University of Rennes 2, M2S-EA 7470, Rennes, FRANCE.
Clinical Investigation Center, INSERM 1414, University of Rennes 1, Rennes, FRANCE.
Med Sci Sports Exerc. 2021 Jun 1;53(6):1303-1314. doi: 10.1249/MSS.0000000000002587.
This study aimed to determine and compare the accuracy of different activity monitors in assessing intermittent outdoor walking in both healthy and clinical populations through the development and validation of processing methodologies.
In study 1, an automated algorithm was implemented and tested for the detection of short (≤1 min) walking and stopping bouts during prescribed walking protocols performed by healthy subjects in environments with low and high levels of obstruction. The following parameters obtained from activity monitors were tested, with different recording epochs0.1s/0.033s/1s/3s/10s and wearing locationsscapula/hip/wrist/ankle: GlobalSat DG100 (GS) and Qstarz BT-Q1000XT/-Q1000eX (QS) speed; ActiGraph wGT3X+ (AG) vector magnitude (VM) raw data, VM counts, and steps; and StepWatch3 (SW) steps. Furthermore, linear mixed models were developed to estimate walking speeds and distances from the monitors parameters. Study 2 validated the performance of the activity monitors and processing methodologies in a clinical population showing profile of intermittent walking due to functional limitations during outdoor walking sessions.
In study 1, GS1s, scapula, QS1s, scapula/wrist speed, and AG0.033s, hip VM raw data provided the highest bout detection rates (>96.7%) and the lowest root mean square errors in speed (≤0.4 km·h-1) and distance (<18 m) estimation. Using SW3s, ankle steps, the root mean square error for walking/stopping duration estimation reached 13.6 min using proprietary software and 0.98 min using our algorithm (total recording duration, 282 min). In study 2, using AG0.033s, hip VM raw data, the bout detection rate (95% confidence interval) reached 100% (99%-100%), and the mean (SD) absolute percentage errors in speed and distance estimation were 9% (6.6%) and 12.5% (7.9%), respectively.
GPS receivers and AG demonstrated high performance in assessing intermittent outdoor walking in both healthy and clinical populations.
本研究旨在通过开发和验证处理方法，确定和比较不同活动监测器在评估健康人群和临床人群间歇性户外行走时的准确性。
在研究 1 中，实施了一种自动算法，并对健康受试者在低和高障碍物环境中进行规定行走方案时短（≤1 分钟）行走和停止回合进行了检测和测试。使用不同的记录时段（0.1s/0.033s/1s/3s/10s）和佩戴位置（肩胛骨/臀部/手腕/脚踝）对以下活动监测器参数进行了测试：GlobalSat DG100（GS）和 Qstarz BT-Q1000XT/-Q1000eX（QS）速度；ActiGraph wGT3X+（AG）矢量幅度（VM）原始数据、VM 计数和步数；以及 StepWatch3（SW）步数。此外，还开发了线性混合模型来估计监测器参数的行走速度和距离。研究 2 验证了活动监测器和处理方法在具有间歇性行走特征的临床人群中的性能，这些人群在户外行走期间因功能限制而间歇性行走。
在研究 1 中，GS1s、肩胛骨、QS1s、肩胛骨/手腕速度以及 AG0.033s、臀部 VM 原始数据提供了最高的回合检测率（>96.7%）和最低的速度（≤0.4 km·h-1）和距离（<18 m）估计均方根误差。使用 SW3s、脚踝步数，使用专有软件时行走/停止持续时间估计的均方根误差达到 13.6 分钟，使用我们的算法达到 0.98 分钟（总记录持续时间 282 分钟）。在研究 2 中，使用 AG0.033s、臀部 VM 原始数据，回合检测率（95%置信区间）达到 100%（99%-100%），速度和距离估计的平均（SD）绝对百分比误差分别为 9%（6.6%）和 12.5%（7.9%）。
GPS 接收器和 AG 在评估健康人群和临床人群的间歇性户外行走方面表现出了很高的性能。
Zotero 插件