TY - GEN
T1 - Improving the accuracy of wearable sensors for human locomotion tracking using phase-locked regression models
AU - Duong, Ton T.H.
AU - Zhang, Huanghe
AU - Lynch, T. Sean
AU - Zanotto, Damiano
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/6
Y1 - 2019/6
N2 - The trend toward soft wearable robotic systems creates a compelling need for new and reliable sensor systems that do not require a rigid mounting frame. Despite the growing use of inertial measurement units (IMUs) in motion tracking applications, sensor drift and IMU-to-segment misalignment still represent major problems in applications requiring high accuracy. This paper proposes a novel 2-step calibration method which takes advantage of the periodic nature of human locomotion to improve the accuracy of wearable inertial sensors in measuring lower-limb joint angles. Specifically, the method was applied to the determination of the hip joint angles during walking tasks. The accuracy and precision of the calibration method were accessed in a group of N =8 subjects who walked with a custom-designed inertial motion capture system at 85% and 115% of their comfortable pace, using an optical motion capture system as reference. In light of its low computational complexity and good accuracy, the proposed approach shows promise for embedded applications, including closed-loop control of soft wearable robotic systems.
AB - The trend toward soft wearable robotic systems creates a compelling need for new and reliable sensor systems that do not require a rigid mounting frame. Despite the growing use of inertial measurement units (IMUs) in motion tracking applications, sensor drift and IMU-to-segment misalignment still represent major problems in applications requiring high accuracy. This paper proposes a novel 2-step calibration method which takes advantage of the periodic nature of human locomotion to improve the accuracy of wearable inertial sensors in measuring lower-limb joint angles. Specifically, the method was applied to the determination of the hip joint angles during walking tasks. The accuracy and precision of the calibration method were accessed in a group of N =8 subjects who walked with a custom-designed inertial motion capture system at 85% and 115% of their comfortable pace, using an optical motion capture system as reference. In light of its low computational complexity and good accuracy, the proposed approach shows promise for embedded applications, including closed-loop control of soft wearable robotic systems.
KW - Human motion analysis
KW - Inertial sensors
KW - Wearable technology
UR - http://www.scopus.com/inward/record.url?scp=85071154667&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85071154667&partnerID=8YFLogxK
U2 - 10.1109/ICORR.2019.8779428
DO - 10.1109/ICORR.2019.8779428
M3 - Conference contribution
C2 - 31374621
AN - SCOPUS:85071154667
T3 - IEEE International Conference on Rehabilitation Robotics
SP - 145
EP - 150
BT - 2019 IEEE 16th International Conference on Rehabilitation Robotics, ICORR 2019
T2 - 16th IEEE International Conference on Rehabilitation Robotics, ICORR 2019
Y2 - 24 June 2019 through 28 June 2019
ER -