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Phase-Dependent Effects of Closed-Loop Tactile Feedback on Gait Stability in Parkinson's Disease.

ABSTRACT: Gait disturbances in people with Parkinson's disease (PD) are a major cause for functional dependence and have recently been shown to be the largest risk factor for falls, institutionalization and death in PD. The use of external cues has been successful at improving gait in people with PD, but the effect of external cues on gait stability is unclear. We examined whether different forms of cueing, open-loop and closed-loop, influenced the local dynamic stability of three critical phases of gait. Forty-three adults with PD completed six, two-minute long walking trials in the following cued conditions: no cue (B), open-loop cueing, fixed auditory cue (OL), closed-loop cueing, tactile feedback delivered to wrist when the ipsilateral foot contacted with the ground (CL). Conditions were performed with and without a cognitive task. Kinematic data were recorded with inertial sensors. Only CL cueing was associated with changes in trunk stability, and these changes were only evident during the weight transfer phase of gait. Both OL and CL caused reductions in overall gait speed, stride length, and an increase in stride time. While CL cueing significantly influenced local dynamic stability during weight transfer, it remains unknown whether these changes are associated with more or less global stability. Future research will explore the clinical implications.

SUBMITTER: Fino PC

PROVIDER: S-EPMC7771239 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Gait Stability Has Phase-Dependent Dual-Task Costs in Parkinson's Disease.

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Project description: Not available

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Project description:This article experimentally investigates the potential of using flexible, inductance-based contraction sensors in the closed-loop motion control of soft robots. Accurate motion control remains a highly challenging task for soft robotic systems. Precise models of the actuation dynamics and environmental interactions are often unavailable. This renders open-loop control impossible, while closed-loop control suffers from a lack of suitable feedback. Conventional motion sensors, such as linear or rotary encoders, are difficult to adapt to robots that lack discrete mechanical joints. The rigid nature of these sensors runs contrary to the aspirational benefits of soft systems. As truly soft sensor solutions are still in their infancy, motion control of soft robots has so far relied on laboratory-based sensing systems such as motion capture, electromagnetic (EM) tracking, or Fiber Bragg Gratings. In this article, we used embedded flexible sensors known as Smart Braids to sense the contraction of McKibben muscles through changes in inductance. We evaluated closed-loop control on two systems: a revolute joint and a planar, one degree of freedom continuum manipulator. In the revolute joint, our proposed controller compensated for elasticity in the actuator connections. The Smart Braid feedback allowed motion control with a steady-state root-mean-square (RMS) error of [1.5]°. In the continuum manipulator, Smart Braid feedback enabled tracking of the desired tip angle with a steady-state RMS error of [1.25]°. This work demonstrates that Smart Braid sensors can provide accurate position feedback in closed-loop motion control suitable for field applications of soft robotic systems.

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