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采样率、滤波和扭矩起始检测对股四头肌扭矩发展速率和扭矩稳定性的影响。

Effect of Sampling Rate, Filtering, and Torque Onset Detection on Quadriceps Rate of Torque Development and Torque Steadiness.

机构信息

Department of Physical Therapy, University of Kentucky, Lexington, KY 40536, USA.

Department of Statistics, University of Kentucky, Lexington, KY 40536, USA.

出版信息

Sensors (Basel). 2024 Jun 30;24(13):4250. doi: 10.3390/s24134250.

DOI:10.3390/s24134250
PMID:39001029
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11243863/
Abstract

Quadriceps rate of torque development (RTD) and torque steadiness are valuable metrics for assessing explosive strength and the ability to control force over a sustained period of time, which can inform clinical assessments of knee function. Despite their widespread use, there is a significant gap in standardized methodology for measuring these metrics, which limits their utility in comparing outcomes across different studies and populations. To address these gaps, we evaluated the influence of sampling rates, signal filtering, and torque onset detection on RTD and torque steadiness. Twenty-seven participants with a history of a primary anterior cruciate ligament reconstruction (N = 27 (11 male/16 female), age = 23 ± 8 years, body mass index = 26 ± 4 kg/m) and thirty-two control participants (N = 32 (13 male/19 female), age = 23 ± 7 years, body mass index = 23 ± 3 kg/m) underwent isometric quadriceps strength testing, with data collected at 2222 Hz on an isokinetic dynamometer. The torque-time signal was downsampled to approximately 100 and 1000 Hz and processed using a low-pass, zero-lag Butterworth filter with a range of cutoff frequencies spanning 10-200 Hz. The thresholds used to detect torque onset were defined as 0.1 Nm, 1 Nm, and 5 Nm. RTD between 0 and 100 ms, 0 and 200 ms, and 40-160 ms was computed, as well as absolute and relative torque steadiness. Relative differences were computed by comparing all outcomes to the "gold standard" values computed, with a sampling rate of 2222 Hz, a cutoff frequency in the low-pass filter of 150 Hz, and torque onset of 1 Nm, and compared utilizing linear mixed models. While all combinations of signal collection and processing parameters reached statistical significance ( < 0.05), these differences were consistent between injured and control limbs. Additionally, clinically relevant differences (+/-10%) were primarily observed through torque onset detection methods and primarily affected RTD between 0 and 100 ms. Although measurements of RTD and torque steadiness were generally robust against diverse signal collection and processing parameters, the selection of torque onset should be carefully considered, especially in early RTD assessments that have shorter time epochs.

摘要

股四头肌的扭矩发展速率(RTD)和扭矩稳定性是评估爆发力和在持续时间内控制力量能力的有价值指标,可用于临床评估膝关节功能。尽管这些指标应用广泛,但在测量这些指标的标准化方法方面仍存在显著差距,这限制了它们在比较不同研究和人群结果方面的效用。为了解决这些差距,我们评估了采样率、信号滤波和扭矩起始检测对 RTD 和扭矩稳定性的影响。27 名有初次前交叉韧带重建病史的参与者(N=27(11 名男性/16 名女性),年龄=23±8 岁,体重指数=26±4 kg/m2)和 32 名对照参与者(N=32(13 名男性/19 名女性),年龄=23±7 岁,体重指数=23±3 kg/m2)接受了等速测力测试,数据在等速测力计上以 2222 Hz 采集。扭矩-时间信号被下采样至约 100 和 1000 Hz,并使用截止频率范围为 10-200 Hz 的低通、零滞后巴特沃斯滤波器进行处理。用于检测扭矩起始的阈值定义为 0.1 Nm、1 Nm 和 5 Nm。计算了 0 到 100 ms、0 到 200 ms 和 40-160 ms 之间的 RTD,以及绝对和相对扭矩稳定性。通过将所有结果与使用 2222 Hz 采样率、低通滤波器截止频率为 150 Hz 和 1 Nm 扭矩起始的“金标准”值进行比较,计算了相对差异,并利用线性混合模型进行比较。虽然所有信号采集和处理参数的组合都达到了统计学意义(<0.05),但这些差异在受伤和对照肢体之间是一致的。此外,临床相关差异(±10%)主要通过扭矩起始检测方法观察到,主要影响 0 到 100 ms 之间的 RTD。虽然 RTD 和扭矩稳定性的测量通常对各种信号采集和处理参数具有鲁棒性,但应仔细考虑扭矩起始的选择,尤其是在早期 RTD 评估中,其时间窗更短。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdca/11243863/6bee881a89c6/sensors-24-04250-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdca/11243863/4a3c1a944231/sensors-24-04250-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdca/11243863/445a3f5ff9a0/sensors-24-04250-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdca/11243863/4efbdafac00e/sensors-24-04250-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdca/11243863/07955ca71e83/sensors-24-04250-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdca/11243863/5284c42d1baa/sensors-24-04250-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdca/11243863/2af559914adc/sensors-24-04250-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdca/11243863/6bee881a89c6/sensors-24-04250-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdca/11243863/4a3c1a944231/sensors-24-04250-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdca/11243863/445a3f5ff9a0/sensors-24-04250-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdca/11243863/4efbdafac00e/sensors-24-04250-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdca/11243863/07955ca71e83/sensors-24-04250-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdca/11243863/5284c42d1baa/sensors-24-04250-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdca/11243863/2af559914adc/sensors-24-04250-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdca/11243863/6bee881a89c6/sensors-24-04250-g007.jpg

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