Background: 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. Objective: To explore smartphone accelerometry in comparison to clinical tests, surveys, and a wrist-worn ActiGraph in pwMS and controls. Methods: 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. Results: 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 (r = 0.43, p < 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 (p < 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 p < 0.001). Conclusions: 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.

中文翻译：

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智能手机加速度计：一种智能，可靠地测量多发性硬化症和健康个体的实际体育活动。

背景：行动障碍在多发性硬化症（pwMS）患者中很常见，可以通过生态学有效性受到限制的临床测试和调查进行评估。基于商业研究的加速度计被认为具有更大的价值，因为它们可以测量现实生活中的移动性。智能手机加速度计可能是一种易于使用的替代方法。目的：与pwMS和控件中的临床测试，调查以及腕戴式ActiGraph相比，探索智能手机的加速度计。方法：对67个pwMS和70个匹配的对照进行了流动性测试和调查。在7天内使用智能手机和ActiGraph收集了真实的数据。我们在技术验证课程中探索了不同的智能手机指标，并计算了ActiGraph之间的事后相关性（每分钟步数），智能手机加速度计（矢量幅度的变化），临床测试和调查。我们还确定了在患者和对照组之间以及不同残疾组之间进行区分的能力。结果：基于技术验证，我们发现矢量幅度的方差是区分智能手机的磨损时间和无磨损时间的可靠估计。由于与不同活动水平的进一步关联，因此将其选择用于现实生活分析。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），而与临床测试的相关性较小（rho在| 0.211 |和| 0.337 |之间）。智能手机数据显示与年龄（rho = -0.487）和临床测试（rho在| 0.565 |和| 0.605 |之间）的相关性更强。ActiGraph仅在pwMS和控件之间有所不同（p <0。001），但不在残疾群体之间。同时，智能手机显示出pwMS和控件之间，RRMS和PP- / SPMS之间以及有/无移动障碍的参与者之间的差异（所有p <0.001）。结论：在自由生活的情况下，对于控件和pwMS，智能手机加速度计比腕戴式标准加速度计提供了更好的移动性和残障估计。考虑到不需要其他设备的事实，智能手机的加速度计可能是健康个体和慢性疾病（例如MS）中真实移动的便捷结果。在控件和pwMS的自由生活环境中，智能手机加速度计比腕戴式标准加速度计提供了更好的移动性和残障估计。考虑到不需要其他设备的事实，智能手机的加速度计可能是健康个体和慢性疾病（例如MS）中真实移动的便捷结果。在控件和pwMS的自由生活环境中，智能手机加速度计比腕戴式标准加速度计提供了更好的移动性和残障估计。考虑到不需要其他设备的事实，智能手机的加速度计可能是健康个体和慢性疾病（例如MS）中真实移动的便捷结果。