TY - GEN
T1 - Estimating Joint Kinematics and Muscles Forces During Robotic Rehabilitation to Detect and Counteract Reduced Ankle Mobility
AU - Peperl, Kim K.
AU - Jensen, Elisabeth R.
AU - Haddadin, Sami
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The paper presents a solution to detect active ankle joint movement while a patient undergoes therapy with a robotic lower limb rehabilitation device that neither restricts nor actively supports ankle dorsi- or plantarflexion. The presented method requires the addition of only two accelerometer sensors to the system as well as a musculoskeletal model of the lower limb. Using forward kinematics and inverse dynamics, it enables knee and ankle joint kinematic tracking in the sagittal plane and muscle force estimation. This is an extension of a previous work in which only hip joint tracking was possible and, thus, muscle force estimation was limited. The correlation results of the current validation study with 12 healthy subjects show high correlation (R=0.88± 0.09) between the kinematics estimated with the proposed method and those calculated from a gold standard motion capture setup for all three joints (hip, knee, and ankle). The correlation results of the estimated m. tibialis anterior muscle force against electromyography measurements (R = 0. 62± 0.27) are promising and a first application to a patient data set shows potential for future clinical application.
AB - The paper presents a solution to detect active ankle joint movement while a patient undergoes therapy with a robotic lower limb rehabilitation device that neither restricts nor actively supports ankle dorsi- or plantarflexion. The presented method requires the addition of only two accelerometer sensors to the system as well as a musculoskeletal model of the lower limb. Using forward kinematics and inverse dynamics, it enables knee and ankle joint kinematic tracking in the sagittal plane and muscle force estimation. This is an extension of a previous work in which only hip joint tracking was possible and, thus, muscle force estimation was limited. The correlation results of the current validation study with 12 healthy subjects show high correlation (R=0.88± 0.09) between the kinematics estimated with the proposed method and those calculated from a gold standard motion capture setup for all three joints (hip, knee, and ankle). The correlation results of the estimated m. tibialis anterior muscle force against electromyography measurements (R = 0. 62± 0.27) are promising and a first application to a patient data set shows potential for future clinical application.
UR - http://www.scopus.com/inward/record.url?scp=85176443413&partnerID=8YFLogxK
U2 - 10.1109/ICORR58425.2023.10304782
DO - 10.1109/ICORR58425.2023.10304782
M3 - Conference contribution
C2 - 37941178
AN - SCOPUS:85176443413
T3 - IEEE International Conference on Rehabilitation Robotics
BT - 2023 International Conference on Rehabilitation Robotics, ICORR 2023
PB - IEEE Computer Society
T2 - 2023 International Conference on Rehabilitation Robotics, ICORR 2023
Y2 - 24 September 2023 through 28 September 2023
ER -