TY - JOUR
T1 - Assessment of Human Dynamic Gait Stability with a Lower Extremity Assistive Device
AU - Chinimilli, Prudhvi Tej
AU - Rezayat Sorkhabadi, Seyed Mostafa
AU - Zhang, Wenlong
N1 - Funding Information:
Manuscript received February 12, 2019; revised July 2, 2019 and October 28, 2019; accepted November 19, 2019. Date of publication January 29, 2020; date of current version March 6, 2020. This work was supported in part by the National Science Foundation under Grant IIS-1756031. (Prudhvi Tej Chinimilli and Seyed Mostafa Rezayat Sorkhabadi contributed equally to this work.) (Corresponding author: Wenlong Zhang.) The authors are with The Polytechnic School, Ira A. Fulton Schools of Engineering, Arizona State University, Mesa, AZ 85212 USA (e-mail: prudhvi.chinimilli@asu.edu; srezayat@asu.edu; wenlong.zhang@asu.edu). Digital Object Identifier 10.1109/TNSRE.2020.2970207
Publisher Copyright:
© 2001-2011 IEEE.
PY - 2020/3
Y1 - 2020/3
N2 - This paper focuses on assessing gait stability by metrics derived from dynamical systems theory to understand the influence of unilateral robot assistance on the human walking pattern. A motorized assistive robot is applied to the right knee joint to provide stance support. The metrics related to global stability (the maximum Floquet multiplier, max FM), local stability (short-term and long-term divergence exponents, $\lambda _{\text {s}}$ and $\lambda _{\text {l}}$ ), and variability (median absolute deviation, MAD) are considered. These metrics are derived for bilateral hip, knee, and ankle joint angles. Additionally, a biomechanical metric, the minimum margin of stability is assessed. Experiments are conducted on 11 healthy participants with different robot controllers. The max FM and $\lambda _{\text {s}}$ yield statistically significant results, showing that the unassisted (left) leg is more stable in right knee assistance conditions when compared to the normal walking condition due to inter-limb coordination. Moreover, MAD and $\lambda _{\text {l}}$ show that the variability and chaotic order of walking pattern during assistance are lower than those of normal walking. The proposed control strategy (automatic impedance tuning, AIT) improves local and orbital gait stability compared to existing controllers such as finite-state machine (FSM). The assessment of dynamic gait stability presented in this paper provides insights for further improving control strategies of assistive robots to help a user reach improved gait stability while maintaining appropriate variability.
AB - This paper focuses on assessing gait stability by metrics derived from dynamical systems theory to understand the influence of unilateral robot assistance on the human walking pattern. A motorized assistive robot is applied to the right knee joint to provide stance support. The metrics related to global stability (the maximum Floquet multiplier, max FM), local stability (short-term and long-term divergence exponents, $\lambda _{\text {s}}$ and $\lambda _{\text {l}}$ ), and variability (median absolute deviation, MAD) are considered. These metrics are derived for bilateral hip, knee, and ankle joint angles. Additionally, a biomechanical metric, the minimum margin of stability is assessed. Experiments are conducted on 11 healthy participants with different robot controllers. The max FM and $\lambda _{\text {s}}$ yield statistically significant results, showing that the unassisted (left) leg is more stable in right knee assistance conditions when compared to the normal walking condition due to inter-limb coordination. Moreover, MAD and $\lambda _{\text {l}}$ show that the variability and chaotic order of walking pattern during assistance are lower than those of normal walking. The proposed control strategy (automatic impedance tuning, AIT) improves local and orbital gait stability compared to existing controllers such as finite-state machine (FSM). The assessment of dynamic gait stability presented in this paper provides insights for further improving control strategies of assistive robots to help a user reach improved gait stability while maintaining appropriate variability.
KW - Dynamic stability
KW - assistive devices
KW - biomechanics
KW - nonlinear dynamics
KW - rehabilitation
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U2 - 10.1109/TNSRE.2020.2970207
DO - 10.1109/TNSRE.2020.2970207
M3 - Article
C2 - 32011260
AN - SCOPUS:85081926661
SN - 1534-4320
VL - 28
SP - 669
EP - 678
JO - IEEE Transactions on Neural Systems and Rehabilitation Engineering
JF - IEEE Transactions on Neural Systems and Rehabilitation Engineering
IS - 3
M1 - 8974246
ER -