高危人群 认知障碍(目标2)。鉴于可穿戴设备越来越受欢迎， 从当前项目开发的知识和工具可以很容易地应用于 对普通人群进行大规模的认知健康筛查。

Project Summary Despite enormous efforts, therapeutic clinical trials for Alzheimer’s disease (AD) have largely failed, possibly because interventions are initiated too late into the disease course when neurodegeneration has begun and is irreversible. Early detection of people at high risk of AD is thus particularly important to help in the effort to develop prevention and treatment options. We hypothesize that subtle changes in motor function may serve as a potential biomarker of early signs of cognitive impairment. Tracking changes in cadence will enable the assessment of potential parallel trajectories of motor/cognitive decline and may prove to be an indicator of declining cognition. This study will leverage a large collection of physical activity and cognitive assessment data, and derive novel digital phenotypes from commercially available wearable devices (Aim 1). We will then assess the correlation of these novel measures with declining cognitive function, and develop advanced machine learning models to identify people at high risk to develop cognitive impairment (Aim 2). Given the increasing popularity of wearable devices, the knowledge and tools developed from the current project could be readily applicable to the general population for the large-scale screening of cognitive health.