Feng Yuanyuan, Wong Christopher K, Janeja Vandana, Kuber Ravi, Mentis Helena M
Department of Information Systems, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD, 21250, USA.
Gait Posture. 2017 Mar;53:11-16. doi: 10.1016/j.gaitpost.2016.12.014. Epub 2016 Dec 15.
Accelerometers have shown great promise and popularity for monitoring gait. However, the accuracy of accelerometers for gait analysis in slow walking conditions is largely unknown. In this study, we compared the accuracy of three accelerometers recommended for gait analysis - Axivity AX3, APDM Opal, and the Actigraph wGT3X-BT, by holding the step-count algorithm constant. We evaluated device accuracy in four minutes of treadmill walking at the speeds of 0.9m/s, 1.1m/s, and 1.3m/s. We constructed a symbolization of the gait data to count the steps using Piecewise Aggregate Approximation and compared the estimated step counts with observer counted steps from video recordings. Our results highlight the variation between the performance of devices - the Axivity AX3 provides more accurate step counts than the other two devices. In this, we provide evidence for future scientific teams to make decisions on selecting accelerometers which can more accurately measure steps taken at slower walking speeds, and suggest ways to improve the design of algorithms and accelerometers.
加速度计在监测步态方面已展现出巨大潜力并广受欢迎。然而，在慢走条件下用于步态分析的加速度计的准确性在很大程度上尚不清楚。在本研究中，我们通过保持步数计算算法不变，比较了三种推荐用于步态分析的加速度计——Axivity AX3、APDM Opal和Actigraph wGT3X - BT的准确性。我们在跑步机上以0.9米/秒、1.1米/秒和1.3米/秒的速度行走四分钟，评估了设备的准确性。我们使用分段聚合近似法构建了步态数据的符号化表示以计算步数，并将估计的步数与视频记录中观察者计数的步数进行比较。我们的结果突出了设备性能之间的差异——Axivity AX3提供的步数计数比其他两种设备更准确。在此，我们为未来的科研团队在选择能够更准确测量慢走速度下所走步数的加速度计方面提供了决策依据，并提出了改进算法和加速度计设计的方法。
