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智能手机应用程序和市售运动传感器在多发性硬化症中的准确性和精确性。

Accuracy and precision of smartphone applications and commercially available motion sensors in multiple sclerosis.

作者信息

Balto Julia M, Kinnett-Hopkins Dominique L, Motl Robert W

机构信息

Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, IL, USA.

出版信息

Mult Scler J Exp Transl Clin. 2016 Mar 4;2:2055217316634754. doi: 10.1177/2055217316634754. eCollection 2016 Jan-Dec.

Abstract

BACKGROUND

There is increased interest in the application of smartphone applications and wearable motion sensors among multiple sclerosis (MS) patients.

OBJECTIVE

This study examined the accuracy and precision of common smartphone applications and motion sensors for measuring steps taken by MS patients while walking on a treadmill.

METHODS

Forty-five MS patients (Expanded Disability Status Scale (EDSS) = 1.0-5.0) underwent two 500-step walking trials at comfortable walking speed on a treadmill. Participants wore five motion sensors: the Digi-Walker SW-200 pedometer (Yamax), the UP2 and UP Move (Jawbone), and the Flex and One (Fitbit). The smartphone applications were Health (Apple), Health Mate (Withings), and Moves (ProtoGeo Oy).

RESULTS

The Fitbit One had the best absolute (mean = 490.6 steps, 95% confidence interval (CI) = 485.6-495.5 steps) and relative accuracy (1.9% error), and absolute (SD = 16.4) and relative precision (coefficient of variation (CV) = 0.0), for the first 500-step walking trial; this was repeated with the second trial. Relative accuracy was correlated with slower walking speed for the first (-.53) and second (-.53) trials.

CONCLUSION

The results suggest that the waist-worn Fitbit One is the most precise and accurate sensor for measuring steps when walking on a treadmill, but future research is needed (testing the device across a broader range of disability, at different speeds, and in real-life walking conditions) before inclusion in clinical research and practice with MS patients.

摘要

背景

多发性硬化症(MS)患者对智能手机应用程序和可穿戴运动传感器的应用兴趣日益增加。

目的

本研究检测了常见智能手机应用程序和运动传感器在测量MS患者在跑步机上行走步数时的准确性和精确性。

方法

45例MS患者(扩展残疾状态量表(EDSS)=1.0 - 5.0)在跑步机上以舒适的步行速度进行了两次500步的行走试验。参与者佩戴了五种运动传感器:Digi-Walker SW-200计步器(Yamax)、UP2和UP Move(Jawbone)以及Flex和One(Fitbit)。智能手机应用程序有Health(苹果)、Health Mate(Withings)和Moves(ProtoGeo Oy)。

结果

在第一次500步行走试验中,Fitbit One的绝对准确性(均值=490.6步,95%置信区间(CI)=485.6 - 495.5步)和相对准确性(误差1.9%),以及绝对精确性(标准差=16.4)和相对精确性(变异系数(CV)=0.0)最佳;第二次试验重复了这一结果。第一次(-.53)和第二次(-.53)试验的相对准确性与较慢的步行速度相关。

结论

结果表明,腰部佩戴的Fitbit One是在跑步机上行走时测量步数最精确和准确的传感器,但在纳入MS患者的临床研究和实践之前,还需要进一步的研究(在更广泛的残疾范围内、不同速度以及现实生活行走条件下测试该设备)。

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