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验证基于可穿戴惯性传感器的步态分析系统在矢状面测量时空参数和下肢关节运动学的准确性。

Validation of wearable inertial sensor-based gait analysis system for measurement of spatiotemporal parameters and lower extremity joint kinematics in sagittal plane.

机构信息

Department of Mechanical Engineering, TTK Center for Rehabilitation Research and Device Development (R2D2), IIT Madras, Chennai, India.

Biodesign Medical Technology, Synersense Private Limited, Ahmedabad, India.

出版信息

Proc Inst Mech Eng H. 2022 May;236(5):686-696. doi: 10.1177/09544119211072971. Epub 2022 Jan 8.


DOI:10.1177/09544119211072971
PMID:35001713
Abstract

Wearable inertial sensor-based motion analysis systems are promising alternatives to standard camera-based motion capture systems for the measurement of gait parameters and joint kinematics. These wearable sensors, unlike camera-based gold standard systems, find usefulness in outdoor natural environment along with confined indoor laboratory-based environment due to miniature size and wireless data transmission. This study reports validation of our developed (i-Sens) wearable motion analysis system against standard motion capture system. Gait analysis was performed at self-selected speed on non-disabled volunteers in indoor ( = 15) and outdoor ( = 8) environments. Two i-Sens units were placed at the level of knee and hip along with passive markers (for indoor study only) for simultaneous 3D motion capture using a motion capture system. Mean absolute percentage error (MAPE) was computed for spatiotemporal parameters from the i-Sens system versus the motion capture system as a true reference. Mean and standard deviation of kinematic data for a gait cycle were plotted for both systems against normative data. Joint kinematics data were analyzed to compute the root mean squared error (RMSE) and Pearson's correlation coefficient. Kinematic plots indicate a high degree of accuracy of the i-Sens system with the reference system. Excellent positive correlation was observed between the two systems in terms of hip and knee joint angles (Indoor: hip 3.98° ± 1.03°, knee 6.48° ± 1.91°, Outdoor: hip 3.94° ± 0.78°, knee 5.82° ± 0.99°) with low RMSE. Reliability characteristics (defined using standard statistical thresholds of MAPE) of stride length, cadence, walking speed in both outdoor and indoor environment were well within the "Good" category. The i-Sens system has emerged as a potentially cost-effective, valid, accurate, and reliable alternative to expensive, standard motion capture systems for gait analysis. Further clinical trials using the i-Sens system are warranted on participants across different age groups.

摘要

基于可穿戴惯性传感器的运动分析系统是一种有前途的替代标准基于相机的运动捕捉系统,可用于测量步态参数和关节运动学。与基于相机的黄金标准系统不同,这些可穿戴传感器由于尺寸小巧且具有无线数据传输功能,因此在户外自然环境以及受限的室内实验室环境中都很有用。本研究报告了我们开发的(i-Sens)可穿戴运动分析系统与标准运动捕捉系统的验证结果。在室内(n=15)和室外(n=8)环境中,非残疾志愿者以自选速度进行步态分析。两个 i-Sens 单元分别放置在膝盖和臀部水平,并带有被动标记(仅用于室内研究),以便使用运动捕捉系统同时进行 3D 运动捕捉。从 i-Sens 系统与作为真实参考的运动捕捉系统计算时空参数的平均绝对百分比误差(MAPE)。针对两个系统,针对正常数据绘制了步态周期运动学数据的均值和标准差图。分析关节运动学数据以计算均方根误差(RMSE)和 Pearson 相关系数。运动学图表明 i-Sens 系统具有高度的准确性。两个系统在髋关节和膝关节角度方面观察到极好的正相关性(室内:髋关节 3.98°±1.03°,膝关节 6.48°±1.91°,室外:髋关节 3.94°±0.78°,膝关节 5.82°±0.99°),RMSE 低。在室内和室外环境中,步长、步频和行走速度的可靠性特征(使用 MAPE 的标准统计阈值定义)均属于“良好”类别。i-Sens 系统已经成为一种具有成本效益、准确可靠的替代昂贵的标准运动捕捉系统的方法,可用于步态分析。需要在不同年龄组的参与者中进一步进行 i-Sens 系统的临床试验。

相似文献

[1]
Validation of wearable inertial sensor-based gait analysis system for measurement of spatiotemporal parameters and lower extremity joint kinematics in sagittal plane.

Proc Inst Mech Eng H. 2022-5

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[3]
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[8]
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[9]
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[10]
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引用本文的文献

[1]
Validity and Reliability of a Smartphone-Based Gait Assessment in Measuring Temporal Gait Parameters: Challenges and Recommendations.

Biosensors (Basel). 2025-6-20

[2]
Validity and reliability of inertial measurement units for measuring gait kinematics in older adults across varying fall risk levels and walking speeds.

BMC Geriatr. 2025-5-14

[3]
Real-world data capture of daily limb loading using force-sensing insoles: Feasibility and lessons learned.

J Biomech. 2024-3

[4]
Validity and reliability of inertial measurement units measurements for running kinematics in different foot strike pattern runners.

Front Bioeng Biotechnol. 2022-12-8

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