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Estimation of stride-by-stride spatial gait parameters using inertial measurement unit attached to the shank with inverted pendulum model
Estimation of stride-by-stride spatial gait parameters using inertial measurement unit attached to the shank with inverted pendulum model
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Estimation of stride-by-stride spatial gait parameters using inertial measurement unit attached to the shank with inverted pendulum model
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Estimation of stride-by-stride spatial gait parameters using inertial measurement unit attached to the shank with inverted pendulum model
Estimation of stride-by-stride spatial gait parameters using inertial measurement unit attached to the shank with inverted pendulum model

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Estimation of stride-by-stride spatial gait parameters using inertial measurement unit attached to the shank with inverted pendulum model
Estimation of stride-by-stride spatial gait parameters using inertial measurement unit attached to the shank with inverted pendulum model
Journal Article

Estimation of stride-by-stride spatial gait parameters using inertial measurement unit attached to the shank with inverted pendulum model

2021
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Overview
Inertial measurement unit (IMU)-based gait analysis systems have become popular in clinical environments because of their low cost and quantitative measurement capability. When a shank is selected as the IMU mounting position, an inverted pendulum model (IPM) can accurately estimate its spatial gait parameters. However, the stride-by-stride estimation of gait parameters using one IMU on each shank and the IPMs has not been validated. This study validated a spatial gait parameter estimation method using a shank-based IMU system. Spatial parameters were estimated via the double integration of the linear acceleration transformed by the IMU orientation information. To reduce the integral drift error, an IPM, applied with a linear error model, was introduced at the mid-stance to estimate the update velocity. the gait data of 16 healthy participants that walked normally and slowly were used. The results were validated by comparison with those extracted from an optical motion-capture system; the results showed strong correlation ( r > 0.9 ) and good agreement with the gait metrics (stride length, stride velocity, and shank vertical displacement). In addition, the biases of the stride length and stride velocity extracted using the motion capture system were smaller in the IPM than those in the previous method using the zero-velocity-update. The error variabilities of the gait metrics were smaller in the IPM than those in the previous method. These results indicated that the reconstructed shank trajectory achieved a greater accuracy and precision than that of previous methods. This was attributed to the IPM, which demonstrates that shank-based IMU systems with IPMs can accurately reflect many spatial gait parameters including stride velocity.
Publisher
Springer Science and Business Media LLC,Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio