Estimating Lower Limb Kinematics Using a Lie Group Constrained Extended Kalman Filter with a Reduced Wearable IMU Count and Distance Measurements.

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第一作者： Luke Wicent F,Sy

第一单位： Graduate School of Biomedical Engineering, UNSW Sydney, Sydney NSW 2052, Australia.

作者： Luke Wicent F,Sy ^[1] ; Nigel H,Lovell ^[1] ; Stephen J,Redmond ^[2]

作者单位： Graduate School of Biomedical Engineering, UNSW Sydney, Sydney NSW 2052, Australia. ^[1] UCD School of Electrical and Electronic Engineering, University College Dublin, Belfield, 4 Dublin, Ireland. ^[2]

关键词 IMU Lie group constrained extended Kalman filter distance measurement gait analysis motion capture pose estimation wearable devices

主题词人类(Humans);下肢(Lower Extremity);运动(Motion)(Motion);步行(Walking)

DOI 10.3390/s20236829

PMID 33260386

发布时间 2021-03-30

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Sensors (Basel, Switzerland)

2020年20卷23期

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Estimating Lower Limb Kinematics Using a Lie Group Constrained Extended Kalman Filter with a Reduced Wearable IMU Count and Distance Measurements.

Sensors (Basel, Switzerland)

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Estimating Lower Limb Kinematics Using a Lie Group Constrained Extended Kalman Filter with a Reduced Wearable IMU Count and Distance Measurements.

Sensors (Basel, Switzerland)

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Sensors (Basel, Switzerland)

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