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我们能降到多低?惯性传感器数据计算的马属动物骨盆位移的采样率影响。

How low can we go? Influence of sample rate on equine pelvic displacement calculated from inertial sensor data.

机构信息

Department of Clinical Science and Services, The Royal Veterinary College, North Mymms, Hatfield, Hertfordshire, UK.

Department of Clinical Studies New Bolton Center, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA, USA.

出版信息

Equine Vet J. 2021 Sep;53(5):1075-1081. doi: 10.1111/evj.13371. Epub 2020 Nov 23.

Abstract

BACKGROUND

Low-cost sensor devices are often limited in terms of sample rate. Based on signal periodicity, the Nyquist theorem allows determining the minimum theoretical sample rate required to adequately capture cyclical events, such as pelvic movement in trotting horses.

OBJECTIVES

To quantify the magnitude of errors arising with reduced sample rates when capturing biological signals using the example of pelvic time-displacement series and derived minima and maxima used to quantify movement asymmetry in lame horses.

STUDY DESIGN

Data comparison.

METHODS

Root mean square (RMS) errors between the 'reference' time-displacement series, captured with a validated inertial sensor at 100 Hz sample rate, and down-sampled time-series (8 Hz to 50 Hz) are calculated. Accuracy and precision are determined for maxima and minima derived from the time-displacement series.

RESULTS

Average RMS errors are <2 mm at 50 Hz sample rate, <4 mm at 40 Hz, <7 mm between 25 and 35 Hz, and increase to up to 20 mm at 20 Hz and below. Accuracy for maxima and minima is generally below 1mm. Precision is 1 mm at 50 Hz sample rate, 3 mm at 40Hz and ≥9 mm at 20 Hz and below.

MAIN LIMITATIONS

Only sample rate, no other sensor parameters were investigated.

CONCLUSIONS

Sample rate related errors for inertial sensor derived time-displacement series of pelvic movement are <2mm at 50 Hz, a rate that many low-cost loggers, smartphones or wireless sensors can sustain hence rendering these devices valid options for quantifying parameters relevant for lameness examinations in horses.

摘要

背景

低成本传感器设备的采样率通常较低。根据信号周期性,奈奎斯特定理允许确定为充分捕获周期性事件(例如,跑步马的骨盆运动)所需的最小理论采样率。

目的

以骨盆时间位移系列为例,量化使用较低采样率捕获生物信号时产生的误差幅度,并得出用于量化跛行马运动不对称性的最小值和最大值。

研究设计

数据比较。

方法

计算“参考”时间位移系列(使用经过验证的惯性传感器以 100Hz 的采样率捕获)与降采样时间序列(8Hz 至 50Hz)之间的均方根(RMS)误差。确定从时间位移系列得出的最大值和最小值的准确性和精密度。

结果

在 50Hz 采样率时,平均 RMS 误差<2mm,在 40Hz 时<4mm,在 25Hz 至 35Hz 之间<7mm,在 20Hz 及以下时增加到高达 20mm。最大值和最小值的准确性通常低于 1mm。在 50Hz 采样率时,精度为 1mm,在 40Hz 时为 3mm,在 20Hz 及以下时为≥9mm。

主要局限性

仅研究了采样率,没有其他传感器参数。

结论

惯性传感器衍生的骨盆运动时间位移系列的采样率相关误差在 50Hz 时<2mm,许多低成本记录器、智能手机或无线传感器都可以维持该速率,因此这些设备是量化马匹跛行检查相关参数的有效选择。

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