Zhai Yuyang, Nasseri Navina, Pöttgen Jana, Gezhelbash Eghbal, Heesen Christoph, Stellmann Jan-Patrick
Institute of Neuroimmunology and Multiple Sclerosis, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany.
Department of Neurology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany.
Front Neurol. 2020 Aug 14;11:688. doi: 10.3389/fneur.2020.00688. eCollection 2020.
Mobility impairment is common in persons with multiple sclerosis (pwMS) and can be assessed with clinical tests and surveys that have restricted ecological validity. Commercial research-based accelerometers are considered to be more valuable as they measure real-life mobility. Smartphone accelerometry might be an easily accessible alternative. To explore smartphone accelerometry in comparison to clinical tests, surveys, and a wrist-worn ActiGraph in pwMS and controls. Sixty-seven pwMS and 70 matched controls underwent mobility tests and surveys. Real-life data were collected with a smartphone and an ActiGraph over 7 days. We explored different smartphone metrics in a technical validation course and computed afterward correlation between ActiGraph (steps per minute), smartphone accelerometry (variance of vector magnitude), clinical tests, and surveys. We also determined the ability to separate between patients and controls as well as between different disability groups. Based on the technical validation, we found the variance of the vector magnitude as a reliable estimate to discriminate wear time and no wear-time of the smartphone. Due to a further association with different activity levels, it was selected for real-life analyses. In the cross-sectional study, ActiGraph correlated moderately ( = 0.43, < 0.05) with the smartphone but less with clinical tests (rho between |0.211| and |0.337|). Smartphone data showed stronger correlations with age (rho = -0.487) and clinical tests (rho between |0.565| and |0.605|). ActiGraph only differed between pwMS and controls ( < 0.001) but not between disability groups. At the same time, the smartphone showed differences between pwMS and controls, between RRMS and PP-/SPMS, and between participants with/without ambulatory impairment (all < 0.001). Smartphone accelerometry provides better estimates of mobility and disability than a wrist-worn standard accelerometer in a free-living context for both controls and pwMS. Given the fact that no additional device is needed, smartphone accelerometry might be a convenient outcome of real-life ambulation in healthy individuals and chronic diseases such as MS.
行动障碍在多发性硬化症患者（pwMS）中很常见，可以通过生态效度有限的临床试验和调查来评估。基于商业研究的加速度计被认为更有价值，因为它们可以测量现实生活中的活动能力。智能手机加速度计可能是一种易于获取的替代方法。为了将智能手机加速度计与临床试验、调查以及pwMS患者和对照组佩戴的腕式ActiGraph进行比较。67名pwMS患者和70名匹配的对照者接受了行动能力测试和调查。通过智能手机和ActiGraph收集了7天的现实生活数据。我们在技术验证过程中探索了不同的智能手机指标，随后计算了ActiGraph（每分钟步数）、智能手机加速度计（矢量大小的方差）、临床试验和调查之间的相关性。我们还确定了区分患者和对照者以及不同残疾组别的能力。基于技术验证，我们发现矢量大小的方差是区分智能手机佩戴时间和非佩戴时间的可靠估计。由于它与不同活动水平进一步相关，因此被选用于现实生活分析。在横断面研究中，ActiGraph与智能手机的相关性中等（r = 0.43，P < 0.05），但与临床试验的相关性较小（rho在|0.211|和|0.337|之间）。智能手机数据与年龄（rho = -0.487）和临床试验（rho在|0.565|和|0.605|之间）的相关性更强。ActiGraph仅在pwMS患者和对照者之间存在差异（P < 0.001），但在残疾组之间没有差异。与此同时，智能手机在pwMS患者和对照者之间、复发缓解型多发性硬化症（RRMS）和原发进展型/继发进展型多发性硬化症（PP-/SPMS）之间以及有/无行走障碍的参与者之间均显示出差异（所有P < 0.001）。在自由生活环境中，对于对照者和pwMS患者，智能手机加速度计比腕式标准加速度计能更好地估计活动能力和残疾程度。鉴于无需额外设备，智能手机加速度计可能是健康个体和MS等慢性病现实生活中行走情况的便捷评估指标。
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