Abstract

There is an increased interest in using wearable inertial measurement units (IMUs) in clinical contexts for the diagnosis and rehabilitation of gait pathologies. Despite this interest, there is a lack of research regarding optimal sensor placement when measuring joint kinematics and few studies which examine functionally relevant motions other than straight level walking. The goal of this clinical measurement research study was to investigate how the location of IMU sensors on the lower body impact the accuracy of IMU-based hip, knee, and ankle angular kinematics. IMUs were placed on 11 different locations on the body to measure lower limb joint angles in seven participants performing the timed-up-and-go (TUG) test. Angles were determined using different combinations of IMUs and the TUG was segmented into different functional movements. Mean bias and root mean square error values were computed using generalized estimating equations comparing IMU-derived angles to a reference optical motion capture system. Bias and RMSE values vary with the sensor position. This effect is partially dependent on the functional movement analyzed and the joint angle measured. However, certain combinations of sensors produce lower bias and RMSE more often than others. The data presented here can inform clinicians and researchers of placement of IMUs on the body that will produce lower error when measuring joint kinematics for multiple functionally relevant motions. Optimization of IMU-based kinematic measurements is important because of increased interest in the use of IMUs to inform diagnose and rehabilitation in clinical settings and at home.

Highlights

  • The importance of gait in clinical evaluation is well established

  • Bias and root mean square error (RMSE) values between joint angles measured by inertial measurement units (IMUs) and the reference motion capture (MOCAP) system are presented in tabular format (Tables 4–6)

  • This study evaluated the impact of IMU sensor location on lower limb joint angle accuracy and bias during the TUG

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Summary

Introduction

The importance of gait in clinical evaluation is well established. Measurement of human gait has the potential to aid clinicians in making diagnoses, targeting areas for rehabilitation, informing approaches for orthopedic surgery, and tracking rehabilitation progress [1]. While direct observation of human gait is done, the quantification of gait is more difficult but important to effectively track changes over time or compare gait to other clinical populations [2]. MOCAP is vulnerable to marker occlusion and limited capture volume, confining data collection to a dedicated laboratory space [3]. This prevents the monitoring and evaluation of patients in more realistic environments

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