用于评估神经退行性疾病与慢性疾病中疲劳、睡眠及日常活动的移动交互技术
Mobile Interaction for Assessing Fatigue, Sleep, and Activity in Neurodegenerative and Chronic Diseases
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中文总结 AI 辅助
本研究利用智能手机数据分析屏幕时间和应用使用特征与患者报告结局的相关性，旨在为神经退行性疾病及慢性疾病的疲劳、睡眠等症状提供客观评估方法。
中文摘要 AI 辅助
疲劳、睡眠障碍或日常活动紊乱是神经退行性疾病（NDD）和免疫介导炎症性疾病（IMID）患者的常见症状。当前这类症状的评估通常采用基于标准化问卷的患者报告结局（PROs），患者需每隔数月完成一次。该评估方案存在诸多问题，因其主观性易产生偏差，且对变化的敏感性较低，可能无法捕捉随时间的变异。本研究探索利用智能手机数据（可作为患者与设备交互情况的代理），为上述症状提供有效、可靠且客观的评估。研究包含137名参与者，涵盖6个不同疾病组及1个健康对照组。我们采用重复测量相关性进行统计分析，分析屏幕时间和应用使用特征与参与者通过智能手机应用收集的PROs得分之间的相关性。
英文摘要
Fatigue, sleep, or disturbances in daily activities are common symptoms among patients with neurodegenerative disorders (NDD) and immune-mediated inflammatory diseases (IMID). The current assessment of such symptoms is usually conducted using patient reported outcomes (PROs) based on standardized questionnaires that patients usually complete every few months. This assessment protocol has raised some concerns, due to its propensity to exhibit biases derived from its subjectivity nature, or the low sensibility to changes, which may lead to a failure when trying to capture variability over time. In this work, we explore the use of smartphone data, which can serve as a proxy for how patients interact with their devices, to provide an effective, reliable, and objective assessment of the symptoms mentioned above. Our study comprises data from 137 participants belonging to 6 different disease groups, plus a healthy control group. We conducted statistical analysis based on repeated measures correlation, in which we analyze the correlation between screen-time and app-usage features with scores obtained from the PROs collected from the participants using a smartphone application.
发表机构
- VTT Technical Research Centre of Finland（芬兰技术研究中心）
- Newcastle upon Tyne Hospitals NHS Foundation Trust（纽卡斯尔 upon Tyne 医院 NHS 信托基金会）
- University Hospital Schleswig-Holstein（石勒苏益格-荷尔斯泰因大学医院）
- Kiel University（基尔大学）
- George Huntington Institute（乔治·亨廷顿研究所）
- Erasmus University Medical Centre（伊拉斯姆斯大学医学中心）
机构由 AI 辅助整理，请以论文原文为准。
