Data-Driven Gait Segmentation for Walking Assistance in a Lower-Limb Assistive Device
This work addresses the challenge of providing online walking assistance in lower-limb assistive devices, particularly for designing impairment-specific rehabilitation strategies, though it appears incremental as it builds on existing data-driven methods.
The authors tackled the problem of controlling hybrid systems like bipedal walkers by developing a data-driven algorithm for real-time hybrid mode determination, enabling model predictive control without predefined gait structures. They demonstrated accurate gait segmentation in human walking data, identifying contact events like heel strike and toe-off using only kinematics data from knee and hip joints.
Hybrid systems, such as bipedal walkers, are challenging to control because of discontinuities in their nonlinear dynamics. Little can be predicted about the systems' evolution without modeling the guard conditions that govern transitions between hybrid modes, so even systems with reliable state sensing can be difficult to control. We propose an algorithm that allows for determining the hybrid mode of a system in real-time using data-driven analysis. The algorithm is used with data-driven dynamics identification to enable model predictive control based entirely on data. Two examples---a simulated hopper and experimental data from a bipedal walker---are used. In the context of the first example, we are able to closely approximate the dynamics of a hybrid SLIP model and then successfully use them for control in simulation. In the second example, we demonstrate gait partitioning of human walking data, accurately differentiating between stance and swing, as well as selected subphases of swing. We identify contact events, such as heel strike and toe-off, without a contact sensor using only kinematics data from the knee and hip joints, which could be particularly useful in providing online assistance during walking. Our algorithm does not assume a predefined gait structure or gait phase transitions, lending itself to segmentation of both healthy and pathological gaits. With this flexibility, impairment-specific rehabilitation strategies or assistance could be designed.