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Abstract Human ambulation is typically characterized during steady-state isolated tasks (e.g., walking, running, stair ambulation). However, general human locomotion comprises continuous adaptation to the varied terrains encountered during activities of daily life. To fill an important gap in knowledge that may lead to improved therapeutic and device interventions for mobility-impaired individuals, it is vital to identify how the mechanics of individuals change as they transition between different ambulatory tasks, and as they encounter terrains of differing severity. In this work, we study lower-limb joint kinematics during the transitions between level walking and stair ascent and descent over a range of stair inclination angles. Using statistical parametric mapping, we identify where and when the kinematics of transitions are unique from the adjacent steady-state tasks. Results show unique transition kinematics primarily in the swing phase, which are sensitive to stair inclination. We also train Gaussian process regression models for each joint to predict joint angles given the gait phase, stair inclination, and ambulation context (transition type, ascent/descent), demonstrating a mathematical modeling approach that successfully incorporates terrain transitions and severity. The results of this work further our understanding of transitory human biomechanics and motivate the incorporation of transition-specific control models into mobility-assistive technology.
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Augmenting Human-Inspired Phase Variables Using a Canonical Dynamical System
Accurately parameterizing human gait cycles is crucial for developing control systems for lower-limb wearable robots. Previous studies on characterizing human gait cycle investigated the use of human-inspired phase variables, but they lack robustness and adaptability to accommodate for transitions that occur between locomotor tasks. This paper proposes augmenting the traditional phase variables with a canonical dynamical system. This system considers the differences between the estimated and true thigh angular velocities, based on which the Fourier series coefficients and phase information will be dynamically updated via an adaptive frequency oscillator. Experiments with six able-bodied participants on level ground, inclines, and declines walking show that the augmented phase variable adapts to various locomotor tasks and transitions better than the traditional approach.
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- Award ID(s):
- 2340261
- PAR ID:
- 10579819
- Publisher / Repository:
- IEEE
- Date Published:
- ISSN:
- 2994-3574
- ISBN:
- 979-8-3315-0964-4
- Page Range / eLocation ID:
- 2271 to 2275
- Format(s):
- Medium: X
- Location:
- Bangkok, Thailand
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ROBIO64047.2024.10907279
