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… Click to show full abstract
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.
