并非所有设备都是平等的:同时收集三个三轴加速度计以不同频率采样的数据

IF 1.1 4区 医学 Q4 ENGINEERING, MECHANICAL
A. Gruber, L. Marotta, James McDonnell, J. Reenalda
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引用次数: 3

摘要

可穿戴设备技术的激增使人们能够在实验室外收集跑步步态数据,用于商业、临床和教练应用。然而,低采样频率会干扰精确测量峰值加速度大小,并且在使用较低采样设备的长时间运行期间跟踪相对变化的能力是未知的。本研究的目的是比较在不同采样频率下同时测量的峰值合成加速度,并评估不同采样频率是否可以在20分钟的跑步机跑步中跟踪峰值加速度的相似相对变化。17名参与者在跑步机上以自主选择的“轻松”配速跑了20分钟(平均 ± SD = 2.6 ± 0.4 m s−1)。三个研究级三轴加速度计(“HiRes” = 1200 Hz,“MedRes” = 462 Hz和“LoRes” = 100 Hz)固定在三个解剖位置(胫骨、下背部、前额)中的每一个。在每个位置比较3至18分钟内每个装置的平均峰值合成加速度(线性混合模型,α = 0.050)。没有观察到显著的设备与时间点的相互作用(p > 0.999)。所有三个位置的采样频率的显著主要影响(HiRes > MedRes > LoRes;p < 0.001)证实了对峰值合成加速度的低采样频率的低估。然而,时间的显著主要影响表明,胫骨采样频率之间的峰值合成加速度随时间变化相似(p = 0.010)和水头(p = 0.002),但不是下背部(p = 0.318)。将HiRes下采样到400和100 Hz将MedRes和LoRes信号中对结果峰值的低估降低了<7.7%。这项研究证实,可穿戴设备的采样频率会显著影响峰值合成加速度,并证明在较低采样频率和尾部位置捕获的信号会产生更大的影响。尽管有这些影响,本研究谨慎地支持使用≥100 Hz采样频率,用于研究、临床和教练应用中“轻松”长时间跑步期间的个人峰值内合成加速度跟踪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
All devices are not created equal: Simultaneous data collection of three triaxial accelerometers sampling at different frequencies
The surge of wearable device technology has enabled out-of-the-lab collection of running gait data for commercial, clinical, and coaching applications. However, low sampling frequencies interfere with measuring peak acceleration magnitudes accurately, and the ability to track relative changes during a prolonged run with lower sampling devices is unknown. The purposes of this study were to compare peak resultant acceleration measured simultaneously at different sampling frequencies and evaluate if different sampling frequencies could track similar relative changes in peak acceleration over a 20-min treadmill run. Seventeen participants ran on a treadmill at a self-selected, “easy” pace for 20-min (mean ± SD = 2.6 ± 0.4 m s−1). Three research-grade, triaxial accelerometers (“HiRes” = 1200 Hz, “MedRes” = 462 Hz, and “LoRes” = 100 Hz) were secured to each of three anatomical locations (tibia, low-back, forehead). Mean peak resultant accelerations from each device during minutes 3 to 18 were compared within each location (linear mixed model, α = 0.050). No significant device by timepoint interaction was observed ( p > 0.999). A significant main effect of sampling frequency at all three locations (HiRes > MedRes > LoRes; p < 0.001) confirmed the underestimation of low sampling frequencies on peak resultant acceleration. However, the significant main effect of time indicated that peak resultant acceleration changed similarly over time between sampling frequencies at the tibia ( p = 0.010) and head ( p = 0.002), but not the low-back ( p = 0.318). Downsampling HiRes to 400 and 100 Hz reduced the underestimation of the resultant peaks within the MedRes and LoRes signals by <7.7% across anatomical locations. This study confirms sampling frequency of wearable devices significantly affects peak resultant acceleration and demonstrates these effects are greater for signals captured at lower sampling frequencies and caudal locations. Despite these effects, this study cautiously supports the use of ≥100 Hz sampling frequencies for within-individual peak resultant acceleration tracking during “easy” prolonged runs for research, clinical, and coaching applications.
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来源期刊
CiteScore
3.50
自引率
20.00%
发文量
51
审稿时长
>12 weeks
期刊介绍: The Journal of Sports Engineering and Technology covers the development of novel sports apparel, footwear, and equipment; and the materials, instrumentation, and processes that make advances in sports possible.
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